Why We Built DB Analytics
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.
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.
Good analytics should lead to a decision.
Search, paid advertising, social, email, referrals and other activity bring people to the website.
Understand what visitors view, where they move next and how they interact with the site.
Connect website behaviour with enquiries, purchases and the actions that actually matter.
Identify the channels, pages and journeys that appear to be contributing to performance.
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.
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.
Start with the question, not the metric.
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.
The website is where different marketing journeys meet.
SEO, PPC, social, email, referrals, campaigns and other activity introduce visitors to the website.
Website behaviour, journeys, interactions, events, ecommerce activity and conversions.
What changed? Why might it matter? How does it relate to the wider activity taking place?
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?
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.