AI - Dancing Badger

When a project goes live, the finished result is the part everybody sees.

A new website. An ecommerce store. A campaign. A new customer journey. Something that looks polished, works properly and hopefully appears as though it was always meant to be that way.

What is less visible is everything that happened before it.

The conversations. The questions. The research. The ideas that were explored and discarded. The details somebody spotted at the last minute. The decisions that moved backwards before they moved forwards.

So we thought it would be useful to go behind the scenes at Dancing Badger and explain what actually happens when we take a digital project from an initial brief through to launch.

Not every project follows exactly the same path.

A website project is different from an ecommerce build, and both are different from a marketing campaign.

But the thinking behind them has a lot in common.

A good project isn’t a relay race where one department finishes its bit and passes the baton on. The strongest work happens when the right people are involved at the right points.

The project starts before anybody starts designing

One of the easiest mistakes in digital work is to begin with the output.

“We need a new website.”

“We need to improve our SEO.”

“We should run Google Ads.”

“We need an ecommerce store.”

Those may eventually be the right answers.

But first we need to understand the question.

What is the business trying to achieve?

Who are the customers?

What is working already?

What is getting in the way?

Is there a technical problem, a visibility problem, a conversion problem, a commercial problem — or several of those things happening together?

That initial understanding shapes almost everything that follows.

Because if we misunderstand the problem at the beginning, there is a very real risk of delivering the wrong solution extremely well.

01 Understand

Clarify the business objective, audience, existing challenges and what a successful outcome should look like.

02 Explore

Review the current position, available data, competitors, customer journeys and wider digital environment.

03 Plan

Agree priorities, scope the work and decide how the different parts of the project need to fit together.

04 Shape

Develop structure, user journeys, content direction and the ideas that will form the experience.

05 Design

Turn the thinking into something visual, usable and appropriate for the people who will actually use it.

06 Build

Develop, configure and integrate the technical parts while continuing to test assumptions from earlier stages.

07 Test

Check content, functionality, devices, journeys, tracking and the details that determine whether the finished project works properly.

08 Launch & learn

Put the work in front of real users, measure what happens and use that information to decide what comes next.

A brief tells us where to start — not necessarily where to finish

Clients normally come to us with an idea of what they need.

Sometimes that idea is already very well developed.

Sometimes the brief is effectively a problem that still needs turning into a project.

Both are perfectly normal.

Our job at the beginning is not simply to write down everything we have been asked to do and begin producing it.

We need to understand why it is being requested.

A client might ask for a redesign when the underlying issue is actually poor navigation.

They might want more website traffic when the bigger opportunity is improving the proportion of existing visitors who enquire.

They might want to advertise a particular service when search behaviour suggests customers describe that service in a completely different way.

Challenging the brief does not mean ignoring what the client wants.

It means making sure the project being built is connected to the outcome they actually care about.

Research is how we reduce expensive guesswork

Before making important decisions, we want to know as much as we reasonably can about the environment the project is entering.

That may involve existing website data.

Search behaviour.

Competitors.

Existing customer journeys.

Advertising performance.

Ecommerce data.

Previous content.

Or simply conversations with people inside the business who understand the customers better than any dashboard ever could.

The purpose is not to delay the creative work with endless research.

It is to make the creative and technical work better informed when it begins.

The earlier we understand the real problem, the less time everybody spends solving the wrong one.

The right specialists need to be involved before their ‘stage’ begins

Digital projects can look very tidy on a project plan.

Strategy first.

Then design.

Then development.

Then content.

Then SEO.

Then analytics.

Real projects are rarely that neat.

A developer may spot a technical implication while something is still being designed.

An SEO specialist may identify an important search opportunity before the site structure is agreed.

A designer may notice that the planned content hierarchy does not make sense visually.

Analytics may show that users behave very differently from the way everybody assumed.

Account management may bring context from the client that changes how a decision should be approached.

That is why collaboration matters.

The objective is not to have everybody involved in every decision.

It is to make sure the right expertise can influence the project while there is still time for that expertise to make a difference.

Client & account

Business context

Keeping the project connected to objectives, priorities, decisions and what is actually happening inside the client’s organisation.

Strategy & data

Evidence

Looking at performance, opportunities, audience behaviour and the information that should influence the direction of the project.

UX & design

Experience

Turning objectives and information into journeys, layouts and interfaces that make sense to the people using them.

Content & search

Language

Making sure the project communicates clearly while considering what customers search for and what they need to understand.

Development

Delivery

Turning the planned experience into something robust, manageable and technically capable of doing what the project requires.

Performance

What happens next

Tracking what users actually do once the project is live and using that information to challenge assumptions and identify improvements.

Collaboration without committee design

More expertise does not mean every decision needs ten opinions.

The point of bringing different disciplines together is to improve the decision, not make the process unnecessarily complicated. Clear ownership still matters. So does knowing when specialist input is useful — and when somebody simply needs to make the call and move the project forward.

Design is where strategy starts becoming visible

By the time a project reaches design, a significant amount of thinking may already have happened.

The audience.

The objectives.

The structure.

The journeys.

The actions we want people to take.

Design turns those decisions into something people can actually experience.

That is why we do not see design as decoration added after the strategy has been completed.

A design decision can change how easy it is to understand a page.

It can alter what somebody notices first.

It can make an important action obvious — or practically invisible.

And sometimes seeing the strategy represented visually exposes a problem nobody had noticed while it existed only as words on a document.

That feedback is useful.

Projects should be allowed to improve as they become more tangible.

Development is not where the thinking stops

Once a design has been approved, it can be tempting to think the difficult decisions have been made and development is simply the process of assembling them.

It rarely works like that.

Development introduces another set of questions.

How should the content be managed?

How does something behave on a smaller screen?

What happens if the client adds significantly more content later?

How should different systems communicate?

What happens when information is missing?

How do we make the feature maintainable rather than merely making it work today?

This is where the experience of people working across website development and ecommerce becomes important.

Good development is partly about writing the code.

It is also about anticipating what the project will need after launch.

Content, SEO and tracking are not jobs we want to discover at the end

Some of the most expensive project problems begin with the phrase: “We’ll sort that out later.”

Content is one example.

A layout that looks perfect with three lines of placeholder copy may behave very differently when the real information arrives.

Search is another.

If SEO only enters the conversation after the structure and URLs have been finalised, opportunities may already have been missed.

The same is true of analytics.

Knowing what should be measured before launch is considerably better than launching first and trying to reconstruct the missing data afterwards.

This is one of the reasons DB Analytics and wider performance measurement are increasingly connected to the work we do.

If success matters, we need a way to recognise it.

Launch day should not be the first time we ask how we are going to know whether the project worked.

Testing is where we deliberately look for problems

By the time a project is close to launch, everybody involved has normally spent a lot of time looking at it.

That familiarity can be dangerous.

You know where the button is, so you stop noticing whether it is obvious.

You know what a field means, so you forget somebody else may not.

You have seen the same page dozens of times, so your brain quietly corrects a typo every time you read it.

Testing means deliberately changing perspective.

Does it work technically?

Does it work across devices?

Does the content make sense?

Do forms and ecommerce journeys behave properly?

Are the important actions measurable?

And can somebody who has not spent weeks inside the project understand what they are supposed to do?

Check 01 Experience

Review navigation, user journeys, calls to action, readability and how the experience behaves across different screen sizes.

Check 02 Content

Check real copy, imagery, links, page titles, product information and the details users will actually encounter.

Check 03 Function

Test forms, ecommerce journeys, integrations, interactions and the technical behaviours the project depends upon.

Check 04 Measurement

Confirm that the important actions can be tracked so the team has useful information once real users arrive.

Then comes the part everybody sees: launch

Launch is an important moment.

It is the point where weeks or months of decisions finally become something customers can use.

But internally, we do not really think of it as the finish line.

It is the moment the project starts receiving a kind of feedback no workshop, prototype or staging site can fully reproduce: real behaviour from real users.

People may behave exactly as expected.

Or they may reveal something none of us anticipated.

A page we expected to be important may receive very little attention.

A secondary route may become one of the strongest conversion journeys.

Search behaviour may shift.

An advertising campaign may expose a weakness on a landing page.

Customers may repeatedly ask a question the new website still does not answer clearly enough.

That information is not evidence that the project failed.

It is evidence that we now know more than we did before launch.

01 Launch

The project moves from a controlled development environment into the real world.

02 Observe

Watch how people arrive, what they engage with and where journeys perform differently from expectations.

03 Learn

Combine analytics, commercial results, customer behaviour and client feedback to understand what the signals mean.

04 Improve

Decide what deserves changing, testing or developing next — then continue the cycle.

Good project management is partly about keeping all of that connected

With several disciplines contributing to a project, somebody also needs to keep sight of the whole thing.

Decisions need recording.

Dependencies need spotting.

Questions need getting to the right person.

Client feedback needs translating into clear actions.

Scope, priorities and deadlines need managing without allowing the project to become purely about administration.

That coordination is less visible than a design or a piece of development, but it has a significant effect on the quality of the finished work.

A project can contain plenty of talented individual work and still struggle if those pieces are not connected.

The process matters, but so does knowing when to adapt it

There is comfort in a perfectly defined process.

Step one.

Step two.

Step three.

Never go backwards.

Digital projects do not always behave like that.

Sometimes research changes the brief.

Sometimes design raises a strategic question.

Sometimes development reveals a better approach.

Sometimes testing exposes something that needs taking back a stage.

The process exists to give the project structure, not to prevent people from responding intelligently when new information appears.

Knowing when to follow the process — and when the project has given you a good reason to revisit something — is part of the experience an agency is there to provide.

What clients see is the outcome. Our job is everything behind it.

Most clients do not need to be involved in every internal conversation.

They should not need to know every technical decision or watch every iteration taking place behind the scenes.

But they should understand the important decisions, know why recommendations are being made and have confidence that the different parts of their project are connected.

That is ultimately what the process is there to achieve.

Not complexity for the sake of complexity.

Not endless meetings.

Not a rigid sequence of agency terminology.

A way of taking an objective, bringing the right expertise around it and gradually turning it into something useful.

Behind the scenes at Dancing Badger

The finished project might look simple. Getting to the right kind of simple usually takes a lot of thinking.

Research, strategy, design, development, content, data and client knowledge all influence the result. The value is not simply completing each stage — it is making sure those stages inform one another.

The exact process will continue to change.

The technology we use will change.

The platforms will change.

And, as we discussed in our article on how AI is changing the way we work at Dancing Badger , some of the tasks involved in delivering digital projects are already becoming faster and more automated.

What matters is that the purpose of the process stays the same.

Understand the problem properly.

Bring the right people to it.

Make informed decisions.

Build carefully.

Measure what happens.

And keep improving.

Start a project

Have something you’re trying to improve, build or solve?

You do not need to arrive with the finished brief. If you know what you are trying to achieve, we can help work out what the project needs to look like from there.

Start a conversation → Website Design Ecommerce SEO PPC DB Analytics Meet the Team

Artificial intelligence has moved very quickly from something agencies experimented with to something that is becoming part of everyday digital work.

At Dancing Badger, that has prompted a slightly different question from simply asking whether we should be using AI.

Where does it genuinely make the work better?

And, just as importantly, where does experience, judgement and human input still matter more?

Those questions are shaping how we use AI across research, analysis, content, technical work and our wider approach to digital growth strategy.

For us, the interesting thing about AI isn’t whether it can do more work. It’s whether it can give our people more time to concentrate on the work that genuinely needs their expertise.

That distinction matters.

Digital agencies have always used technology to make their work more efficient.

Analytics platforms collect millions of data points that would be impossible to process manually. Advertising platforms automate bidding and audience selection. Ecommerce platforms manage transactions, stock and customer journeys at scale.

AI is another significant step in that progression.

But it also introduces something different.

It can summarise, interpret, draft, compare, organise and suggest.

That makes it extremely useful.

It also makes knowing when not to accept the first answer increasingly important.

More suited to AI assistance More dependent on human judgement

Organise

Sorting, structuring and summarising large amounts of information.

Research

Exploring topics, questions, competitors and possible lines of investigation.

Analyse

Helping surface patterns, anomalies and relationships that deserve further attention.

Create

Supporting ideas, structures, first drafts and alternative approaches.

Interpret

Understanding what the information means within the reality of a particular client or market.

Decide

Choosing what should happen, taking responsibility for the recommendation and balancing commercial priorities.

We started with the work that takes time

Some agency tasks are valuable because of the thinking involved.

Others are simply necessary stages you have to complete before you can reach the interesting part.

Gathering information from several sources.

Organising a large volume of notes.

Comparing different datasets.

Producing an initial structure for a piece of content.

Working through repetitive technical problems.

Creating the first version of something that will ultimately need refining.

These are areas where AI can be particularly useful.

Not because the work suddenly becomes unimportant, but because reducing the manual effort involved gives specialists more time to concentrate on what happens next.

The value of AI isn’t removing people from the process. It’s giving people more time for the parts of the process that need judgement.

Research can become faster without becoming automatic

Research is one of the clearest examples.

Whether we are developing a search strategy, reviewing a market, planning a website or exploring opportunities for a client, there is normally a significant amount of information to work through.

AI can help organise that process.

It can help summarise material, group related themes, identify questions that need answering and explore alternative interpretations.

That can make the initial stage substantially more efficient.

But research isn’t finished when information has been collected.

Someone still needs to decide which sources deserve confidence, which findings actually matter and what is relevant to the problem being solved.

A technically correct observation may have almost no commercial importance.

Another apparently small detail may completely change the recommendation.

Context is what separates collecting information from understanding it.

01 Gather

Bring together the available information, data, research and client context.

02 Explore

Use AI to organise information, investigate themes and identify useful questions.

03 Verify

Check sources, assumptions, calculations and claims rather than treating generated output as fact.

04 Interpret

Add client knowledge, commercial context and the experience of the relevant specialist.

05 Decide

Turn that understanding into work or advice that somebody is prepared to stand behind.

AI can help us interrogate data more quickly

The same principle applies to data analysis.

Modern digital businesses generate an enormous amount of information.

Website behaviour. Search performance. Advertising data. Ecommerce transactions. Customer activity. Conversion rates. Geographic patterns. Changes over time.

AI gives us another way to question and interrogate that information.

It can help identify unusual changes, compare periods, group information and bring patterns to the surface more quickly.

That complements the work we already do through DB Analytics and our wider analytics work.

But there is an important distinction between identifying something and understanding why it matters.

If a conversion rate changes, AI can help highlight it.

Understanding whether that change relates to audience quality, seasonality, website behaviour, product mix, campaign activity or something happening elsewhere in the business requires a wider view.

AI can help surface the signal. People still have to decide whether the signal matters.

Content is one of the easiest places to use AI — and one of the easiest places to get it wrong

For many businesses, content generation was their first meaningful encounter with generative AI.

The appeal is obvious.

A tool can produce a blog structure, social post, email draft, product description or page outline in seconds.

Used properly, that can be genuinely valuable.

AI can help develop ideas, explore angles, organise research, challenge a first draft and adapt information into different formats.

But the ease with which content can be generated creates its own problem.

More content does not automatically mean better content.

Without sufficient input and editorial oversight, AI-generated material can become generic, repetitive, inaccurate or completely disconnected from what makes the organisation distinctive.

That matters whether the content is being created to support SEO and search visibility, an email campaign or the wider website experience.

The best input is often the material AI cannot invent.

Genuine client expertise. Real experience. First-hand knowledge. Customer conversations. Original data. A distinctive opinion. The reason something was done in a particular way.

AI can help us work with those ingredients.

It shouldn’t replace them.

Research & strategy

Exploring markets, organising information, challenging assumptions and identifying questions that deserve deeper investigation.

Data & performance

Helping interrogate datasets, compare performance and surface patterns that specialists can investigate further.

Content & marketing

Supporting ideation, structures, initial drafts, variations and the transformation of existing expertise into useful content.

Development & technical work

Assisting with troubleshooting, repetitive code tasks, documentation and exploring implementation approaches before developer review.

Development is becoming AI-assisted too

AI is also increasingly useful in technical work.

It can help developers explore implementation approaches, examine code, troubleshoot problems, create documentation and accelerate repetitive tasks.

For an agency working across websites and ecommerce, that creates some obvious efficiencies.

But producing code and delivering a reliable digital product are very different things.

A developer still needs to understand how that code fits into the wider system.

They need to consider performance, maintainability, accessibility, security, integrations and what happens when something changes six months later.

This is particularly important when working with platforms and technologies supported by partners such as Automattic and Shopify.

AI can assist the developer.

The developer remains responsible for the result.

Strategy is where human judgement becomes more important

AI becomes particularly interesting when it moves from producing things to recommending things.

Give a capable system enough information and it can suggest dozens of possible actions.

Increase advertising.

Create new landing pages.

Improve organic visibility.

Change the customer journey.

Develop more content.

Introduce new automation.

Many of those recommendations may be entirely reasonable.

The challenge is deciding which one deserves priority.

That is where understanding the client becomes essential.

What is the business trying to achieve?

Which customers actually matter most?

What can the business afford?

What can its team realistically deliver?

Which opportunity could create the greatest commercial value?

And which apparently attractive idea should be left alone because there is something more important to do first?

Those are the conversations behind our Growth Strategy approach.

AI can support strategy. It shouldn’t be mistaken for strategy.

Context

Understanding the history, customers, people and commercial realities behind the information.

Judgement

Knowing which signals matter, which assumptions deserve challenging and what should be prioritised.

Creativity

Bringing together ideas, experience and understanding to create something distinctive rather than merely plausible.

Accountability

Being prepared to explain the recommendation, make the decision and take responsibility for the work delivered.

We don’t assume that an AI answer is the right answer

One of the risks created by generative AI is how convincing an incorrect answer can sound.

AI systems can misunderstand context, make unsupported assumptions, misinterpret incomplete information or confidently present something that simply isn’t true.

That means speed has to be accompanied by verification.

If something is factual, the source matters.

If something is based on data, the data needs checking.

If something represents a client’s brand, it needs to sound like the client.

And if something is going to influence a commercial decision, somebody needs to understand how that conclusion was reached.

Stage 01 Generate

Use AI to explore, summarise, analyse, draft or investigate.

Stage 02 Challenge

Question assumptions, look for gaps and test whether the response actually answers the problem.

Stage 03 Verify

Check factual claims, source material, calculations, technical details and client-specific information.

Stage 04 Own it

A specialist reviews the final work and takes responsibility for what reaches the client or goes live.

AI is changing what valuable agency time looks like

Perhaps the most significant change is not what AI can produce.

It is what happens to the time that no longer needs to be spent producing it manually.

If gathering and organising information takes less time, more time can be spent interpreting it.

If a first draft appears more quickly, more time can be spent improving the thinking and making it distinctive.

If analysis can be explored faster, more questions can be asked of the data.

If repetitive technical tasks become easier, developers can focus more attention on solving the harder parts of a project.

This is the opportunity we find most interesting.

Not simply doing exactly the same work faster.

Using that efficiency to spend more time on work that creates greater value.

Technology keeps changing

AI doesn’t sit in isolation from the rest of the digital ecosystem.

The platforms our clients already use are themselves becoming more intelligent and automated. Our role is to understand how those capabilities fit into the wider website, marketing, ecommerce and data environment rather than adopting technology simply because it is new.

Google Microsoft Meta Automattic Shopify Klaviyo

AI is becoming part of the workflow, rather than a separate activity

The longer-term change is likely to be less visible.

Instead of somebody deciding to “use AI” for a particular task, AI-assisted capabilities increasingly become part of the tools and processes already being used.

Research becomes easier to interrogate.

Reporting becomes easier to question.

Information can move between different stages of a project more efficiently.

Repetitive processes can become easier to manage.

This direction also connects with the thinking behind Growth Strategy and the way we are developing Growth Intelligence.

The objective isn’t to ask technology to make every decision.

It is to make the right information easier for people to work with when they make those decisions.

So what does that mean for our clients?

Ideally, very little of this should feel like technology for technology’s sake.

The benefit should appear in the work itself.

Research can move more quickly.

More information can be considered.

Data can be explored from more angles.

Repetitive tasks can consume less specialist time.

And our team can spend more of that time interpreting, questioning, improving and solving.

Clients still work with the people behind Dancing Badger.

Our specialists still make recommendations, challenge assumptions, develop ideas and take responsibility for the work.

They simply have access to better tools.

AI at Dancing Badger

The more capable the technology becomes, the more important it is to know when to trust it, when to challenge it and when not to use it at all.

We see AI as another powerful tool in the agency toolkit — one that can accelerate research, analysis and delivery, while making human judgement, creativity and accountability even more important.

AI will undoubtedly continue to change the way digital agencies work.

The tools we use in twelve months may look very different from the tools available today.

What is less likely to change is what clients ultimately need from us.

Understand the problem.

Understand the opportunity.

Bring the right expertise to it.

Make a clear recommendation.

And be accountable for the result.

AI can help us do all of those things more effectively.

But it is the people behind the technology who still have to decide what good looks like.

Looking at how technology could create more value from your digital activity?

Our work brings together strategy, data, websites and digital marketing to identify where technology can genuinely improve performance rather than adding complexity for its own sake.

Growth Strategy Data Analysis DB Analytics SEO PPC Website Design Ecommerce Email Marketing

The Great Barn Devon is a premium wedding and events venue located in Devon, offering exclusive-use weddings, luxury accommodation and event experiences.

The venue already had a talented internal marketing team and a clear direction for its brand and digital presence. However, specialist support was required to ensure that both the website and digital marketing infrastructure were implemented effectively.

Rather than taking ownership away from the client, Dancing Badger worked alongside the existing team, providing technical expertise, strategic guidance and implementation support where required.

This collaborative approach helped strengthen both online visibility and marketing performance whilst allowing the client to maintain control of its ongoing activity.

+24.7%

Increase In Organic Search Traffic Year On Year

View the The Great Barn Devon project

Key Results

+24.7%

Increase in Organic Search Traffic

Organic Search sessions increased from 728 to 908 year on year, helping The Great Barn Devon attract more prospective visitors through search engines.

+66.6%

Increase in AI Discovery Traffic

Traffic from AI Assistant platforms grew from zero to 66 sessions, helping position the venue for emerging search behaviours and AI-powered discovery.

+25%

Increase in Searches for “The Great Barn Exeter”

Branded local search demand increased significantly, indicating stronger awareness and local visibility.

121 Wedding-Enquiry Actions Generated Through Google Ads

The newly launched Google Ads campaign generated brochure downloads, lead form submissions, conversation starts and call interactions, creating a strong foundation for ongoing lead generation.

The Client

The Great Barn Devon is a luxury wedding and events venue offering exclusive-use celebrations, on-site accommodation and bespoke guest experiences.

As competition within the wedding venue sector continues to increase, ensuring strong visibility across local search, wedding-related searches and paid advertising channels is critical for attracting new enquiries and bookings.

The Challenge

The Great Barn Devon already had a strong brand and a clear vision for its digital presence.

However, there were several areas where specialist support would deliver greater impact:

Building and implementing the website effectively
Providing technical expertise beyond internal resources
Setting up and launching Google Ads campaigns
Improving local SEO visibility
Establishing systems for local search monitoring
Supporting long-term organic growth
Enhancing visibility for wedding venue searches
Providing guidance without disrupting internal processes

The objective was to strengthen performance whilst supporting, rather than replacing, the existing marketing team.

Our Role

Website Development & Technical Delivery

The Great Barn Devon approached Dancing Badger with an established vision and design direction for the website.

Our role was to provide the technical expertise required to transform those concepts into a fully functioning, user-friendly website capable of supporting long-term growth.

By working closely with the internal team, we helped ensure the final website reflected both the venue’s brand and commercial objectives.

SEO Consultancy

SEO support focused on helping The Great Barn Devon increase visibility across wedding and venue-related searches.

This included:

Technical SEO recommendations
Search visibility analysis
Keyword opportunities
Website structure recommendations
Local SEO improvements
Content guidance

As part of the project, we recommended and implemented BrightLocal, allowing the team to monitor and improve local SEO performance on an ongoing basis. The internal team continues to use and manage this platform independently.

Google Ads Setup

Dancing Badger helped establish Google Ads activity designed to generate qualified wedding enquiries.

Campaigns were configured to support:

Brochure downloads
Enquiry generation
Lead forms
Phone interactions
User engagement

From launch, the campaign generated more than 120 measurable engagement and enquiry actions, providing a valuable source of qualified leads.

Strategic Consultancy

A key part of the engagement was providing strategic input rather than simply executing tasks.

This included:

Marketing advice
Technical recommendations
Search visibility guidance
Audience insights
Platform recommendations
Best-practice implementation

This flexible approach allowed the in-house team to remain in control whilst gaining access to specialist expertise whenever required.

The Approach

Our role was never to replace The Great Barn Devon’s internal marketing team.

Instead, we focused on complementing and supporting existing resources.

By understanding the client’s structure and strengths, we were able to step in where specialist knowledge was needed whilst allowing the internal team to continue leading day-to-day marketing activity.

This consultative model ensured:

Growth could continue sustainably
Knowledge remained within the business
Internal resources were strengthened
Best-practice tools were implemented
Specialist expertise was available when required

Results

Key Outcomes

24.7% increase in Organic Search traffic
Increased visibility across wedding-related search terms
Improved local SEO infrastructure through BrightLocal implementation
Successful delivery of the website build
Google Ads campaign launched and configured
121 wedding-focused enquiry and engagement actions generated
Strong growth in branded local search demand
Improved rankings for key wedding venue searches
Ongoing support provided without replacing the in-house team

Improving Visibility for Wedding Venue Searches

One of the most significant areas of growth came through improved visibility for wedding-related searches.

Search performance improved across key terms including:

Devon wedding venue
Wedding venues in Exeter
Small wedding venues Devon
Wedding venues with accommodation

Several of these searches showed substantial ranking improvements, increasing opportunities for prospective couples to discover the venue through organic search.

Supporting, Not Replacing, Internal Teams

The Great Barn Devon perfectly reflects the philosophy behind DB Growth.

Not every business wants or needs a fully outsourced marketing function.

Many organisations already have talented internal teams and simply require additional expertise in specific areas.

Our role was to provide that expertise, helping the client move faster, avoid technical pitfalls and implement industry-leading tools and strategies while keeping ownership and knowledge within the business.

Conclusion

The Great Barn Devon project demonstrates the value of a flexible, consultative approach to digital marketing.

By combining website development expertise, SEO consultancy, Google Ads implementation and ongoing strategic support, Dancing Badger helped strengthen the venue’s digital foundations whilst supporting the existing marketing team.

The result was a successful website launch, a 24.7% increase in organic search traffic, improved wedding venue visibility and a paid advertising programme generating more than 120 wedding-related lead and engagement actions. Most importantly, the project showcases how specialist support can work alongside internal teams to accelerate growth without replacing existing capabilities.

Executive summary Your product page is no longer the only version of your product that matters.

Ecommerce products are increasingly discovered through Google Shopping, paid advertising, social catalogues, marketplaces and AI-led shopping experiences. Many of those environments do not begin by reading the product page in the same way a customer does. They rely on structured product information: titles, identifiers, prices, availability, variants, categories, imagery, delivery information and other attributes supplied through feeds, catalogues and APIs.

That makes product data a commercial asset. The clearer, more complete and more consistent it is, the easier it becomes for platforms to understand what you sell, match products to relevant customers and keep information accurate across channels.

Takeaway: the website remains the place where your brand, proposition and conversion experience come together — but the product feed is increasingly the data layer that helps your products travel beyond it.

For a long time, ecommerce optimisation naturally centred on the website.

Improve the product photography. Rewrite the description. Make the navigation clearer. Speed up the site. Simplify checkout. Test the call to action.

All of that still matters.

But there is another layer of ecommerce performance that customers may never see directly: the structured product information sitting behind the store.

That information can determine how accurately a product appears in Google Shopping, whether the correct variant is shown in an advert, whether Meta understands which item is available, whether a marketplace receives the right price and whether an AI shopping system has enough detail to recommend the product for a specific request.

The ecommerce website is the shopfront. The product feed is becoming the distribution layer that helps other platforms understand what is on the shelves.

That distinction is becoming more important as ecommerce moves further into automated advertising, multi-channel selling and AI-assisted discovery.

Google describes accurate product data as a foundational input for ads, free listings and its AI-powered formats. Shopify now uses structured catalogue information to make eligible products available across AI-led shopping environments as well as its traditional sales channels.

In other words: the product page is still important, but the information underneath it needs just as much attention.

01 Two versions of the same product

Customers see a product page. Platforms see a product record.

Open an ecommerce product page and a customer might see a headline, lifestyle photography, product description, price, available options, delivery information, reviews and a button to buy.

A good page combines information with persuasion. It explains the product, communicates the brand and gives the customer confidence to act.

But external platforms often need that information in a more structured form.

Google Merchant Center, social catalogues, advertising systems, marketplaces and connected shopping tools need to know specific things about the item: what it is, how it should be categorised, which variants belong together, what it costs, whether it is available and which image belongs to which offer.

Customer-facing layer

The product page

Brand story and positioning
Persuasive product copy
Lifestyle and detail imagery
Reviews and reassurance
Delivery and returns explanation
Conversion journey and calls to action

Structured data layer

The product record

Product ID, SKU and identifiers
Title, category and product type
Price and availability
Variants, colour, size and material
Images, video and product links
Delivery, condition and other attributes

This is why ecommerce development increasingly needs to think beyond the page template itself.

A beautifully designed store can still have weak product data. Equally, a technically complete feed cannot compensate for a product page that fails to communicate value or convert the visitor.

Modern ecommerce needs both.

02 The feed is a distribution system

One product record can now influence several sales and marketing channels

Product feeds used to feel like specialist infrastructure sitting somewhere between an ecommerce platform and Google Shopping.

That description is now too narrow.

Ecommerce businesses increasingly distribute product information into several connected environments. A central product catalogue might feed Google Merchant Center, Meta, marketplaces, affiliate systems, comparison services, shopping apps and other integrations.

The exact route varies by platform. Some channels use direct integrations. Some use feeds. Some use APIs. Some can also crawl structured data from the website.

But the principle is the same: the quality of the source information affects the quality of what gets distributed.

ProductsTitles, descriptions, types, attributes and identifiers.

Commerce dataPrice, stock, variants, delivery and promotional information.

MediaPrimary images, additional imagery and product video.

Structured product layer Your product data

Organised, mapped, validated and kept in sync before being distributed into the channels that need it.

GoogleShopping, free listings and advertising.

MetaCatalogue-based advertising and commerce surfaces.

MarketplacesChannel-specific listings, attributes and inventory.

AI shoppingStructured catalogues and connected commerce experiences.

This is where multi-channel selling and third-party integrations become strategic rather than purely technical.

If every destination needs its own manually maintained version of the catalogue, the business creates more places for data to become inconsistent.

A stronger model keeps the core information controlled centrally and then maps or adapts it to the requirements of each channel.

03 Product data affects discoverability

Platforms can only work with the product information you give them

Good product data is not about filling in fields for the sake of completeness.

Attributes give platforms context.

A clear title helps describe the product. A category helps establish what type of item it is. GTINs and other identifiers help distinguish recognised products. Variant data shows how colours, sizes or configurations relate. Accurate price and availability information tells a platform whether the offer is still valid.

Google explicitly states that product information is used to match products to relevant queries and as a foundational input for its AI-powered advertising formats and experiences.

That makes catalogue quality part of PPC performance, not simply an ecommerce-admin task.

01Identity

SKU, product ID, GTIN, MPN and brand help identify the exact product or offer.

02Title

A clear product name gives the system a concise description of what the item actually is.

03Category

Product type and platform categories help place an item into the right commercial context.

04Variants

Colour, size, material and option relationships help separate and group related offers correctly.

05Price

Current pricing needs to agree with the customer-facing store and any sale or promotional logic.

06Availability

Stock and availability signals help channels avoid promoting offers that cannot be fulfilled.

07Media

Accurate imagery, additional images and increasingly video help external channels represent the item.

08Fulfilment

Delivery, returns and related information can influence whether a product is eligible or useful in a given experience.

Google’s 2026 product-data specification

Google says accurate product data is essential for successful ads and free listings and is used as a foundational input for AI-powered ad formats. Its 2026 specification update also introduced new product-level delivery attributes and a product video-link attribute. See the Merchant Center product data specification and 2026 specification update.

A platform cannot infer a reliable commercial answer from product information that is incomplete, inconsistent or out of date.

04 Accuracy becomes more important with automation

Automation can scale good product data — and bad product data

One of the benefits of feeds and integrations is scale.

Change the price in the ecommerce platform and the connected systems can receive the update. Mark a product unavailable and advertising can adjust. Add a new variant and it can be distributed without rebuilding every listing manually.

But automation works both ways.

If the source catalogue contains the wrong availability, a weak title, duplicated identifiers, missing attributes or inconsistent variant logic, that information can travel just as efficiently.

Feed problems therefore stop being isolated admin errors. They can become advertising problems, marketplace problems, customer-experience problems and reporting problems at the same time.

SourceProduct data is wrong

The price, variant, stock status or core attribute is inaccurate at source.

DistributionThe feed carries it outward

Connected advertising, catalogues or marketplace systems receive the same weak information.

PlatformEligibility or matching suffers

The product may be represented poorly, matched less effectively or generate diagnostics and disapprovals.

CustomerTrust and conversion suffer

The shopper sees inconsistent information, lands on the wrong option or discovers that an offer is not actually available.

Google specifically warns that missing or inaccurate product information can cause disapprovals, limited eligibility or incorrect product displays. It also uses structured data on the website to help keep price and availability information in Merchant Center up to date.

That is another reason ecommerce, website development and paid media should not be managed as completely separate systems.

The quality of the underlying commerce data affects all three.

Structured data can help keep feeds aligned

Google describes structured data as a machine-readable representation of product information on the website. It can be used for automatic item updates, helping reduce price and availability mismatches between a product page and Merchant Center. Google’s guidance also makes clear that structured data should match what customers actually see on the landing page. Read Google’s structured-data guidance for Merchant Center.

05 AI shopping raises the stakes

AI shopping makes structured product information more visible

The shift becomes particularly interesting when the customer is not browsing a traditional category page at all.

A shopper might ask an AI assistant for a navy waterproof coat under a certain budget, a sofa suitable for a specific room size or a gift with several practical constraints.

That kind of request is much more detailed than a simple search for “coat”, “sofa” or “gift”.

To respond usefully, a shopping system needs structured information that helps it distinguish one item from another.

Shopify has been investing heavily in this area. In 2026 it expanded Agentic Storefronts and Shopify Catalog so eligible products can be discovered through environments including ChatGPT, Microsoft Copilot, Google AI Mode and Gemini. Shopify describes its catalogue as structured, queryable product infrastructure designed so agents can discover and understand products using current data such as price, availability and attributes.

01Customer describes the need

Budget, use case, colour, size, material, delivery timing or another combination of requirements.

02System searches product data

Structured catalogue information provides attributes that can be compared and filtered.

03Relevant options are surfaced

Products can be presented using current information rather than relying only on generic page text.

04Customer continues to purchase

The journey can move to the merchant’s store or, where supported, continue inside the shopping environment.

This does not mean every ecommerce business needs to rebuild its entire store around AI shopping tomorrow.

It does mean that the direction of travel rewards something ecommerce teams should have wanted anyway: clean, detailed and reliable product information.

Better product data improves today’s feeds and advertising while also making the catalogue easier to use in emerging shopping environments.

Shopify’s current agentic-commerce model

Shopify says its Catalog structures product data and distributes eligible products across AI channels. In 2026 it expanded support across ChatGPT, Microsoft Copilot, Google AI Mode and Gemini, while keeping pricing and inventory synchronised from the merchant’s commerce system. See Shopify’s March 2026 agentic-commerce update and Spring ’26 merchant update.

06 Taxonomy becomes commercially useful

Product organisation should describe how customers actually compare

Product data is not only a technical exercise in meeting platform requirements.

It is also a useful way to think about merchandising.

If customers choose products by size, material, style, finish, compatibility, room, use case or another defining characteristic, those distinctions should usually exist clearly somewhere in the underlying catalogue.

That can improve more than a feed.

The same well-structured information can support website filtering, collections, landing pages, internal search, merchandising rules, email segmentation, paid-media campaigns and reporting.

In other words, a good product taxonomy can serve the customer experience and the marketing infrastructure at the same time.

This is where conversion rate optimisation and product-data work overlap. If customers repeatedly need a particular piece of information to make a decision, hiding it in inconsistent free text is rarely the strongest long-term approach.

07 The website and feed must agree

The product feed does not replace the ecommerce website

There is a risk in talking about product feeds, AI shopping and distributed commerce that the website starts to sound less important.

It is not.

The website remains the place where the business controls the strongest version of the brand experience: navigation, storytelling, merchandising, reassurance, conversion design, checkout, customer service information and the broader relationship between products.

Product data gets the item into more environments. The website still has to make the customer want to buy it.

And the two need to agree.

A feed that advertises one price while the landing page shows another creates friction. An availability mismatch damages trust. A generic feed title that sends someone to a confusing variant page weakens the experience. A brilliant advert that lands on an underdeveloped product page wastes the quality of the acquisition.

That is why Paid Social, PPC, ecommerce and CRO work best when they share the same product logic rather than each maintaining their own interpretation of the catalogue.

08 What good product-feed management looks like

Start with the source of truth, not the channel

A common mistake is to treat every channel problem as a channel problem.

A Google feed is fixed inside Google. A Meta catalogue is patched inside Meta. A marketplace listing is manually corrected in the marketplace. The ecommerce store contains a slightly different version again.

Sometimes channel-specific rules make local changes unavoidable. But repeated manual correction often indicates that the product model at source needs attention.

A stronger review starts with the core catalogue, decides which information genuinely belongs there and then maps that data into each destination deliberately.

A practical ecommerce product-data review

1 Define the source of truthKnow which system owns the authoritative title, SKU, price, inventory, variant logic, imagery and product attributes.

2 Audit the attributes customers actually useLook at how people filter, compare, search and ask questions. Make sure commercially important characteristics are structured consistently.

3 Standardise product and variant logicKeep identifiers stable and make sure related variants are grouped consistently across the store and connected channels.

4 Keep price and availability synchronisedReduce the delay and manual handling between changes on the website and the systems advertising or listing the product elsewhere.

5 Review imagery and media at feed levelCheck which images are actually being distributed, whether variants receive the right media and whether newer formats such as product video are useful.

6 Map each destination deliberatelyGoogle, Meta, marketplaces and other systems have different attribute requirements. Transform the same core data rather than creating disconnected catalogues.

7 Monitor diagnostics and rejected productsTreat channel warnings as evidence. Repeated errors can reveal weaknesses in the underlying catalogue rather than isolated platform problems.

8 Measure the commercial resultFeed quality matters because it should improve useful visibility, qualified product traffic, advertising efficiency, conversion and sales — not because a dashboard has more green ticks.

09 The ecommerce maturity curve

The goal is not a bigger feed. It is a more useful product system.

Ecommerce businesses do not need every possible attribute simply because a field exists.

The objective is to create product information that is accurate enough for operations, detailed enough for customers and structured enough for the channels the business actually uses.

As that foundation improves, new channels become easier to activate because the business is not rebuilding the catalogue from scratch each time.

Stage 1Fragmented

Product information is stored differently across the website, advertising platforms and marketplaces, with frequent manual corrections.

Stage 2Consistent

Core identifiers, variants, pricing and availability follow common rules, reducing mismatches between the store and channels.

Stage 3Channel-ready

Attributes are structured and mapped so products can be distributed efficiently into Google, Meta and other relevant destinations.

Stage 4Reusable infrastructure

The catalogue becomes a reliable product-information layer that can support new channels, automation and emerging shopping experiences.

That is the bigger opportunity behind integration work.

The value is not simply connecting system A to system B. It is making sure the information moving between them is useful, controlled and commercially meaningful.

The same principle applies to Data Analysis: channel performance becomes easier to interpret when products, variants and transactions share stable identifiers instead of being labelled differently in every system.

The new ecommerce infrastructure

Your website sells the product. Your product data helps the product travel.

As commerce spreads across advertising platforms, social catalogues, marketplaces and AI-led shopping environments, structured product information is becoming part of the marketing infrastructure — not just the back-office catalogue.

At Dancing Badger, we think the useful question is no longer simply, “Does the product feed work?”

It is: “Can every important channel understand the product accurately, and does the information still lead the customer into a strong buying experience?”

That requires ecommerce, paid media, integrations, merchandising and conversion strategy to work from the same product truth.

The businesses that get that foundation right are better placed not only for Google Shopping and Meta today, but for whatever the next meaningful commerce channel turns out to be.

Service Ecommerce

Build and optimise online stores around better merchandising, customer experience and commercial performance.

Service Multi-channel Selling

Connect product information and commerce operations with the external channels where customers discover and buy.

Service Third-party Integrations

Connect ecommerce platforms with the systems responsible for product data, marketing, fulfilment and customer experience.

Service PPC

Use stronger product data and campaign structure to improve how products are promoted across paid search and shopping.

Partner Shopify

Commerce infrastructure that connects product catalogues, storefronts, sales channels and emerging AI-led shopping experiences.

Partner Google

Merchant Center, Shopping and paid-media tools that depend on accurate, structured product information.

Partner Meta

Catalogue-based advertising and commerce experiences across Facebook and Instagram.

Is your product catalogue ready to work beyond your website?

We can review the structure, quality and distribution of your ecommerce product data — from the source catalogue and product pages through to Google, Meta, marketplaces, advertising feeds and the integrations connecting them.

Ecommerce Multi-channel Selling Third-party Integrations PPC Paid Social Conversion Rate Optimisation Website Design Data Analysis Shopify Google Meta

Executive summary The more marketing platforms automate, the more valuable your own customer data becomes.

Advertising, email and analytics platforms are increasingly using AI to decide who to reach, what to prioritise and how to optimise performance. Those systems can process huge amounts of information, but they still need businesses to define what a valuable customer, conversion or outcome actually looks like.

First-party data — information collected through your own customer relationships and digital touchpoints — gives automation context that is specific to your business. Purchases, qualified leads, lifecycle stage, repeat orders, product interest and customer value can all help turn generic automation into more commercially useful marketing.

Takeaway: automation makes execution easier to scale, but your competitive advantage increasingly comes from the quality of the signals you can give it.

Marketing technology is becoming very good at making decisions quickly.

Google can automate bidding, audience expansion, search matching and parts of creative delivery. Paid social platforms use machine learning to find people who are more likely to act. Email platforms can trigger journeys, personalise content and segment customers from their behaviour.

It is tempting to look at that progress and conclude that businesses need to provide less input.

In reality, the opposite is happening.

On 10 September 2026, Google described “a strong data foundation to fuel AI” as one of the three elements behind its latest measurement strategy. That is a useful summary of where modern marketing is heading.

As platforms take on more of the execution, the information used to guide those systems becomes more important.

An algorithm can optimise towards a conversion. But can it tell whether that conversion became a profitable customer? It can find more people who behave like previous buyers. But does it know which buyers stayed, reordered, bought higher-margin products or turned into long-term accounts?

Often, that knowledge sits inside the business rather than inside the advertising platform.

That is why first-party data is becoming more valuable.

01 What first-party data actually means

Your most useful marketing data is often the data your business already owns

First-party data is information a business collects directly through its own relationships, systems and customer touchpoints.

It can include obvious information such as an order, enquiry or email address. But the more commercially useful picture is usually broader than that.

A website can tell you which services or products someone explored. An ecommerce platform can show what they bought and whether they returned. A CRM can show whether an enquiry became a qualified opportunity. Email data can reveal engagement and lifecycle stage. Sales records can show revenue, margin or repeat purchase.

None of those signals is especially powerful in isolation.

The value appears when they begin to describe the relationship between customer behaviour and business outcome.

Website On-site behaviour

Pages viewed, content explored, products considered and meaningful actions taken on digital properties you control.

Lead generation Forms & enquiries

What someone asked for, which service they need, where they are based and how they chose to contact you.

CRM Sales outcomes

Lead status, qualification, opportunity value, closed business and the reasons different enquiries progress or stall.

Ecommerce Orders & products

Products bought, basket value, first purchase, repeat purchase, returns and customer buying patterns.

Retention Email engagement

Subscriptions, campaign activity, automated journeys, preferences and the stages customers move through over time.

Commercial Customer value

Revenue, margin, repeat behaviour, account value, retention and the customer groups that matter most to the business.

Your first-party data advantage

Platforms can understand general behaviour at enormous scale. Your business is the source of truth for which customers and outcomes are commercially valuable to you.

This is where Data Analysis and Audience & Segmentation start to overlap.

Analysis helps identify the behaviour and outcomes that matter. Segmentation turns those differences into useful customer groups. The result can then influence advertising, email, website journeys and wider Growth Strategy.

The important point is that first-party data is not valuable simply because it is “your data”.

It becomes valuable when it helps the business make a better decision.

02 Why automation changes the value of data

Automation can optimise faster — but it still needs to know what good looks like

Traditional digital marketing involved more manual decision-making.

A marketer selected keywords, built audiences, set bids, wrote variations, chose segments and adjusted activity after reviewing performance.

Those jobs have not disappeared, but platforms increasingly make more of the individual delivery decisions themselves.

In paid search, for example, automated bidding and AI-led campaign features can use large numbers of signals to decide how aggressively to enter an auction. In paid social, automated delivery can explore audiences beyond narrow manual targeting. In email, behavioural data can trigger personalised journeys without someone manually deciding who should receive each message.

This changes the marketer’s job from controlling every individual action to improving the inputs, objectives, guardrails and feedback around the system.

Business input First-party signals

Customer type, purchase behaviour, qualified leads, revenue, product interest, lifecycle stage and other meaningful outcomes.

Platform execution Automation & AI

Bidding, matching, delivery, audience expansion, personalisation, journey triggers and other decisions can happen at scale.

Commercial result What happened next?

Did the customer buy, qualify, return, spend more, remain profitable or move into a more valuable relationship?

Feed meaningful outcomes back into planning → improve the signals → make the next round of automation more commercially informed.

This is closely related to the shift explored in Google Ads Is Becoming More Automated: What AI Max Means for Your Marketing Strategy.

The more Google makes decisions across query matching, creative, landing pages and bidding, the more important it becomes to provide a reliable conversion signal and a clear commercial objective.

But the principle is bigger than Google Ads.

Every marketing system that learns from behaviour benefits from better information about what the business actually values.

Automation makes execution easier to scale. First-party data makes that automation more specific to your business.

03 The quality of the signal matters

A conversion is useful. A commercial outcome is more useful.

Many marketing platforms are asked to optimise around the easiest event to measure.

For an ecommerce business, that might be a purchase. For a service business, it might be a completed enquiry form. Those are useful signals, but they are not always the final business outcome.

Two purchases can have different margins. Two customers can have very different repeat behaviour. Two enquiries can look identical in analytics while one becomes a valuable long-term account and the other was never suitable in the first place.

First-party data gives the business an opportunity to add that missing context.

Engagement

A customer viewed a page, watched content, clicked an advert or interacted with a campaign.

Useful context

Conversion

An enquiry, sign-up, call, booking or transaction took place.

Stronger signal

Qualified outcome

The lead was commercially relevant, the order met the right criteria or the customer matched the intended audience.

Business context

Revenue & margin

The business can compare marketing activity with the financial value it actually created.

Commercial signal

Customer value

Repeat purchase, retention, lifetime value, account growth or customer type reveals which acquisitions proved most valuable over time.

Strategic insight

For lead-generation businesses, this may mean connecting marketing data with CRM outcomes rather than stopping at form submissions.

For ecommerce, it may mean distinguishing first-time buyers from returning customers, understanding which products lead to repeat purchases, or identifying customer groups with higher long-term value.

For retention marketing, it may mean using purchase history and engagement to shape more relevant Email Marketing journeys rather than sending the same campaign to everyone.

The objective is not to upload every internal business field into an advertising platform.

It is to understand which information meaningfully improves targeting, measurement, personalisation or commercial decision-making — and connect that information responsibly.

04 One customer, several marketing systems

The real opportunity appears when first-party data stops living in silos

Many businesses already collect useful data.

The problem is that it often sits in separate systems.

Website analytics knows what happened on the site. The CRM knows whether a lead became an opportunity. The ecommerce platform knows what was purchased. The email platform knows whether the customer is active, lapsing or highly engaged. Google and Meta know how their campaigns performed inside their own environments.

Each system can be useful on its own.

But when the data can be connected appropriately, one part of the marketing system can start learning from another.

01 PPC

Use stronger conversion and customer-value signals to judge and optimise paid search against outcomes that matter.

02 Paid Social

Support audience creation, retargeting, exclusions and campaign learning with relevant first-party customer information.

03 Email

Build lifecycle journeys around purchase history, engagement, interests and customer stage instead of broad mailing lists.

04 Segmentation

Group customers by behaviour, value, need, geography, product interest or lifecycle stage to make messaging more relevant.

05 Analytics

Compare campaign activity with website behaviour, customer outcomes and commercial performance rather than channel metrics alone.

06 CRO & website

Use real audience and conversion insight to prioritise journeys, propositions, content and tests around the customers you want more of.

One source of customer truth, several useful applications

Connected data can help acquisition, retention, conversion and reporting reinforce one another rather than learning in separate channel silos.

This is why Third-party Integrations can be a marketing issue as much as a development issue.

If the website, CRM, ecommerce platform, email system and advertising tools cannot exchange the information needed for measurement or activation, the business may have valuable data without being able to use it effectively.

The same principle applies to Paid Social, PPC and CRO.

Better customer understanding should travel between channels rather than being trapped inside the platform that happened to collect it.

That is also the wider argument behind Why More Marketing Activity Doesn’t Always Mean More Growth: the channels become more useful when they stop learning in isolation.

05 Why this matters right now

Google is making first-party data a bigger part of its AI and measurement infrastructure

The direction is particularly visible in Google’s advertising and measurement products.

On 10 September 2026, Google announced a set of changes designed to make first-party data easier to connect, manage and evaluate across its marketing tools.

Google said Data Manager is being integrated directly into Google Analytics and Display & Video 360, alongside its existing role in Google Ads. It also announced that the Data Manager API is now universal and introduced a new Data Strength Uplift Metric designed to estimate the additional conversions recovered through a first-party data setup.

The announcement is important less because of any one feature and more because of what the collection of changes says about the direction of travel.

Google is not treating first-party data as a niche CRM exercise. It is positioning the data foundation as part of how AI-powered advertising is measured and improved.

September 2026 · Google measurement update

Three changes that show where first-party data is heading.

Data Manager expands

Google is integrating Data Manager into Google Analytics and DV360 to make first-party data connections easier to manage across more of its ecosystem.

One API direction

The Data Manager API is now positioned as a universal route for connecting, managing and activating data across supported advertising use cases.

Data strength becomes measurable

A new uplift metric is intended to show the additional conversions associated with stronger first-party data foundations.

Google also reports performance improvements from several of these data connections.

In its September announcement, Google said advertisers connecting offline and app data through Data Manager saw an average 26% increase in incremental ROAS, while advertisers using enhanced conversions saw an average 11% increase in Search conversions compared with standard conversion imports.

Those are Google’s own aggregated results, not a guarantee for an individual advertiser. But they reinforce a useful principle: improving the information available to the measurement and optimisation system can change what the system is able to see and learn from.

Google’s September 2026 data and measurement update

Google published its latest measurement changes on 10 September 2026, including Data Manager integrations, the universal Data Manager API and the Data Strength Uplift Metric. Read Google’s data and measurement announcement, Data Manager guidance and enhanced conversions guidance for current platform detail.

06 More data is not automatically better data

The goal is a stronger data foundation — not collecting everything you possibly can

The growing value of first-party data can easily be misunderstood as an instruction to collect more information about everyone.

It is not.

Poor-quality, duplicated, outdated or irrelevant data can make automation less useful. A CRM full of unqualified contacts does not become strategically valuable just because it is large. An email list does not become better because more addresses have been added to it. A conversion event does not become useful if it is firing incorrectly or measuring an action with little commercial meaning.

Data quality and data governance therefore become part of marketing performance.

Businesses need to know where information came from, why it is being collected, whether it is accurate, how long it should be retained and what it can legitimately be used for.

For UK organisations, first-party data does not sit outside data-protection and direct-marketing rules simply because it was collected directly.

The ICO continues to emphasise principles including lawfulness, fairness and transparency, purpose limitation, data minimisation, accuracy and storage limitation. Its direct-marketing guidance also makes clear that organisations should plan how customer information will be used and respect people’s marketing preferences.

In practical terms, that means the better marketing-data strategy is usually collect what has a clear purpose, keep it accurate, connect it carefully and use it transparently.

First-party data still needs responsible governance

The ICO’s current guidance covers the UK data-protection principles and responsible use of personal information for direct marketing. See its data protection principles and direct marketing guidance. The ICO notes that some guidance is being reviewed following the Data (Use and Access) Act, so implementation should always be checked against current requirements.

Consent and tracking configuration are also part of the same foundation.

Tools such as Cookiebot can help businesses manage consent choices, while analytics and advertising configurations still need to be designed around the organisation’s actual data requirements and responsibilities.

First-party data is valuable because it can be relevant and specific — not because it gives a business unrestricted permission to use personal information however it wants.

07 From collection to activation

Most businesses do not need more tools. They need a clearer data flow.

The technology stack can become complicated very quickly.

CRM. Ecommerce. Analytics. Consent management. Email. Advertising platforms. Customer service. Data warehouses. Reporting dashboards. Integrations.

Adding another platform does not automatically solve the problem.

The more useful question is whether the information needed to make a decision can move from the place it is created to the place it can create value.

Stage 01 Collected

Useful information exists across website forms, ecommerce, CRM, email and analytics, but each system is mostly viewed separately.

Stage 02 Connected

Key systems exchange the information needed to understand the customer journey and relate marketing activity to business outcomes.

Stage 03 Activated

Relevant customer data informs segmentation, advertising, retention, personalisation, conversion journeys and commercial reporting.

Stage 04 Improved

Performance feeds back into the system so the business can refine audiences, measurement, journeys and strategy over time.

This is where DB Analytics can play a different role from an advertising dashboard.

A platform is naturally strongest at explaining what happened inside its own environment. A wider analytics view can compare channels with website behaviour, customer outcomes and other commercial information.

That is also why the earlier question — what data should we track? — needs to come before the question of how much data can be collected.

The right data foundation starts with the decisions the business needs to make.

08 What businesses should do now

Start with customer value, then work backwards into the data

A first-party data strategy does not need to begin with a large technology project.

In many businesses, the first useful step is simply to map what information already exists, where it sits and which decisions would improve if that information was better connected.

A practical first-party data review

1 Define what a valuable customer looks like Revenue matters, but so can margin, lead quality, repeat purchase, service fit, geography, retention or long-term account value.

2 Map the data you already collect Identify useful information across the website, CRM, ecommerce, email, sales, customer service and analytics before buying another tool.

3 Separate activity from outcome Know the difference between a click, a conversion, a qualified lead, a sale and a genuinely valuable customer.

4 Find the disconnected systems Look for places where useful information stops: CRM outcomes that never reach marketing, purchases that never shape email, or website behaviour that never informs segmentation.

5 Choose the activation use case Decide whether the data should improve measurement, advertising, retention, personalisation, CRO, reporting or another specific business decision.

6 Check consent, purpose and data quality Make sure the information is collected and used appropriately, remains accurate and is not retained or activated simply because it might be useful one day.

7 Feed commercial learning back into marketing Use real customer outcomes to refine campaigns, segments, website journeys, content and budget decisions.

8 Measure whether the connection improved anything Better data architecture is only valuable if it leads to better decisions, stronger measurement, improved customer journeys or more profitable growth.

The most important step is the first one.

If a business has not agreed what a high-quality lead, profitable customer or valuable repeat buyer looks like, connecting more data will only automate an unclear objective.

Once the commercial outcome is defined, the technology becomes much easier to judge.

Does this integration give the campaign a better outcome signal? Does this customer field create a useful segment? Does this email behaviour tell us something actionable? Does this dashboard connect activity with revenue? Does this automation reflect how customers actually buy?

Those are better questions than simply asking whether the business is “using AI”.

09 The competitive advantage

When everyone has access to similar automation, your customer intelligence becomes more distinctive

Marketing platforms are becoming easier to automate.

That means many businesses can access similar bidding systems, campaign types, AI tools, personalisation features and reporting interfaces.

The technology itself is therefore less likely to be the whole competitive advantage.

What remains specific to each organisation is its customer relationship.

Your history of enquiries. Your purchase behaviour. Your repeat customers. Your sales outcomes. Your product mix. Your margins. Your audience knowledge. Your understanding of which customers are genuinely a good fit.

That information cannot be copied from a competitor’s campaign account.

As automation becomes more capable, businesses that understand and responsibly activate those signals have a better chance of directing the technology towards the outcomes they actually care about.

The automation advantage

AI can make more marketing decisions. Your first-party data helps make those decisions more relevant to your business.

The next phase of digital marketing is not about choosing between automation and human strategy. It is about combining automated execution with better customer intelligence, clearer commercial objectives and reliable measurement.

At Dancing Badger, that means treating data as part of the wider growth system rather than a reporting layer added at the end.

Growth Strategy defines the commercial objective. Data Analysis identifies the signals that matter. Audience & Segmentation turns customer differences into usable groups. Integrations help the information move between systems. PPC, Paid Social and Email Marketing can then activate those insights in different parts of the customer journey.

The more marketing becomes automated, the more important it is to make sure the automation is learning from the right things.

Your first-party data is one of the clearest ways to tell it what matters.

Service Data Analysis

Connect marketing performance with customer behaviour and commercial outcomes so decisions are based on evidence rather than platform metrics alone.

Service Audience & Segmentation

Turn customer behaviour, value and lifecycle information into sharper groups for targeting, messaging and reporting.

Service Email Marketing

Use customer and purchase behaviour to create more relevant campaigns, lifecycle automation and retention journeys.

Partner Google

Advertising and measurement tools where conversion quality, customer data and automation increasingly work together.

Partner Klaviyo

Customer marketing built around ecommerce data, segmentation, automation and stronger repeat-customer journeys.

Service Third-party Integrations

Connect websites, ecommerce, CRM, analytics and marketing tools so useful information can move between the systems that need it.

Is your customer data helping your marketing learn — or just sitting in separate systems?

We can review how customer, website, advertising, ecommerce and CRM data currently flows through your marketing setup, identify the signals that are commercially useful, and prioritise the integrations, measurement and segmentation opportunities most likely to improve decision-making.

Growth Strategy Data Analysis DB Analytics Audience & Segmentation PPC Paid Social Email Marketing Third-party Integrations CRO AI Marketing Google Klaviyo

Operating within the luxury home and interiors sector requires more than simply attracting traffic. Success depends on reaching the right customers, showcasing products effectively and creating a seamless path to purchase.

Dancing Badger worked with Brights of Nettlebed to improve visibility, strengthen customer acquisition and maximise the return from digital marketing activity. Through a combination of SEO, PPC optimisation, audience targeting and data analysis, we developed a strategy focused on delivering measurable commercial growth.

The result was improved engagement, stronger conversion performance and increased visibility across multiple acquisition channels.

+364%

Year On Year Ad Conversions

View the Brights of Nettlebed project

Key Results

+321%

Increase in Direct Traffic

Brand awareness and customer engagement increased significantly, resulting in more than three times as many direct sessions year on year.

+78%

Increase in Organic Search Conversions

SEO-led improvements helped organic search generate substantially more conversion events, demonstrating improved visibility and stronger user engagement.

+53%

Increase in Paid Search Traffic

Targeted paid search activity increased traffic volumes while maintaining strong engagement and conversion quality.

+58.9%

Increase in Paid Search Conversions

Campaign optimisation and improved targeting delivered significant growth in key conversion actions from paid search users.

+52%

Improvement in Paid Search Conversion Rate

Paid Search session conversion rates increased substantially year on year, demonstrating more effective traffic acquisition and optimisation.

The Client

Brights of Nettlebed is a well-established luxury retailer offering premium furniture, interiors and lifestyle products.

The business serves customers seeking quality craftsmanship, timeless design and exceptional products for the home. As competition within ecommerce continues to increase, maintaining visibility across organic and paid channels is essential for attracting new customers and driving online sales.

The Challenge

While Brights of Nettlebed already had a strong reputation, opportunities existed to improve digital acquisition performance and maximise marketing efficiency.

Our objectives included:

Increasing high-quality website traffic
Expanding organic search visibility
Improving paid advertising performance
Strengthening conversion rates
Improving audience targeting
Enhancing customer journeys
Increasing acquisition across multiple channels
Supporting long-term ecommerce growth

The goal was to create a joined-up digital strategy capable of delivering sustainable commercial improvements.

Our Role

Data Analysis & Growth Strategy

The project began with a comprehensive review of website and campaign performance data.

Our data analysis focused on:

Acquisition channels
User behaviour
Conversion performance
Campaign effectiveness
Audience segmentation
Product engagement
Growth opportunities

These insights allowed us to prioritise activity and focus investment on the channels delivering the strongest returns.

SEO Strategy

SEO activity focused on improving visibility and helping customers discover products through organic search.

This included:

Keyword research
Technical SEO improvements
Metadata optimisation
Content recommendations
Internal linking enhancements
Search intent analysis
Ongoing performance monitoring

These improvements helped maintain strong organic visibility while increasing conversion opportunities from search traffic.

PPC Management

Paid media activity was continually refined to improve performance and efficiency.

Our PPC work included:

Campaign optimisation
Audience targeting
Search term analysis
Bid management
Budget allocation
Ad testing
Landing page recommendations

These refinements generated stronger engagement and increased conversion performance from paid channels.

Audience Segmentation & CRO

Understanding customer behaviour played an important role throughout the project.

Through audience analysis and conversion rate optimisation recommendations, we identified opportunities to:

Improve user journeys
Enhance product discovery
Reduce friction during the buying process
Increase conversion rates
Improve marketing effectiveness

This helped maximise the value of incoming traffic.

AI Recommendations & Copywriting

Alongside manual analysis, AI-assisted recommendations were used to identify growth opportunities, enhance content and support optimisation efforts across the website.

This ensured ongoing improvements were informed by both data and user intent.

The Approach

The strategy was built around a simple principle: use data to identify where the greatest opportunities existed and focus resources accordingly.

Rather than treating SEO and PPC as separate disciplines, performance insights were shared across channels.

Search behaviour informed content planning.
Campaign performance informed acquisition strategy.
User engagement informed CRO recommendations.
Audience data informed targeting and segmentation.

This integrated approach created a more efficient and effective growth programme.

Results

Key Outcomes

321% increase in Direct traffic
78% increase in Organic Search conversions
53% increase in Paid Search traffic
58.9% increase in Paid Search conversions
52% improvement in Paid Search conversion rate
Improved engagement across paid and organic channels
Stronger customer acquisition performance
Enhanced audience targeting and segmentation
More effective conversion pathwaysIncreased visibility across key acquisition channels

Strengthening Acquisition Across Organic & Paid Channels

A key success of the project was creating stronger alignment between acquisition channels.

SEO activity helped attract highly engaged visitors through organic search, while PPC campaigns captured high-intent customers actively researching products and ready to purchase.

Together, these channels generated stronger customer acquisition opportunities and increased conversion performance across the website.

Turning Data Into Commercial Growth

Performance data sat at the centre of every recommendation made throughout the project.

By continually analysing customer behaviour, campaign results and engagement metrics, we were able to identify new opportunities, refine existing activity and ensure marketing investment remained focused on delivering measurable outcomes.

This approach allowed Brights of Nettlebed to make informed decisions and continually improve performance across digital channels.

Combining SEO, PPC & CRO for Sustainable Growth

The success of the project came from integrating multiple marketing disciplines into a single strategy.

SEO improved long-term visibility.
PPC generated targeted traffic.
Audience segmentation improved targeting accuracy.
CRO enhancements improved conversion performance.

Together, these activities delivered stronger acquisition performance and helped build a sustainable foundation for future ecommerce growth.

Conclusion

The Brights of Nettlebed project demonstrates the value of combining SEO, PPC, audience insight and conversion optimisation within a unified growth strategy.

Through ongoing analysis, campaign optimisation and customer-focused improvements, Dancing Badger helped Brights of Nettlebed increase traffic, improve conversion performance and strengthen marketing efficiency.

The result was a 321% increase in Direct traffic, a 53% increase in Paid Search traffic, a 58.9% increase in Paid Search conversions and a 78% increase in Organic Search conversions, creating a stronger platform for long-term ecommerce growth.

National Family Mediation operates within a highly sensitive and competitive sector where individuals often require support during significant life events. Ensuring that users can quickly find trusted information and access appropriate mediation services is essential.

Dancing Badger worked closely with National Family Mediation to improve online visibility, increase enquiry volumes and maximise the performance of digital marketing activity. By combining SEO, paid advertising, audience analysis and ongoing optimisation, we created a strategy focused on reaching users at the point they were actively seeking support.

The result was stronger campaign performance, increased lead generation and a more effective digital acquisition strategy.

+43.9%

Increase in PPC Conversions Year on Year

View the National Family Mediation project

Key Results

+43.9%

Increase in PPC Conversions Year on Year

Targeted campaign improvements and ongoing optimisation generated significantly more enquiries and conversion opportunities from paid media.

+47.4%

Increase in PPC Clicks Year on Year

Improved visibility and audience targeting helped National Family Mediation reach substantially more prospective service users.

+268%

Improvement in Paid Search Conversion Rate

Campaign refinements dramatically increased the proportion of users completing key actions after arriving via paid search.

+150%

Increase in Paid Search Key Events

Paid Search generated significantly stronger lead-generation performance compared with the previous year.

The Client

National Family Mediation is a leading, non-profit provider of family mediation services, helping families find constructive solutions to challenges involving separation, finances and child arrangements.

As more people turn to search engines when seeking information about mediation services, maintaining strong visibility across both organic and paid channels is vital for connecting individuals with appropriate support.

The Challenge

National Family Mediation already had a well-established service offering, but opportunities existed to strengthen digital performance and improve lead generation.

Key objectives included:

Increasing qualified enquiry volumes
Improving PPC efficiency
Strengthening visibility for mediation-related searches
Improving audience targeting
Enhancing user journeys
Increasing conversion rates
Expanding reach across key acquisition channels
Using data more effectively to support decision-making

The goal was to ensure marketing investment generated the greatest possible impact while helping more people access mediation services.

Our Role

Data Analysis & Strategic Planning

The project began with a detailed review of performance data across Google Analytics 4, Google Ads and website engagement metrics.

Our analysis focused on:

User acquisition channels
Conversion performance
Audience behaviour
Search demand
Campaign efficiency
User journeys
Engagement metrics

This insight allowed us to identify opportunities for growth and prioritise optimisation activity around channels with the highest potential.

SEO Strategy

Alongside paid advertising improvements, we delivered ongoing SEO support designed to strengthen organic visibility and improve website relevance.

Activities included:

Keyword research
Search intent analysis
Content recommendations
Metadata optimisation
Internal linking recommendations
Technical SEO improvements
Page-level optimisation

This ensured National Family Mediation continued to maintain a strong presence in organic search whilst supporting long-term visibility growth.

PPC Management & Optimisation

A significant focus of the project was improving the performance of paid search campaigns.

Our work included:

Campaign restructuring
Audience segmentation
Bid optimisation
Search term analysis
Budget management
Ad copy testing
Landing page recommendations
Ongoing performance reviews

These refinements helped improve campaign quality, attract more relevant traffic and increase conversion volumes.

Audience & Segmentation

Understanding audience behaviour was central to the strategy.

Through segmentation analysis, we were able to better understand how different users searched for and engaged with mediation services. This enabled more targeted campaign delivery and improved advertising efficiency.

AI Recommendations & Copywriting

Using a combination of expert analysis and AI-assisted recommendations, we identified opportunities to improve messaging, strengthen content and enhance user engagement throughout the website.

This supported both SEO performance and conversion optimisation efforts.

The Approach

The strategy focused on creating a joined-up digital marketing programme where every channel contributed towards the same objective: generating more qualified enquiries.

Rather than treating SEO and PPC as separate activities, insights were shared across channels to create a more cohesive acquisition strategy.

Search behaviour informed content improvements.
Campaign data informed audience targeting.
User behaviour informed conversion recommendations.
Performance analysis informed future optimisation priorities.

This integrated approach ensured activities remained aligned with measurable business outcomes.

Results

Key Outcomes

43.9% increase in PPC conversions year on year
47.4% increase in PPC clicks year on year
268% improvement in Paid Search conversion rate
150% increase in Paid Search key events
Improved lead generation performance
Greater efficiency from marketing spend
Enhanced audience targeting
Strong organic search visibility maintained
Increased acquisition opportunities across multiple channels
More users successfully engaging with mediation services

Improving the Quality of Enquiries

One of the project’s primary objectives was not simply to attract more traffic but to improve the quality of traffic reaching the website.

By refining audience targeting, improving campaign relevance and enhancing user journeys, National Family Mediation was able to connect with more individuals actively seeking mediation support and increase the likelihood of meaningful engagement.

This improvement in traffic quality contributed directly to stronger conversion performance across digital channels.

Using Data to Drive Better Decisions

Data analysis remained at the centre of every recommendation throughout the project.

Regular performance reviews allowed us to identify trends, uncover new opportunities and continually refine campaign activity.

This ensured optimisation decisions were driven by real user behaviour rather than assumptions, helping National Family Mediation maximise the effectiveness of its digital marketing investment.

Combining SEO, PPC & Audience Insight

The success of the project came from integrating multiple disciplines into a single growth strategy.

SEO supported long-term visibility.
PPC generated immediate demand.
Audience segmentation improved targeting.
Data analysis informed optimisation.

Together, these activities created a stronger and more sustainable digital acquisition framework capable of delivering measurable results.

Conclusion

The National Family Mediation project demonstrates the value of combining SEO, PPC, audience insight and data analysis to drive meaningful lead-generation growth.

Through ongoing optimisation, campaign refinement and a data-led approach to decision-making, Dancing Badger helped National Family Mediation increase visibility, improve conversion performance and generate substantially more enquiries.

The result was a 47.4% increase in PPC clicks, a 43.9% increase in PPC conversions and a 268% improvement in Paid Search conversion rate, creating a stronger platform for long-term growth and helping more individuals access the support they need.

English Roses operates within a highly competitive ecommerce market where customers are often purchasing for significant life events, celebrations and milestones.

Success depends on reaching customers at the right moment with the right message, whether they are searching for anniversary gifts, named roses, birthday presents or commemorative products.

Dancing Badger worked closely with English Roses to create a marketing strategy that combined organic search growth with more efficient paid advertising and conversion improvements. The objective was not simply to generate more traffic, but to increase the quality of visitors arriving on the site and improve overall return on investment.

+312%

ROI Increase Year On Year

View the English Roses project

Key Results

+312%

Increase in ROI Year on Year

A combination of SEO, PPC optimisation, audience targeting and conversion improvements delivered substantially stronger marketing efficiency and commercial return.

+544%

Growth in Traffic from Key Anniversary Search Themes

Improved rankings and visibility helped English Roses capture significantly more users searching for milestone anniversary gifts.

+208%

Growth in Ruby Wedding Anniversary Search Visibility

Targeted optimisation and improved content helped strengthen performance for one of the site’s most commercially valuable anniversary categories.

+530%

Increase in Referral Traffic

Broader brand visibility and improved digital performance contributed to substantial growth from referral channels.

The Client

English Roses specialises in named roses, anniversary roses and commemorative gift products designed to celebrate life’s most important moments.

The brand has built a strong reputation for quality and personalisation, making it a popular choice for customers searching for meaningful gifts to mark birthdays, anniversaries and special milestones.

As search behaviour continues to evolve, maintaining visibility across both transactional and informational searches became increasingly important for continued growth.

The Challenge

Although English Roses already had a strong foundation, several opportunities existed to improve performance.

These included:

Increasing visibility beyond brand searches
Growing market share across anniversary gifting categories
Improving PPC efficiency and return on ad spend
Identifying new customer acquisition opportunities
Strengthening rankings for commercial gifting searches
Improving conversion performance
Expanding visibility for rose-related informational searches
Creating a more data-driven growth strategy

The challenge was to develop a scalable approach capable of delivering sustainable growth across multiple marketing channels.

Our Role

Data Analysis & Strategic Planning

Every recommendation was informed by data.

Using Google Analytics 4, Google Search Console and advertising platform insights, we analysed:

Customer acquisition channels
Seasonal purchasing trends
Product performance
Search demand
Audience behaviour
Conversion opportunities
Campaign effectiveness

This analysis formed the foundation for both SEO and paid marketing strategies.

SEO Strategy

Our SEO programme focused on increasing visibility across commercially valuable search themes.

This included:

Keyword research
Search intent analysis
Metadata optimisation
Technical SEO improvements
Internal linking enhancements
Category page optimisation
Content development
Ongoing performance monitoring

Particular focus was placed on high-converting anniversary-related searches where demand and purchase intent were strongest.

PPC Optimisation

Paid advertising campaigns were continually refined through:

Audience segmentation
Search term analysis
Bid adjustments
Budget optimisation
Campaign restructuring
Ad copy testing
Landing page recommendations

This helped deliver greater efficiency from advertising spend while improving overall return on investment.

CRO & User Experience Improvements

Alongside acquisition activity, we identified opportunities to improve conversion performance throughout the customer journey.

Recommendations focused on:

User experience improvements
Customer journey optimisation
Landing page enhancements
Product discovery
Purchase decision support

These improvements ensured more traffic translated into commercial results.

Content Strategy

Search data revealed significant opportunities across content themes including:

Wedding anniversaries
Milestone birthdays
Named roses
Rose varieties
Gift inspiration
Rose meanings
Seasonal gifting occasions

Strategic content development helped English Roses capture additional search demand whilst strengthening topical authority across key product categories.

The Approach

The project was built around a unified growth strategy where SEO, PPC, content and conversion optimisation worked together.

Rather than treating channels independently, insights were shared across every aspect of the marketing programme.

Search data informed content creation.
PPC data informed SEO priorities.
Customer behaviour informed conversion improvements.
Seasonality data informed promotional planning.

This integrated approach ensured resources were focused on areas with the greatest commercial potential.

Results

Key Outcomes

312% increase in ROI year on year
544% growth across key anniversary search themes
208% increase in Ruby Wedding Anniversary search performance
530% increase in referral traffic
Increased visibility across gifting-related search queries
Improved rankings for milestone anniversary keywords
Enhanced PPC efficiency and campaign performance
Stronger audience targeting and segmentation
Greater reach beyond existing brand demand
Improved customer acquisition opportunities
Increased visibility throughout the customer buying journey

Strengthening Visibility for Anniversary Gifting

One of the most successful areas of the project was expanding visibility across anniversary-related searches.

Search data highlighted growing demand around milestone anniversaries, with particularly strong opportunities in categories such as Ruby, Golden, Diamond and other commemorative gifting occasions.

By improving category optimisation, refining keyword targeting and creating supporting content, English Roses strengthened its visibility across some of its most commercially valuable search themes.

This not only generated additional traffic but also introduced the brand to a wider audience actively researching meaningful anniversary gifts.

Building Demand Beyond Brand Searches

A key objective was reducing reliance on existing brand awareness by increasing visibility among new customers.

Through category optimisation, content development and strategic campaign management, English Roses expanded its reach across broader gifting and rose-related searches.

This allowed the business to appear earlier in the customer journey, creating more opportunities to influence purchasing decisions before competitors.

Combining SEO, PPC & Data for Long-Term Growth

The project demonstrates the power of integrating multiple channels under a single growth strategy.

Rather than focusing on individual tactics, every recommendation was driven by customer behaviour, search demand and commercial performance.

The combination of SEO, PPC, content, conversion optimisation and strategic analysis enabled English Roses to improve visibility, attract more qualified visitors and increase marketing efficiency across the business.

Conclusion

The English Roses project demonstrates how a data-led marketing strategy can unlock substantial ecommerce growth.

Through a combination of SEO, PPC optimisation, audience segmentation, conversion improvements and content development, Dancing Badger helped English Roses strengthen its online presence, increase customer acquisition opportunities and achieve a 312% increase in ROI year on year.

Most importantly, the project established a scalable framework for continued growth, enabling English Roses to expand visibility beyond existing brand demand and reach more customers at every stage of their buying journey.

LHP Medical Aesthetics operates within a highly competitive market where patients increasingly conduct extensive online research before booking a consultation.

The objective was to increase the clinic’s visibility across organic search, improve how users discovered treatments and create a website structure that better aligned patient concerns with available solutions.

Dancing Badger delivered a comprehensive SEO strategy combining technical optimisation, content development, keyword research and website improvements. The project was designed not only to increase traffic but to improve the quality of traffic arriving on the website and make it easier for users to find relevant treatment information.

+75.07%

Increse in Organic Traffic Year On Year

View the LHP Medical Aesthetics project

Key Results

+75.07%

Increase in Organic Traffic Year on Year

A strategic SEO and content programme delivered substantial year-on-year organic growth and established organic search as the clinic’s strongest acquisition channel.

+73.35%

Growth in Organic Search Sessions

Organic search sessions increased by more than 73%, demonstrating significantly improved visibility across treatment and condition-related searches.

+530.77%

Increase in Referral Traffic

Enhanced visibility and a stronger online presence contributed to a substantial increase in referral traffic year on year.

The Client

LHP Medical Aesthetics offers advanced non-surgical aesthetic treatments designed to address a range of skin, facial and ageing concerns.

The clinic’s focus on professional treatments and patient care meant there was a strong opportunity to attract more qualified traffic through organic search, provided the website could effectively match patient intent and answer key pre-treatment questions.

The Challenge

The website contained valuable treatment information, but several challenges were limiting its ability to maximise organic performance:

Opportunities to improve visibility for treatment-related keywords
Limited coverage of condition-based searches
Scope to strengthen internal linking between treatments
Opportunities to expand topical authority through supporting content
Potential to improve technical and on-page SEO signals
Need for a clearer patient journey between concerns and treatments

The challenge was to create a structure that worked for both users and search engines while supporting future growth.

Our Role

Data Analysis & Insights

The project began with a comprehensive review of performance data using Google Search Console and Google Analytics 4.

This analysis helped identify:

Treatment pages with the greatest growth potential
Search behaviour trends
User engagement patterns
Content gaps
High-value keyword opportunities
Areas requiring optimisation

By understanding how users interacted with the website, we could make more informed strategic recommendations.

SEO Strategy

A full SEO optimisation programme was implemented across the website, including:

Keyword research
Page title optimisation
Meta description updates
Heading structure optimisation
Content improvements
Internal linking enhancements
Technical SEO recommendations

Each key page was reviewed and optimised to improve relevance, search visibility and user experience.

Conditions Section Development

One of the most significant improvements was the introduction of a dedicated Conditions section.

Rather than focusing exclusively on treatment names, the new structure addressed the concerns patients were actively searching for, including issues such as skin ageing, pigmentation, acne and rosacea.

Each condition page was linked to the most appropriate treatment options, creating a more intuitive user journey while helping search engines better understand the relationship between concerns and solutions.

Content Cluster Strategy

To strengthen topical authority, we analysed search behaviour and developed supporting content clusters around key treatment areas.

This content strategy focused on building relevance around themes including:

Skin rejuvenation
Anti-ageing treatments
Acne and acne scarring
Pigmentation concerns
Facial aesthetics
Preventative treatments
Skin health and maintenance

The resulting content ecosystem helped support both category-level visibility and treatment page performance.

AI Recommendations & Copywriting

Alongside manual SEO analysis, AI-assisted recommendations were used to identify content opportunities, strengthen internal linking and enhance topical coverage across the website.

This allowed content improvements to be implemented strategically and at scale.

The Approach

The project focused on aligning the website more closely with real-world patient behaviour.

Rather than simply promoting treatments, the strategy was built around understanding:

What prospective patients were searching for
Which concerns generated the highest demand
How users moved through the website
Which content gaps existed within the patient journey

From this analysis, we implemented a joined-up strategy consisting of:

Technical SEO improvements
Enhanced site architecture
Conditions-based content
Treatment page optimisation
Strategic internal linking
Blog content cluster development

Together, these improvements created a website that was more visible, more useful and better positioned to attract qualified traffic.

Results

Key Outcomes

75.07% increase in organic traffic year on year
73.35% increase in organic search sessions
More than 530% increase in referral traffic
Organic search became the clinic’s primary acquisition channel
Improved visibility across treatment and condition-related searches
Enhanced internal linking structure
Creation of a dedicated Conditions hub
Stronger content relevance and topical authority
Increased engagement from organic search users
More opportunities for consultation enquiries and lead generation

Creating Condition-Led Patient Journeys

A significant factor in the project’s success was understanding how patients search.

Many prospective clients search for concerns such as acne, rosacea, pigmentation or ageing skin before they search for a specific treatment.

The dedicated Conditions section allowed LHP Medical Aesthetics to address this behaviour directly, helping users find relevant information faster and creating stronger pathways towards appropriate treatments.

Building Authority Through Content

The content cluster strategy enabled LHP Medical Aesthetics to grow beyond individual treatment pages.

By creating supporting content around key aesthetic themes and patient concerns, the website was able to address a wider range of search intents while strengthening the authority of core treatment pages through strategic internal linking.

This approach laid the foundations for continued long-term organic growth.

Conclusion

The LHP Medical Aesthetics project demonstrates the value of combining data analysis, SEO expertise and content strategy to drive sustainable growth.

Through a comprehensive programme of keyword research, website optimisation, condition-led content development and topical authority building, Dancing Badger helped transform organic search into the clinic’s leading digital acquisition channel.

The result was a 75.07% increase in organic traffic, a 73.35% increase in organic search sessions and significantly greater visibility across both treatment and condition-focused searches, helping more prospective patients discover the right solutions at the right stage of their journey.

Executive summary Search visibility is no longer limited to pages on your website.

Google can surface and measure content from platforms such as Instagram, TikTok, X and YouTube, while AI-led search experiences increasingly connect information from multiple sources before a customer ever reaches a website.

Your website still matters enormously. But modern SEO increasingly means making sure your brand is clear, useful and discoverable across the wider digital places where people search, research and compare.

Takeaway: SEO is becoming less about ranking one website and more about building a connected search presence wherever your customers look for answers.

For years, SEO was easy to picture.

A customer searched Google. Google showed a list of websites. The goal was to make your website appear as high as possible for the searches that mattered.

That is still part of search optimisation — and a very important part.

But it is no longer the whole picture.

Search results can now include videos, social posts, local listings, images, products, discussion content, AI-generated answers and traditional website pages. Customers can discover a business on one platform, research it on another and only visit the website much later in the journey.

Google itself is now acknowledging this change in the tools it gives marketers.

In July 2026, Google made new Search Console platform properties globally available, allowing businesses and creators to see how content from Instagram, TikTok, X and YouTube performs in Google Search, Discover and Google News.

That is a significant shift.

Search Console has traditionally been one of the clearest windows into the performance of a website in Google. It can now show search impressions, clicks and queries for content that does not live on your website at all.

If Google is measuring the search performance of your social and video content, SEO can no longer be thought of as something that happens only inside the website CMS.

01 The search result has changed

Your website is still important. It is just no longer the only thing that can be found.

The traditional ten-blue-links view of Google has been changing for a long time.

Maps, Shopping results, images, videos and featured results have already changed how people move through search. AI Overviews and AI Mode have pushed that change further by helping people explore more complex questions without following a simple one-query, one-result journey.

Google says its AI search features can use multiple related searches across different subtopics and data sources before building a response and linking people to supporting content.

At the same time, social and video content is becoming easier for Google to surface and measure.

This means a brand can appear in search through several different assets rather than one website URL.

Owned Website pages

Service pages, product pages, articles, guides, case studies and landing pages.

Social Social posts

Public content on platforms such as Instagram, TikTok and X can become part of search discovery.

Video YouTube & video

Video can appear across standard results, video search, images and Discover.

Local Business information

Profiles, reviews, locations and locally relevant information influence how a brand is discovered.

AI search Supporting sources

AI Overviews and AI Mode can surface links from a wider set of relevant pages and sources.

One brand, multiple search surfaces

The opportunity is no longer simply “rank the homepage”. It is to make the brand discoverable wherever the customer’s question is being answered.

This changes the role of SEO.

Technical health, site structure, page quality, internal linking and search intent remain fundamental. Google is explicit that the same core SEO best practices continue to apply to AI Overviews and AI Mode.

But businesses now need to think about the wider collection of content and profiles representing them in search.

02 Google has made the shift measurable

Search Console now measures social and video content

One of the clearest signs that search is expanding beyond the website came from Google Search Console in July 2026.

Google introduced platform properties for Instagram, TikTok, X and YouTube. After an initial rollout, Google confirmed on 29 July that they were globally available.

A verified platform property can show the Google search terms that led people to social or video content, along with clicks, impressions, trending content and broader performance information.

Google also encourages businesses and creators to compare performance across platforms and use the data to influence future topics, captions, titles and content formats.

Instagram

See which posts and search themes are generating visibility from Google.

TikTok

Track search discovery of short-form content and the queries behind it.

Measure the Google search performance of public posts and account content.

YouTube

Connect video discovery with the search terms and content driving visibility.

Google Search Console One search-performance view

Clicks, impressions, queries, trending posts and platform-level visibility can help shape a connected search and content strategy.

That creates a useful new relationship between SEO, social media and content.

A social team no longer needs to judge every post only by likes, comments or platform reach. Some content may also be answering searchable questions and building visibility outside the social platform itself.

Equally, an SEO team can use social and video performance as another source of customer-language and topic insight.

If a YouTube video or Instagram post is repeatedly being discovered for a particular question, that may be evidence for a new article, service page, FAQ, video series or campaign.

Search data can start informing social content — and social search data can start informing SEO.

Google’s platform-property guidance

Google announced platform properties in July 2026 and confirmed their global availability on 29 July. Read Google’s platform properties and social/video performance guide for the latest setup and reporting information.

If customers can discover your expertise before they reach your website, search strategy has to start before the website too.

03 Content needs different jobs

One idea can create visibility across several search environments

This does not mean copying the same piece of content onto every platform.

Different formats answer different parts of the customer journey.

A detailed website article may explain a complex subject properly. A short video can demonstrate a process quickly. A social post can show a first-hand example. A case study can provide proof. A service page can turn that research into an enquiry.

The strongest strategy gives each format a role while keeping the subject, expertise and brand position connected.

01 Website guide

Own the detailed explanation, evidence, internal links and next step on a platform you control.

02 Short-form video

Turn one useful part of the subject into an accessible demonstration, answer or viewpoint.

03 Social post

Surface the idea in a format designed for discovery, conversation or first-hand perspective.

04 Long-form video

Explain nuance, comparisons or process in a format that can also gain Google visibility.

05 Case study

Show that the business has real experience applying the subject rather than only discussing it.

06 Commercial page

Give customers who are ready to act a clear route into the relevant product, service or enquiry.

This is one reason copywriting and content strategy should increasingly work across channels rather than treating the blog as the only “SEO content” channel.

It also creates an opportunity to make social content more useful.

Rather than posting because the content calendar says Tuesday needs a post, businesses can create content around genuine questions, customer problems, product detail, expertise and first-hand experience — all things that may also have value in search.

That makes social media less disconnected from search strategy and gives both teams better evidence for what people actually care about.

04 AI search widens the source pool

AI-led search makes your wider digital footprint more important

AI Overviews and AI Mode add another layer to this change.

Google says these experiences can use a process called query fan-out: the system explores several related searches, subtopics and data sources before generating a response and presenting supporting links.

Google is also clear that there is no special “AI SEO” markup required to appear. The existing fundamentals still matter: indexable content, helpful information, strong page experience, clear text, relevant images and video, accurate structured data and up-to-date business information.

That is important because it prevents businesses from chasing another fashionable technical shortcut.

The practical implication is more straightforward: useful, credible information needs to exist in places search systems can understand and customers can trust.

Expert website content Detailed guides, services, products and first-party information.

Video Demonstrations, explanations, reviews and visual expertise.

Social content Public posts, first-hand perspectives and timely commentary.

Business information Profiles, locations, product data and other structured signals.

Search & AI discovery

Google evaluates relevant, eligible information across search systems and can provide supporting links within AI experiences.

Customer research

The user may learn about the brand, compare options, watch content or read supporting material before ever arriving on the main commercial page.

This connects closely with our earlier insight, Your Customers May Find You Before They Ever Visit Your Website.

The customer journey is increasingly being shaped before the website session begins.

That means the content people encounter elsewhere needs to reinforce the same expertise, positioning and proposition they eventually find on the site.

Our AI marketing and SEO work therefore needs to sit alongside brand, content and website strategy rather than becoming a completely separate discipline.

Google’s guidance on AI features

Google says there are no additional technical requirements or special schema needed specifically for AI Overviews or AI Mode. Its advice remains to follow strong SEO fundamentals and create useful, reliable content. See Google’s AI features and your website guidance.

05 Google is connecting brand content

Search profiles make the connected-brand idea even clearer

Google has also introduced Search profiles, which bring together content associated with a creator or publisher from across the web and social platforms.

Google’s current guidance says a Search profile can connect content from a website with channels including Instagram, TikTok, YouTube, X and Facebook.

People can follow that profile on Google, and Google says content linked to the profile may then be more likely to appear for that audience in Discover.

Again, this is not a reason to abandon the website.

It is evidence that search engines increasingly understand a brand, publisher or creator as something that exists across more than one URL.

For businesses, consistency therefore matters.

Names, descriptions, expertise, visual identity, topics and profile information should make sense together rather than presenting five disconnected versions of the organisation.

On the website itself, structured data can also help Google understand identity. Google’s organisation guidance allows businesses to reference external profile pages using sameAs URLs, further connecting the owned site with relevant profiles elsewhere.

Search profiles and brand identity

Read Google’s Search profile guidance and Organisation structured data documentation for current implementation detail.

06 The website still has a unique role

SEO moving beyond the website does not make the website less important

There is an important distinction here.

Social platforms can create discovery. Video can create understanding. Search features can surface an answer. AI can introduce a source.

But the website remains the digital asset the business controls most directly.

You control the structure, the customer journey, the depth of information, the commercial pages, the conversion path, the analytics setup and the relationship between one piece of content and another.

A platform can change its algorithm, format, rules or reach. The website should remain the strongest owned source of truth for the business.

Owned asset

Your website

The place where the business controls the experience from discovery through to conversion.

Detailed service and product information
Case studies, evidence and expertise
Internal linking and site architecture
Conversion journeys and calls to action
First-party analytics and measurement

Platform presence

Social, video & search surfaces

Places where customers can discover, follow, compare and interact with the brand before visiting the site.

Instagram, TikTok and X content
YouTube and other video discovery
Google Search and Discover visibility
Business profiles and local information
AI-led search and supporting links

That is why website design and SEO still need to work together.

The wider digital ecosystem can attract attention and create trust, but the site still needs to turn that interest into something commercially useful.

A business that becomes more visible across Google and social platforms but sends people to a confusing or weak website has improved discovery without improving the outcome.

Visibility and conversion still need to connect.

07 What modern SEO should look like

Build search visibility around the subject, not just the URL

The most useful change businesses can make is to stop thinking about SEO as a list of website tasks.

Instead, start with the customer question or commercial topic.

What is the customer trying to understand? Which part of that question belongs on the website? Would it benefit from video? Is there first-hand material that would work on social? Is there a local or product-data component? Where should the customer go when they are ready to act?

This turns SEO from a page-ranking exercise into a connected visibility strategy.

It also fits the principle behind our Growth Strategy work: channels should have jobs within the wider customer journey rather than operating as isolated activities.

A practical search-visibility review

1 Protect the website fundamentals Keep technical SEO, indexability, internal linking, page quality, structured data and user experience strong. The website remains the foundation.

2 Map where customers search and research Identify whether the audience also uses YouTube, social platforms, local results, product results or AI-led search when making decisions.

3 Connect Search Console platform properties Where relevant, verify Instagram, TikTok, X and YouTube so search visibility from those platforms can be measured rather than guessed.

4 Turn search insight into multi-format content Use genuine search questions to inform articles, social posts, short-form video, long-form video, FAQs and commercial pages.

5 Keep identity consistent Make sure profiles, website content, descriptions, topics and structured information clearly describe the same brand and expertise.

6 Measure the business outcome Search impressions are useful, but they still need to connect to visits, enquiries, sales, customers and commercial growth.

Measurement is particularly important because broader visibility creates more assisted journeys.

A customer may watch a video, later search the brand name, visit directly and then enquire. The platform that introduced the business may not receive the final attribution.

Our Data Analysis work and DB Analytics are designed to look at the wider behaviour rather than treating the last visible touchpoint as the whole story.

For more on that principle, read Knowing What Data Analytics to Track Based on Your Marketing Goals.

08 The opportunity

SEO is becoming a bigger part of brand and content strategy

Search optimisation used to be easy to separate from the rest of marketing.

The SEO team changed website pages. The social team managed social channels. The content team wrote articles. The website team looked after the site.

That separation makes less sense when a social post can generate Google search impressions, a YouTube video can appear in search results, AI search can surface supporting links, and customers can move between all of those environments before converting.

The specialist disciplines still matter.

But the insight needs to travel between them.

Search terms can inform social content. Social engagement can reveal new content themes. Video can strengthen an article. Website behaviour can show which subjects create commercial interest. Customer questions can become the next round of search content.

This is the same wider principle explored in Why More Marketing Activity Doesn’t Always Mean More Growth: the value increases when the channels stop learning in isolation.

The new search landscape

Your website is still the foundation. But your search presence is now much bigger than your website.

Strong modern SEO connects technical performance, useful website content, social discovery, video, brand identity, AI search visibility and commercial measurement around the same customer questions.

At Dancing Badger, that means treating SEO as part of a wider growth system.

We still care deeply about rankings, technical quality and website performance.

But we also need to understand how people are discovering the brand before they reach the site, what content is shaping that decision and which search surfaces are creating useful visibility.

The question is no longer simply, “Where does our website rank?”

It is, “When our customers look for answers, where does our brand appear — and what do they find when it does?”

Service SEO

Technical, content and search strategy designed around relevant visibility and commercial outcomes.

Service Social Media

Content and channel strategy that builds discovery, engagement and useful audience insight.

Partner Google

Search, advertising and analytics tools used to understand demand, visibility and customer behaviour.

Partner Meta

Instagram and Facebook form part of the wider social discovery and content ecosystem.

Is your SEO strategy still focused only on your website?

We can review how your brand is being discovered across Google, social, video, AI-led search and your own website — then identify the content, technical and measurement opportunities most likely to improve meaningful visibility.

SEO Social Media Copywriting AI Marketing Growth Strategy Data Analysis DB Analytics Website Design Google Meta

The project starts before anybody starts designing

There is a process. But it isn’t a production line.

A brief tells us where to start — not necessarily where to finish

Research is how we reduce expensive guesswork

The right specialists need to be involved before their ‘stage’ begins

Good digital work is rarely the product of one discipline.

Business context

Evidence

Experience

Language

Delivery

What happens next

Design is where strategy starts becoming visible

Development is not where the thinking stops

Content, SEO and tracking are not jobs we want to discover at the end

Testing is where we deliberately look for problems

Ready to launch means more than “the page loads”.

Then comes the part everybody sees: launch

Launch gives us something planning never can: real behaviour.

Good project management is partly about keeping all of that connected

The process matters, but so does knowing when to adapt it

What clients see is the outcome. Our job is everything behind it.

The finished project might look simple. Getting to the right kind of simple usually takes a lot of thinking.

The further a task moves towards judgement, the more the human matters.

Organise

Research

Analyse

Create

Interpret

Decide

We started with the work that takes time

Research can become faster without becoming automatic

AI can accelerate the journey. It shouldn’t remove the checkpoints.

AI can help us interrogate data more quickly

Content is one of the easiest places to use AI — and one of the easiest places to get it wrong

Different disciplines use AI differently.

Research & strategy

Data & performance

Content & marketing

Development & technical work

Development is becoming AI-assisted too

Strategy is where human judgement becomes more important

Better tools make good judgement more valuable, not less.

Context

Judgement

Creativity

Accountability

We don’t assume that an AI answer is the right answer

Generated quickly. Checked properly.

AI is changing what valuable agency time looks like

AI is becoming part of the workflow, rather than a separate activity

So what does that mean for our clients?

The more capable the technology becomes, the more important it is to know when to trust it, when to challenge it and when not to use it at all.

Key Results

+24.7%

Increase in Organic Search Traffic

+66.6%

Increase in AI Discovery Traffic

+25%

Increase in Searches for “The Great Barn Exeter”

121

Wedding-Enquiry Actions Generated Through Google Ads

The Client

The Challenge

Our Role

Website Development & Technical Delivery

SEO Consultancy

Google Ads Setup

Strategic Consultancy

The Approach

Results

Key Outcomes

Improving Visibility for Wedding Venue Searches

Supporting, Not Replacing, Internal Teams

Conclusion

Customers see a product page. Platforms see a product record.

The product page persuades the customer. Structured product data helps platforms understand the offer.

The product page

The product record

One product record can now influence several sales and marketing channels