Dancing Badger Dancing Badger

Explore

News

A structured route into Dancing Badger's strategy, web, design and analytics ecosystem.

View overview

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.

A typical project · From first conversation to what happens next

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

Different projects place more emphasis on different stages. The important part is that learning at one stage can influence what happens elsewhere.
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.

One project · Different perspectives

Good digital work is rarely the product of one discipline.

Not every project needs every specialist. The value comes from involving the relevant expertise when the project needs it.
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?

Pre-launch · Looking at the project from different angles

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

Quality assurance is partly technical and partly about stepping back from the project to make sure the whole experience still makes sense.
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.

After launch · The feedback loop

Launch gives us something planning never can: real behaviour.

The most useful digital projects continue learning. Performance data and client feedback can then inform the next round of decisions.
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.

Over the years, one question has come up again and again in conversations with our clients: “Is our website and digital marketing actually working?”

It sounds like a simple question.

The problem is that the answer is often spread across analytics dashboards, advertising platforms, ecommerce reports, search data and spreadsheets.

Businesses have access to more data than ever before, but more data does not automatically mean more clarity. In fact, it can create the opposite problem.

There are hundreds of metrics available, different platforms can tell slightly different stories, and it is easy to spend more time looking at reports than deciding what to do next.

Why we built DB Analytics ultimately comes down to that problem.

We wanted a clearer way to understand website performance, connect it to the wider marketing picture and make the information genuinely useful when deciding what should happen next.

That became DB Analytics.

Businesses don’t need more data. They need clearer answers.

Analytics had become harder to explain than it needed to be

Analytics has always been a fundamental part of how we work.

If we are designing a website, running an SEO campaign, managing paid advertising or improving an ecommerce store, we need to understand what people do once they arrive.

Where did they come from?

Which pages did they visit?

What made them continue?

Where did they leave?

Did they enquire, purchase, sign up or take another valuable action?

Those questions matter far more to most businesses than the mechanics of an analytics platform.

Google Analytics has been an important part of the digital marketing landscape for years, and Google Analytics 4 remains an extremely powerful platform.

But we increasingly found ourselves spending time translating analytics rather than discussing what the analytics meant.

For someone who works inside analytics every day, navigating reports, dimensions, events and attribution models becomes second nature.

For a business owner or marketing manager who logs in occasionally, the experience can feel very different.

We wanted something that made the important information easier to see, easier to explain and — most importantly — easier to act on.

We wanted to move from reporting data to making decisions

A dashboard should not be the end of the process.

Knowing that website traffic increased by 18%, for example, might be interesting.

But it immediately raises another question: was that additional traffic valuable?

Did it generate more enquiries?

Did ecommerce revenue increase?

Which marketing channel produced it?

Did visitors reach the pages we wanted them to reach?

Did one campaign perform significantly better than another?

That difference — between reporting what happened and understanding what to do next — became one of the guiding principles behind DB Analytics.

From activity to action · Analytics with a purpose

Good analytics should lead to a decision.

Traffic figures are useful. Understanding what happened after somebody arrived — and what to do about it — is where analytics becomes commercially valuable.
01 Activity

Search, paid advertising, social, email, referrals and other activity bring people to the website.

02 Behaviour

Understand what visitors view, where they move next and how they interact with the site.

03 Conversion

Connect website behaviour with enquiries, purchases and the actions that actually matter.

04 Insight

Identify the channels, pages and journeys that appear to be contributing to performance.

05 Decision

Decide what should be improved, tested, prioritised or investigated next.

Why we chose Matomo as the foundation

We did not want to reinvent web analytics technology from scratch.

We wanted to create a better way of using it.

DB Analytics is powered by Matomo, an established open-source analytics platform with a strong focus on privacy, first-party analytics and control over website data.

That gave us a powerful analytics foundation while allowing us to shape the implementation, reporting and client experience around what we actually needed.

Privacy was an important part of that decision too.

The digital landscape has changed significantly in recent years, with businesses and consumers becoming far more aware of how website data is collected and used.

Matomo gives organisations extensive privacy controls and greater control over their analytics data.

But technology alone was never the objective.

The important part for us was what we could build around it.

The technology behind it
A proven analytics platform, shaped around the way we work with clients.

Matomo provides the analytics engine underneath DB Analytics. Our focus is on how the data is configured, interpreted and used to support better conversations about website and marketing performance.

Learn more about Matomo →

Building analytics around the questions our clients actually ask

When clients talk to us about website performance, they rarely start by asking for a particular analytics metric.

They ask commercial questions.

Client questions · The things businesses actually want to know

Start with the question, not the metric.

The purpose of analytics is not to teach clients the language of analytics. It is to help answer the questions that matter to the business.
Acquisition “Where are our enquiries coming from?”
Revenue “Which marketing is generating sales?”
Behaviour “What are people actually doing on the website?”
Content “Which pages are performing best?”
Performance “Why has something suddenly changed?”
Priority “What should we do next?”

Those are commercial questions, not analytics questions.

So rather than asking clients to learn the language of analytics, we wanted DB Analytics to help us translate website activity into information that supports those conversations.

That means looking beyond headline traffic figures and understanding traffic sources, landing pages, visitor journeys, goals, ecommerce activity and conversions in the context of the wider marketing being carried out.

Analytics works better when marketing isn’t viewed in isolation

One of the reasons we wanted our own analytics environment is that Dancing Badger does not work in isolated digital channels.

A website redesign can affect SEO.

Paid advertising can introduce a completely new audience to a site.

An email campaign can create a sudden spike in returning visitors.

Social content can influence people who later come back through search.

Changes to a product page can affect conversion rates even though the advertising campaign sending visitors there has not changed.

Looking at each platform separately only gives part of that story.

DB Analytics gives us a consistent website-level view that can sit alongside the specialist platforms we already use across digital marketing, search, paid advertising, ecommerce and email.

Connected performance · Bringing the signals together

The website is where different marketing journeys meet.

DB Analytics provides a website-level view that can be considered alongside the specialist platforms used to manage each individual marketing channel.
01 Marketing signals

SEO, PPC, social, email, referrals, campaigns and other activity introduce visitors to the website.

02 DB Analytics

Website behaviour, journeys, interactions, events, ecommerce activity and conversions.

03 Commercial context

What changed? Why might it matter? How does it relate to the wider activity taking place?

04 Next action

Improve, investigate, test, invest, refine — and then measure what happens next.

It isn’t about replacing every other platform

DB Analytics is not intended to pretend that one dashboard can replace every specialist marketing platform.

We still use the data available within tools such as Google Ads, Google Search Console, Meta, ecommerce platforms, email systems and SEO software when that is the right place to answer a particular question.

The value of DB Analytics is that it gives us another consistent layer: what happened on the website itself.

That distinction matters.

An advertising platform might tell us that somebody clicked an advert.

Search Console can show how a website appeared in organic search.

An email platform can tell us somebody clicked through from a campaign.

DB Analytics helps us understand what happened after they arrived.

It has also changed the way we talk about performance

One of the most useful outcomes of DB Analytics has not been a particular feature or report.

It has been the conversations it allows us to have.

Instead of reporting a collection of metrics simply because they are available, we can start with the commercial question and work backwards.

If the objective is to increase enquiries, we can look at which channels and landing pages contribute to those enquiries and where potential customers appear to leave.

If the objective is ecommerce growth, we can look beyond overall traffic and focus on the journeys and marketing activity associated with revenue.

If a campaign suddenly performs differently, we can investigate what changed rather than simply reporting that the number went up or down.

Good analytics shouldn’t just tell you what happened yesterday. It should help you decide what to do tomorrow.

DB Analytics is part of a bigger change in the way we work

Building DB Analytics also reflects how Dancing Badger itself has evolved.

Our work increasingly sits across websites, ecommerce, digital marketing, design and analytics rather than treating them as completely separate disciplines.

A better website can improve the performance of paid media.

Better analytics can reveal a conversion problem.

A conversion problem might lead to a design change.

Search data can influence content.

Ecommerce behaviour can change advertising strategy.

The stronger the connection between those areas, the better the decisions we can make.

That is why analytics now sits much closer to the centre of our approach.

It is not something added at the end of a project simply to produce a monthly report.

It is one of the signals we use to decide what happens next.

The platform is only part of the answer

There is one thing we have learned from working with analytics for years: no dashboard makes decisions for you.

Technology can collect the data, organise it and make patterns easier to see.

But someone still has to understand the business, ask the right questions and interpret what those patterns actually mean.

That is why we have never seen DB Analytics as simply another piece of software.

It is a tool that supports the wider relationship between our team and our clients — helping both sides work from the same information, challenge assumptions and make better-informed decisions.

And, like the rest of the work we do, it continues to evolve as we find new ways to connect website behaviour, marketing activity and commercial performance.

Why did we build DB Analytics?

Ultimately, the answer is fairly simple.

We built it because we wanted analytics to be clearer, more useful and easier to act on.

Not another dashboard full of numbers for the sake of having a dashboard.

Not another monthly report that gets opened once and forgotten.

A better way to answer the questions that actually matter: what is working, what isn’t, and what should we do next?

Why we built DB Analytics

Data becomes valuable when it helps somebody make a better decision.

DB Analytics was built to make the important signals easier to see, easier to discuss and easier to connect with the decisions that shape a website and its wider digital marketing.

DB Analytics
Make more sense of your website data.

If you’re trying to understand which parts of your website and digital marketing are driving results, DB Analytics can help turn website activity into a clearer picture of what’s happening and what to prioritise next.

One of the most important pieces of infrastructure behind online advertising has just been ordered to become more open.

On 16 September 2026, the full remedies in the US Department of Justice’s ad-tech case against Google were made public. The US District Court for the Eastern District of Virginia stopped short of breaking Google’s advertising technology business apart, but imposed a six-year package of interoperability, data-sharing and anti-discrimination requirements across key parts of its open-web advertising stack.

This is not another Google Ads interface update. It reaches much further into the machinery that sits between advertisers, ad exchanges and the publishers selling advertising space across the open web.

Google keeps its ad exchange and publisher ad server. What changes is how tightly those products can be connected to each other — and how easily rival technology can compete around them.
16 Sep 2026 The court’s remedies were unsealed after its April 2025 liability decision found that Google had unlawfully monopolised open-web publisher ad-server and ad-exchange markets and unlawfully tied DFP to AdX. The new judgment focuses on changing that conduct rather than forcing a divestiture.

This is about the infrastructure behind digital advertising

When most businesses think about Google advertising, they think about search campaigns, Shopping, YouTube or Performance Max. The case is different.

It centres on open-web display advertising: the automated systems publishers use to sell advertising space and advertisers use to bid for it, often in the fraction of a second between somebody opening a webpage and the page finishing loading.

Google operates technology at several points in that process. Its publisher ad server, historically known as DoubleClick for Publishers or DFP, helps publishers manage and sell inventory. Its AdX exchange connects advertising demand with that inventory. Google also supplies advertiser demand through its advertising products.

In April 2025, the court found that Google had unlawfully monopolised the publisher ad-server and ad-exchange markets for open-web display advertising and that the tie between DFP and AdX had harmed competition.

Ad tech · Simplified auction flow

What happens between an advertiser and a publisher?

A simplified view of the open-web display ecosystem at the centre of the ruling. Real programmatic auctions can involve additional platforms and intermediaries.
Buy side Advertiser demand

Brands and agencies use buying tools to bid for audiences and advertising opportunities.

Marketplace Ad exchange

Real-time auctions match advertiser demand with available publisher inventory.

Sell side Publisher ad server

The publisher decides which advertising opportunity wins and which advert is ultimately served.

The competition issue was not simply that Google participated in this chain. The court found that Google’s control of multiple layers, combined with the way DFP and AdX were tied together, restricted competition from rival ad-tech products.

That distinction is important for advertisers. The ruling is not a ban on Google advertising, and it does not mean businesses running PPC campaigns suddenly need to rebuild them.

What it does challenge is the structure underneath parts of programmatic display advertising — specifically whether publishers can access important Google demand while using competing technology elsewhere in their stack.

The ruling does not break up Google’s ad-tech business. It tries to create competition by forcing the existing stack to become more interoperable.

Google now has to open connections that were previously far more restricted

The remedies focus on behaviour and technical access rather than ownership.

Google is not being forced to sell AdX or DFP. Instead, it must create and support integrations that allow rival publisher technology to compete more effectively for the same advertising opportunities.

One of the biggest changes involves Prebid, the open-source technology widely used by publishers for header bidding. The court has ordered Google to support integrations between AdX and Prebid, and between DFP and Prebid. AdX must also be able to submit real-time bids into competing publisher ad servers.

Interoperability · Before and after

The practical direction of travel is from a tighter stack to more open connections.

This diagram is illustrative rather than a technical map of every auction route. The court’s order sets obligations that Google must now implement.
Previously
Google advertiser demand Highly valuable demand flowing through Google’s ecosystem.
Tighter link through Google’s own exchange and publisher technology
AdX + DFP The court found the tie between the two products had anticompetitive effects.
Rival publisher technology Could face disadvantages when trying to access the same demand on equivalent terms.

Publishers could have a commercial incentive to remain inside more of Google’s stack in order to retain effective access to Google demand.

Court-ordered direction
Google advertiser demand Still commercially important, but subject to non-discrimination requirements.
Required interoperability + non-discriminatory access
AdX + DFP Remain owned by Google, but must support specified integrations with rival systems.
Prebid + competing ad servers Gain routes to participate more directly without publishers having to use Google’s complete stack.

The objective is to make the choice of publisher technology less dependent on whether that publisher also wants access to Google’s advertising demand.

The court also ordered Google to make publisher data more portable. Publishers must be able to access and export their own data from DFP and AdX, reducing one of the practical barriers involved in changing technology providers.

Google’s advertiser network must also bid on a non-discriminatory basis rather than receiving preferential treatment because Google owns other parts of the transaction. The Department of Justice’s summary uses the historic name AdWords when describing this advertiser demand; marketers will know the current platform as Google Ads.

Compliance will be overseen by a monitor and technical committee for six years.

The judgment is significant, but it is not a breakup of Google

Much of the discussion around the case had focused on whether Google might be forced to divest part of its ad-tech operation. That did not happen.

The court concluded that behavioural remedies could be used instead. That means the impact will depend heavily on implementation: the quality of the integrations, the way auction data is shared, how non-discrimination is monitored and whether publishers find it commercially realistic to switch or diversify their technology.

The judgment · Four key facts

What the ruling actually changes.

The remedies are designed to alter market behaviour while leaving Google’s core ad-tech assets under Google ownership.
Ownership No forced sale

Google keeps AdX and DFP / Google Ad Manager rather than divesting them.

Access More interoperability

Google must support integrations with Prebid and competing publisher ad servers.

Data Greater portability

Publishers must be able to access and export their data from key Google ad-tech products.

Oversight Six-year regime

A monitor and technical committee will oversee compliance with the final judgment.

Google has consistently argued that forcing structural separation would disrupt publishers and advertisers and that its products compete in a market with many alternatives. It has also said it disagrees with the court’s underlying liability ruling and intends to appeal.

The Department of Justice takes the opposite view: that interoperability, data access and restrictions on self-preferencing are required to restore competition after the conduct identified by the court.

Those positions matter because this is not simply a technical disagreement. It is a debate about how much control one company should be able to exercise when it operates technology for buyers, sellers and the marketplace connecting them.

Publishers and independent ad-tech platforms are closest to the immediate impact

The most direct beneficiaries — if the remedies work as intended — are likely to be publishers and independent ad-tech providers.

Publishers could gain more freedom to choose how they manage advertising inventory without giving up effective access to important Google demand. Rival ad servers, exchanges and header-bidding technologies could gain a better opportunity to compete on the quality of their technology rather than on whether they are connected to Google’s wider ecosystem.

For agencies and advertisers, the effect is less immediate. Most businesses will not see a dramatic change inside their Google advertising account simply because the judgment has been published.

Industry impact · Distance from the ruling

Not every part of digital advertising will feel the change at the same speed.

The first-order effect is on publisher monetisation and programmatic infrastructure. Broader advertiser effects will depend on how the market responds.
Direct impact

Publishers

More choice around ad-serving technology, better access to their own data and potentially less dependence on one integrated stack.

Direct impact

Independent ad tech

Greater opportunity for exchanges, publisher ad servers and Prebid-based technology to compete for inventory and demand.

Indirect impact

Advertisers

Potential longer-term changes to auction competition, inventory access, transparency and pricing — but no guaranteed immediate reduction in media costs.

More competition in the infrastructure could influence advertiser outcomes, but the ruling itself does not guarantee cheaper advertising, better performance or lower platform fees.

That last point is important. Greater competition can create pressure for better products, clearer reporting and more efficient pricing, but it would be premature to claim that advertiser costs will automatically fall.

Programmatic advertising remains a complex market. Auction mechanics, publisher supply, audience data, platform fees, inventory quality and buyer demand all influence what advertisers ultimately pay and what publishers ultimately receive.

The bigger issue is how much of digital advertising happens inside black boxes

Even businesses that never buy open-web display advertising directly should pay attention to the principles behind the case.

Modern advertising has become increasingly automated. Campaign types such as Performance Max deliberately make more decisions on behalf of advertisers: audience selection, bidding, placements and creative combinations are increasingly handled by machine-learning systems rather than manually controlled line by line.

That automation can be extremely useful. It also makes transparency, independent data analysis and commercial measurement more important, because the platform optimising a campaign is often also the platform reporting whether that optimisation worked.

The ad-tech judgment addresses a different part of the market, but it reflects the same broader industry tension: how much control and visibility should sit with the platform, and how much should remain with its customers and competitors?

As advertising becomes more automated, access to data and independent measurement becomes more valuable — not less.

For advertisers, that makes it increasingly important to compare platform reporting with real commercial outcomes: qualified enquiries, orders, customer value, margin, geography and repeat business.

It is also why changes to the underlying advertising ecosystem matter even when they are invisible in the campaign interface. The rules governing access to inventory, demand and auction data shape the market in which those campaigns ultimately operate.

The implementation will matter more than the headline

The remedies are now public, but that does not mean the market changes overnight.

Google will need to build and support the required technical integrations. Publishers and independent platforms will need to test whether those connections work at commercial scale. The monitor and technical committee will need to assess whether Google is complying with the judgment in practice, not simply on paper.

There is also the appeals process. Google has said it disagrees with the court’s liability ruling, so the legal story is not necessarily finished.

And the market itself is moving. Retail media networks, connected TV, commerce media and AI-led advertising products are all changing where digital budgets are spent. By the time the six-year remedy period ends, the advertising ecosystem may look substantially different again.

That does not make the ruling irrelevant. It makes the underlying principle more important: competition increasingly depends on whether large platforms allow data, demand and technology to move between systems rather than remaining locked inside vertically integrated ecosystems.

The wider industry shift

Google keeps the stack. The court is trying to change the rules around how that stack connects to the rest of the market.

The next test is not whether the ruling sounds significant. It is whether publishers can genuinely use alternative technology, whether rivals can compete on more equal terms and whether that competition eventually produces a healthier advertising market for publishers and advertisers alike.

Primary sources and further reading

The key facts in this article are based on the court record and the published positions of the parties. For readers who want to go deeper, the principal source material is available below.

Over more than a decade of working with businesses on websites, digital marketing, ecommerce and analytics, one thing has become increasingly clear to us.

Most businesses do not have a shortage of data.

They have Google Analytics, Search Console, advertising platforms, ecommerce reports, CRM systems, SEO tools, spreadsheets, monthly dashboards and increasingly sophisticated technology telling them what is happening across their digital operation.

What they don’t always have is a clear answer to a much more important question.

What should we do next?

We didn’t build Growth Intelligence because businesses needed another dashboard. We built it because having more information doesn’t automatically make the next decision any clearer.

That problem has shaped a lot of the thinking behind Growth Strategy at Dancing Badger.

A client might know that organic traffic has fallen, paid search is becoming more expensive or conversion rates could be better.

They may also have opportunities in email, content, ecommerce, social advertising, website improvements and new markets.

All of those things can be true at the same time.

But budgets, internal resources and management attention are finite.

So the challenge isn’t simply identifying more things that could be done.

It’s deciding which things are most worth doing.

A long list of recommendations isn’t a growth strategy. The difficult part is deciding what deserves to happen first.

Reporting was only answering half the question

Digital reporting has become remarkably good at explaining what has already happened.

We can see which search terms generated clicks, which adverts produced conversions, which landing pages people visited, which products sold and where customers dropped out of a journey.

Through data analysis and our own DB Analytics platform, we have invested heavily in making that information easier for clients to understand.

But understanding yesterday doesn’t automatically tell you how to invest tomorrow.

A report can tell you that PPC produced 60 enquiries.

It doesn’t necessarily tell you whether increasing the budget is a better decision than improving the landing page, investing in SEO, fixing an ecommerce problem or developing a stronger retention programme.

That requires another layer.

Interpretation.

Commercial context.

Prioritisation.

And ultimately, a decision.

Growth Intelligence · From information to action

Data only becomes valuable when it changes what happens next.

Growth Intelligence is designed to create a clearer path from fragmented marketing information to practical commercial priorities.
Stage 01 Data

Bring together the signals already available across marketing, website, customer and commercial activity.

Stage 02 Insight

Understand what the numbers are actually saying about performance, behaviour and opportunity.

Stage 03 Priority

Compare opportunities and identify where time, budget and attention could have the greatest impact.

Stage 04 Action

Turn priorities into a practical roadmap across the appropriate channels and disciplines.

Stage 05 Measure

Compare the outcome with the original objective, learn from the result and inform the next decision.

The problem was never a lack of marketing opportunities

One of the things we see regularly is that growing businesses have far more potential marketing activity than they could realistically undertake.

Should they invest more in SEO?

Increase paid search?

Launch more paid social campaigns?

Improve the website?

Work on conversion rate optimisation?

Develop better email journeys?

Expand the ecommerce proposition?

Introduce new technology or AI?

There is rarely a shortage of sensible ideas.

The problem is that every idea competes with every other idea for the same money, people and time.

That is why we started thinking less about simply generating recommendations and more about creating a consistent way to compare them.

Connected intelligence · Look beyond the channel

The strongest decision rarely comes from one data source.

Growth decisions become more useful when digital performance is considered alongside customer behaviour and commercial reality.
Search & demand What people are searching for, where visibility exists and where unmet demand may be available.
Paid media Where spend is generating demand efficiently and where acquisition costs or audience quality are changing.
Website behaviour How people move through the site, where friction occurs and which journeys lead to meaningful action.
Customer data Which customers buy, return, enquire, spend more or create the greatest long-term value.
Commercial context Margin, capacity, seasonality, product priorities, markets and the realities behind the marketing numbers.
Strategic direction What the business is actually trying to achieve and which opportunities matter most over the coming months.

This broader view matters because channels can look successful when considered individually while still creating the wrong overall outcome.

A Google campaign can generate a high volume of conversions, but those conversions still need to become valuable customers.

A new WordPress or WooCommerce platform can create a much stronger digital foundation, but only if the business knows what that foundation needs to achieve.

An ecommerce business built around Shopify might have strong acquisition but an opportunity to improve repeat purchase or average order value.

A successful Meta campaign might reveal an audience or message that should influence other parts of the customer journey.

The technologies matter.

But understanding how they fit together matters more.

Prioritisation became the missing piece

This was the point where the idea for Growth Intelligence really started to take shape.

We wanted a clearer way to distinguish between something that is simply a good idea and something that deserves genuine priority.

Because those are not the same thing.

A technically valid SEO opportunity may have limited commercial value.

A website improvement might deliver a relatively small percentage increase in conversion but affect every marketing channel sending traffic to the site.

A paid media opportunity may be capable of delivering results almost immediately, while a larger organic opportunity could require a much longer investment horizon.

None of those makes one channel inherently better than another.

They simply need to be assessed in context.

Prioritisation · Separate possibility from priority

A good opportunity still has to earn its place in the plan.

Growth Intelligence helps frame recommendations around commercial potential, practicality and the evidence available.
Opportunity

Could this create meaningful growth?

  • Size of the potential audience
  • Commercial value of the outcome
  • Impact across the wider customer journey
  • Fit with current business priorities
Priority

Is this where we should act next?

The strongest recommendation sits where commercial opportunity, available evidence and practical delivery come together.

  • What happens if we do it now?
  • What happens if we delay it?
  • What else competes for the same investment?
  • What dependency needs solving first?
Practicality

Can the business realistically deliver it?

  • Budget and available resources
  • Internal capacity
  • Technical dependencies
  • Expected time to impact

This is also why Growth Intelligence isn’t intended to produce a giant checklist of everything that could theoretically be improved.

Most businesses already have enough lists.

What is more useful is a shorter number of clearly prioritised actions, accompanied by an explanation of why they matter and how they fit into the wider plan.

The goal isn’t to identify everything a business could do. It’s to make the next decision easier to defend.

We wanted strategy to become something practical

Strategy can easily become abstract.

A report identifies an opportunity. A presentation describes the direction. Everyone agrees with it.

Then Monday morning arrives.

What actually happens?

One of the principles behind Growth Intelligence is that strategic thinking should eventually become a clear sequence of work.

Some improvements should happen immediately.

Others need to be tested.

Some require technical development.

And some opportunities may be commercially attractive but only make sense after something else has been fixed first.

Roadmap · Different opportunities move at different speeds

Growth needs both quick wins and long-term investment.

A useful growth plan separates immediate actions from work that compounds over a longer period.
Now · 0–90 days

Remove friction

Address obvious blockers, improve measurement and act on opportunities capable of influencing performance quickly.

  • Tracking and attribution fixes
  • Paid media optimisation
  • Landing page improvements
  • Conversion issues
Next · 3–6 months

Build momentum

Develop the assets, journeys and channel improvements needed to create a stronger growth engine.

  • New landing pages
  • Email and retention journeys
  • Content development
  • Ecommerce improvements
Longer term · 6–12+ months

Compound advantage

Invest in areas where value builds over time and supports the wider direction of the business.

  • Organic search authority
  • AI and GEO visibility
  • Platform development
  • New markets and propositions

The result is intended to be more than a strategy document that gets presented once and then disappears into a folder.

It becomes a roadmap that can be revisited as performance changes, new information becomes available and the priorities of the business evolve.

Forecasting should improve the conversation, not pretend to predict the future

There was another recurring problem we wanted Growth Intelligence to address.

Marketing recommendations often arrive without enough commercial context.

“Increase PPC spend.”

“Invest in SEO.”

“Improve conversion.”

All reasonable statements.

But a business making an investment decision needs to ask what sits behind them.

What are we assuming?

How much investment is involved?

What would need to change for that investment to make sense?

And how will we know afterwards whether the original assumption was right?

Forecasting cannot remove uncertainty.

Nor should it be presented as a guarantee of what will happen.

But making assumptions explicit creates a much better basis for a commercial decision than leaving them hidden.

Forecasting · Make assumptions measurable

A forecast isn’t a promise. It’s a hypothesis we can test.

The objective is not perfect prediction. It is creating a clearer relationship between the decision, the assumption and the result.
01 Define

Agree the commercial objective and what improvement would actually matter.

02 Forecast

Set out the assumptions behind the proposed investment and expected change.

03 Act

Implement the agreed activity with a clear understanding of what it is intended to influence.

04 Learn

Compare forecast with reality, understand the difference and improve the next decision.

Growth Intelligence is also changing how we work as an agency

The development of Growth Intelligence reflects a broader change in the role Dancing Badger increasingly plays with clients.

We still design and develop websites.

We still run SEO, PPC, paid social, email and digital campaigns.

We still build ecommerce stores, integrate platforms and analyse performance.

Those specialist capabilities remain fundamental.

What is changing is the conversation that happens before them.

Rather than starting with:

“Which service do you need?”

We increasingly want to start with:

“What are you trying to achieve, and what is most likely to get you there?”

Sometimes the answer will be a new website.

Sometimes it will be paid media.

Sometimes it will be organic visibility, improved conversion, better customer retention or stronger data.

Sometimes the recommendation may involve several of those things working together.

And occasionally, the evidence may tell us that the right thing to do is not to invest in something new at all.

Growth Intelligence gives us a framework for making that conversation more structured and more transparent.

The principle · Strategy before activity

Four ideas sit at the centre of what we’re building.

Growth Intelligence is intended to support expert judgement, not replace it.

Start with the business

Marketing performance only makes sense when it is viewed alongside commercial goals, customers, margins, capacity and business direction.

Connect the channels

SEO, paid media, websites, ecommerce, email and customer data should inform one another rather than being managed as isolated disciplines.

Prioritise relentlessly

The output should not be the longest possible list of recommendations. It should make the most important actions easier to identify.

Keep learning

Every action creates new information. Strategy should change when the evidence changes rather than remaining fixed because it appeared in the original plan.

Built from the way our clients actually make decisions

Growth Intelligence hasn’t come from sitting in a room and imagining what a marketing strategy platform ought to look like.

It has grown out of the conversations we have with businesses every week.

Businesses trying to decide whether the next £10,000 belongs in advertising, development or organic growth.

Ecommerce teams trying to understand why traffic is increasing faster than revenue.

Marketing managers with reports from six different systems but no single view of what should take priority.

Management teams who need to understand the commercial case behind a marketing recommendation before approving investment.

And businesses that have reached a point where doing more activity is no longer enough.

They need to make better choices about the activity they already have.

Connected technology
Growth Intelligence sits above the platforms, not in place of them.

Our technology partnerships give clients access to specialist platforms across websites, ecommerce, advertising, data and customer engagement. Growth Intelligence is intended to help us interpret those different signals together and decide where they fit within the wider growth plan.

What we’re building towards

Growth Intelligence is still evolving.

And we expect it to continue evolving as we use it across more businesses, more sectors and more complicated growth challenges.

The ambition, however, is straightforward.

We want to make it easier to move from information to insight.

From insight to priority.

From priority to a practical plan.

And from that plan to measurable outcomes that improve the next decision.

In other words, Growth Intelligence isn’t about creating more marketing activity.

It’s about creating greater confidence in why that activity deserves to happen.

Why we built Growth Intelligence

If businesses already have all this data, deciding what to do next shouldn’t still be the hardest part.

Growth Intelligence is our attempt to close that gap — combining data, commercial context and human expertise to help turn complex digital opportunities into clearer priorities.

It also represents where Dancing Badger is heading as an agency.

Not away from delivery, but towards a stronger strategic layer around it.

Because a technically brilliant website, well-managed advertising campaign or ambitious SEO programme is only valuable if it is solving the right problem.

Our role is increasingly to help establish what that problem is, where the opportunity sits and which combination of expertise is most capable of changing the outcome.

That’s the thinking behind our Growth Strategy work.

And it’s why we’re building Growth Intelligence.

Looking for a clearer view of where your next growth opportunity sits?

Our Growth Strategy work looks across your business, marketing, customer journey and performance data to identify priorities before deciding where time and investment should go next.