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

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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.

Dancing Badger has changed significantly since we opened our doors in 2014.

We’re larger, more specialised and broader in capability than the agency we started more than a decade ago. But that evolution hasn’t come from adding services for the sake of becoming bigger.

It has been driven by the problems our clients ask us to solve.

How we’ve evolved to bring strategy, digital marketing, web and design together around one goal: helping our clients grow.

A new website quickly becomes a conversation about generating better-quality traffic. A successful advertising campaign raises questions about conversion. An ecommerce project leads into retention, email or automation. A rebrand has to work across the website, paid campaigns, social and every other customer touchpoint.

Web, marketing, data and creative no longer operate neatly in isolation.

Neither do we.

From delivering digital services to solving bigger problems

When Dancing Badger was founded, website design, development and digital marketing formed the core of what we did.

They still do.

But the digital landscape businesses operate in today is considerably more complex.

Customers might discover a business through Google, see an advert on Instagram, research it through an AI platform, visit the website several times, receive an email and eventually make an enquiry or purchase weeks later.

No single one of those interactions necessarily creates the customer.

The whole experience does.

That has changed the way we think about our role as an agency.

Rather than looking at a website, SEO, PPC, paid social or email marketing as individual services, we increasingly look at the complete customer journey and ask a more useful question:

What is actually preventing this business from growing?

Sometimes the answer is visibility.

Sometimes it’s the website.

Sometimes it’s positioning, creative or conversion.

And sometimes the biggest opportunity is simply making better use of the customers, technology and data a business already has.

That is why Growth Strategy has become such an important part of how we work.

Three specialist disciplines. One connected agency.

Today, Dancing Badger is structured around three core disciplines.

Digital Marketing

Our digital marketing work brings together search, paid media, social, content, email and audience strategy.

But generating more traffic isn’t the end goal.

The objective is to reach the right people, understand what motivates them and turn marketing investment into measurable commercial results.

That can mean developing an organic search strategy, managing substantial paid advertising budgets, building email journeys, identifying new audiences or creating a broader digital growth plan.

Different channels play different roles.

Our job is to understand how they work together.

Web

A website shouldn’t simply look good on launch day.

It needs to perform.

Our website design and development team builds websites and ecommerce platforms around what the business actually needs them to achieve — whether that’s generating enquiries, selling products, connecting with internal systems or supporting more sophisticated marketing activity.

Increasingly, that also means looking beyond the initial build.

Conversion Rate Optimisation helps us understand how people actually use a site and where improvements can turn more visitors into customers.

Third-party integrations connect websites with CRM platforms, ecommerce systems, marketing technology and the wider operational infrastructure behind a business.

And our growing relationships with technology partners are strengthening that capability further.

In 2026, for example, Dancing Badger became an official Automattic partner and recommended WordPress agency, giving our team an even closer relationship with the ecosystem behind WordPress and WooCommerce. Our recent partnership announcement explains more about what that means for our clients.

Design & Branding

How a business looks is only one part of branding.

How it communicates, how consistently it presents itself and how easily customers recognise and trust it matter just as much.

Our branding and creative work therefore sits alongside web and digital marketing rather than operating as a separate studio.

It means campaign creative can be developed with an understanding of where it will appear. Brand systems can be designed for digital environments from the outset. And websites can reflect the wider positioning and personality of the businesses behind them.

When strategy, creative and delivery are connected, each becomes stronger.

Strategy · Connected growth

The growth ecosystem

Sustainable growth comes from the relationship between marketing, experience, brand, data and strategy — not one discipline operating alone.
BUSINESS
GROWTH
DIGITAL MARKETING Attract the right audience
DESIGN & BRAND Build recognition and trust
DATA & STRATEGY Measure, learn and improve
WEB Create the right experience

Why bringing everything together matters

One of the problems with digital is that it is remarkably easy to optimise one part of a business while accidentally creating a problem somewhere else.

A PPC campaign can generate plenty of traffic while sending customers to a page that doesn’t convert.

A beautiful website can launch without a meaningful strategy for generating traffic.

An SEO campaign can improve rankings without attracting the type of visitor most likely to become a customer.

A strong piece of creative can generate attention without an effective journey afterwards.

Even reporting can become disconnected, with different platforms each claiming responsibility for the same customer.

We’ve seen every version of it.

The alternative is to consider each decision within the wider commercial picture.

Customer journey · Continual optimisation

Not a funnel with an end point. A cycle that gets smarter.

Each stage creates information that can improve the next — and feed back into what happens at the beginning.
01

ATTRACT

SEO · PPC · Paid Social · Content

02

ENGAGE

Brand · Creative · Messaging

03

CONVERT

Website · Ecommerce · CRO

04

RETAIN

Email · Audiences · Remarketing

05

LEARN

Analytics · Attribution · Strategy

LEARN ↺ ATTRACT — measurement informs what happens next.

Data has changed the conversations we have with clients

Having more data doesn’t automatically mean making better decisions.

Businesses have access to enormous amounts of information from advertising platforms, ecommerce systems, social networks, search tools and website analytics.

The difficult part is working out what matters.

That’s one of the reasons we’ve continued investing in our own approach to measurement and DB Analytics.

We want reporting to move beyond simply telling a client how many clicks an advert received or how many people visited a website.

The questions that matter

Which activity is generating customers? Where are opportunities being lost? Which audiences convert most effectively? Where should the next pound of marketing budget go? And what should we change next?

That distinction is important.

Data should inform decisions, not simply fill reports.

Our specialists use it to challenge assumptions, identify opportunities and continually refine the direction we’re taking.

Specialists who understand the bigger picture

Growing Dancing Badger hasn’t meant creating layers between our clients and the people doing the work.

We’ve deliberately taken a different approach.

Our team now brings together specialists across digital strategy, search, advertising, content, social, email, development, ecommerce, UX, analytics and design.

But clients still work directly with the people responsible for delivering their projects.

That matters because specialists make better decisions when they understand what everyone around them is trying to achieve.

A developer should understand the SEO implications of a technical decision.

A PPC specialist should care about the quality of the landing page they’re sending traffic to.

A designer should understand whether something needs to work on a billboard, Instagram advert, ecommerce product page or email.

And a strategist needs visibility across all of it.

Specialists in what we do.
Connected in how we do it.

DIGITAL MARKETING × WEB × DESIGN
Connected by strategy + data

Outcomes, not outputs

One thing hasn’t changed as Dancing Badger has evolved.

We have always believed digital work should have a purpose.

The number of campaigns launched, pages built, adverts created or reports produced might explain what we’ve been doing.

They don’t necessarily tell us whether it worked.

For us, the more important measures are the outcomes behind that activity.

  • Did the website generate more enquiries?
  • Did more visitors become customers?
  • Did revenue increase?
  • Did advertising become more efficient?
  • Did organic visibility improve?
  • Did the business enter a new market successfully?
  • Did we solve the problem we were originally brought in to solve?

That also means we’re comfortable telling clients when we don’t think they need something.

Being full-service shouldn’t mean trying to sell every client every service.

Quite the opposite.

Having specialists across different disciplines means we can look more objectively at the problem and recommend the combination of activity that makes commercial sense.

The next stage of Dancing Badger

We’re proud of how far Dancing Badger has come since 2014.

We’ve supported more than 300 businesses, expanded our specialist team, acquired another agency and built closer relationships with the technology businesses shaping the platforms our clients use every day.

But what matters more is where we go next.

AI is changing how customers discover information. Search behaviour is evolving. Ecommerce is becoming more sophisticated. Marketing platforms are becoming more automated. Websites are expected to connect with more of the systems behind a business.

At the same time, access to technology is becoming easier.

Knowing what to do with it is becoming more valuable.

Our role is to understand those changes, separate genuine opportunity from noise and help clients make better decisions about where to invest.

That is the agency we’re continuing to build.

Not simply somewhere businesses come for a website, an advertising campaign or a new brand.

A team they can turn to when they need to work out what comes next.

For years, the digital customer journey has been relatively easy to visualise.

Someone has a need. They search Google. They find an article or product page. They explore a website. They compare their options. Eventually, they make an enquiry or purchase.

It’s the familiar digital marketing funnel, and it still matters.

But it’s no longer the whole story.

Today, a potential customer could have researched their problem, understood the available options, compared several brands and even formed an opinion about your business before they have visited your website once.

AI is creating new entrances, shortcuts and loops within the customer journey — and that is changing what it means for a business to be discoverable online.

The funnel hasn’t disappeared. The journey through it has changed.

The traditional marketing funnel remains useful because the fundamental stages are much the same.

People become aware of a need. They research it. They consider their options. They make a decision.

What has changed is where those stages happen.

For years, search engines frequently acted as the gateway. Our job as marketers was to understand what people searched for, create the right content around those searches and build a website capable of turning that traffic into customers.

That journey hasn’t gone away.

Google says Search queries have reached an all-time high at the same time as its AI-powered search experiences have grown. AI Overviews now reach more than 2.5 billion monthly users, while AI Mode has surpassed one billion monthly users.1

Rather than search disappearing, something more interesting is happening.

Search is changing, while entirely new forms of digital discovery are developing alongside it.

The new customer journey is much less tidy

Imagine someone looking for a new winter coat.

Traditionally, they might search Google for “best waterproof men’s coat for winter”. They could visit several retailers, read a buying guide, compare products, look at reviews and eventually make a purchase.

Now imagine that same customer asks an AI assistant:

“I need a smart men’s coat for commuting in the UK. I want something waterproof, warm enough for winter, but not overly technical or outdoorsy. What should I look for?”

That is a very different starting point.

The AI could help them understand which materials and features matter, explain the difference between waterproof and water-resistant fabrics, introduce styles or terminology they hadn’t considered, and help narrow the options based on budget, intended use or personal preferences.

Depending on the question and the information available to it, it could also surface particular products, brands or sources worth investigating.

By the time that customer reaches Google — or your website — they may no longer be at the beginning of their journey.

They may already be halfway through it.

Graphic 01 · Customer journey

From a linear path to a connected discovery journey

The funnel still exists. Customers just don’t necessarily travel through it in a straight line anymore.
Then · Predominantly linear
Need
↓
Google Search
↓
Useful Content
↓
Product / Service Page
↓
Consideration
↓
Conversion
Now · Multiple entrances, shortcuts & loops
AI Assistant
Social / Video
Reviews
Website
Third-party Content
AI Comparison
Conversion
Brand / Direct
Instagram→ChatGPT→Google→Website→Reddit→ChatGPT→Direct visit→Purchase

AI can influence almost every stage

It’s tempting to think of AI as simply another top-of-funnel traffic source.

That misses the bigger change.

AI can appear almost anywhere in the customer journey.

Someone who has only just identified a need might ask an AI assistant what type of product they should be looking for. Someone researching options might use Google’s AI-powered search features to understand the differences between materials or products. A shopper who has narrowed their choice to two coats could ask an AI assistant to compare them.

And after purchasing, that same customer could use AI to ask how to care for, style or use the product.

So rather than asking “How do we rank in ChatGPT?”, the more useful question is:

Can our business be properly understood and represented wherever our customers are researching their decisions?

That is a much bigger marketing challenge — and it reflects what we are already seeing in consumer behaviour.

Adobe reported that traffic from generative AI platforms to UK retail websites rose 329% year-on-year during the 2025 holiday period. Adobe’s analysis says shoppers are using these tools to research products, compare options and look for deals before reaching retail sites.2

At the same time, Gartner’s consumer research points to a more nuanced picture: GenAI is currently complementing rather than simply replacing traditional search. In its survey, consumers were moving across several research environments and often continuing beyond AI summaries.3

Graphic 02 · AI touchpoints

AI isn’t another stage in the funnel

It can help shape discovery, research, consideration, comparison, purchase and even the post-purchase experience.
Discover
◎
AI recommendation
Research
?
AI explanation
Consider
≡
AI shortlist
Compare
⇄
AI comparison
Buy
✓
AI product search
Post-purchase
↻
AI support & advice
The journey can jump forwards, loop backwards and move between platforms at any point.

Your website may actually become more important

There’s an obvious question that follows all of this.

If people are getting more information from AI, does your website become less important?

We’d argue the opposite.

Its role is changing.

Your website isn’t only somewhere customers land after a Google search. It is increasingly part of the evidence layer that helps search engines, AI systems and prospective customers understand your organisation.

For a fashion brand, that might mean making it incredibly clear what you sell, who your products are designed for, which materials you use, how products fit, where they are made, how customers should care for them and what makes the brand different.

If that information is vague, shallow or scattered, it doesn’t only make life harder for people visiting your website. It can make your business harder for machines to understand too.

Strong product information, useful buying guides, clear category pages, brand stories, FAQs, reviews, sizing advice, material information and technically accessible content therefore become part of a much bigger picture.

Your website remains the digital home of your business. But increasingly, other platforms may be interpreting what’s inside it on your behalf.

For ecommerce brands, that makes the relationship between eCommerce design and development, content, search visibility and conversion increasingly difficult to separate.

Good content matters — but perhaps not in the way it used to

For years, businesses have been told to “create content for SEO”.

That has resulted in an enormous amount of content created primarily because somebody found a keyword with sufficient search volume.

Some of it is useful.

Quite a lot of it isn’t.

An AI-assisted customer journey makes genuinely useful content more important, not less.

Think about the questions someone might actually ask while deciding which coat to buy:

What is the difference between these two materials?

Which coat is best for wet but relatively mild weather?

How should this style fit?

Is it suitable for everyday commuting?

How do I care for this fabric?

What should I look for when comparing different brands?

Those questions don’t always fit neatly into traditional keyword research. But they represent real customer intent.

Good content therefore has to do more than attract a click. It needs to demonstrate knowledge, answer questions properly and provide useful information that both people and machines can understand.

Being discoverable is becoming bigger than SEO

None of this means SEO is dead. Far from it.

Many of the fundamentals of good SEO and search optimisation overlap heavily with what businesses need in an AI-assisted discovery environment: clear website architecture, strong and useful content, technical accessibility, authority, expertise, consistent business information and relevant third-party references.

Traditional search traffic also remains considerably larger than identifiable referral traffic from AI assistants.

Ahrefs’ May 2026 analysis of more than 74,000 websites reported that AI chatbots accounted for around 0.28% of total web traffic in March 2026, compared with 28.12% from Google.4

So this isn’t about abandoning SEO to chase the latest acronym.

Google is no longer the only environment where digital discovery happens.
2.5bn+

Monthly users reached by Google AI Overviews, according to Google in 2026.

+329%

Year-on-year growth in UK retail traffic from AI sources during the 2025 holiday period, according to Adobe.

0.28%

Share of total traffic from AI chatbots across Ahrefs’ March 2026 dataset — still small beside Google, but measurable.

Your digital footprint now extends well beyond your website

A business doesn’t exist online solely through the information it publishes itself.

Customers — and increasingly the systems helping them research — can encounter a brand through customer reviews, retail partners, editorial coverage, social platforms, YouTube, industry publications, forums and online communities, directories, influencers, comparison websites and marketplaces.

All of those sources contribute to the wider digital picture surrounding a business.

That means brand consistency matters. Product information matters. Reputation matters. PR matters. Reviews matter. Third-party mentions matter.

Your own website remains central, but the information published elsewhere about your business is becoming part of the discovery ecosystem too.

Marketing attribution is about to get even messier

There’s another challenge this creates.

Measurement.

Some AI referral traffic can be identified when customers click directly through from platforms such as ChatGPT or Perplexity. But many AI-influenced journeys won’t leave such a clean trail.

Someone might discover a business through an AI response and then Google the brand. They might remember the name and visit later. They could see a recommendation, leave the platform entirely and return days later through another channel.

The channel that receives the conversion therefore won’t necessarily be the channel that originally generated the demand.

Graphic 03 · Attribution

What happened vs what analytics may report

The final click can be measured accurately while still giving an incomplete picture of what created the demand.
What actually happened
AI research→ Brand discovered→ Google brand search→ Website→ Purchase
AI research→Brand remembered→Direct visit→Purchase
What analytics may report
Organic Search→Purchase
“Organic Search generated the sale.”
Direct→Purchase
“Direct generated the sale.”

So what should businesses actually do?

We don’t think the answer is to rip up your digital strategy and replace everything with an “AI strategy”.

The businesses best placed to adapt are likely to be those that get the fundamentals right.

Keep investing in search

Traditional search remains enormous, while AI is increasingly becoming part of the search experience itself. SEO isn’t disappearing; its scope is broadening.

Create genuinely useful content

Think beyond keywords. Understand the questions customers ask while discovering, researching, comparing and validating their options — then answer them properly.

Make your business easy to understand

It should be obvious what you do, what you sell, who you serve, what makes you different and where your expertise lies.

Improve product information

For ecommerce businesses, go beyond features. Cover fit, sizing, materials, use cases, care, construction, provenance and the questions customers need answered before buying.

Build authority beyond your site

PR, reviews, relevant publications, social platforms, directories and independent mentions all contribute to the wider picture surrounding your brand.

Measure beyond the last click

Consider brand search, direct traffic, assisted journeys, AI referrals, repeat visits, lead or order quality — and sometimes simply ask customers how they found you.

The funnel isn’t dead. We’ve just lost sight of parts of it.

Customers still become aware. They still research. They still compare. They still make decisions. The difference is that increasingly, those stages don’t all happen somewhere we can see.

A customer could spend 20 minutes researching a product category with an AI assistant before your business is ever mentioned. They could discover your brand through an AI-generated answer, validate it through Google, research products on your website, compare you elsewhere and return three days later directly.

From your analytics platform, you might see only the final few minutes of that journey.

That’s why the answer isn’t to chase every new platform independently. It’s to build a stronger digital ecosystem: a clear brand, useful and technically sound website, detailed product or service information, genuine expertise, strong content, consistent information, external authority and good measurement.

The traditional funnel still matters.
But the front door isn’t where it used to be.

Sources & further reading

  1. Google — New opportunities, control and insights for website owners (updated August 2026).
  2. Adobe Digital Insights — UK online retail spending hits record high (January 2026).
  3. Gartner — GenAI and traditional search consumer research (January 2026).
  4. Ahrefs — AI Chatbot Traffic: What It Is, and How to Get More (May 2026).