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Digital analytics consultancy: making your data tell the truth

We help you measure properly before you decide. Because the problem is rarely a lack of data — it is that the data you have was poorly collected and nobody has checked.

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What does digital analytics involve?

Digital analytics involves measuring what happens on your website or application, interpreting it and turning it into decisions. That last part is the one almost nobody does.

Let me explain. Collecting data today is cheap and almost automatic. The hard part comes next: knowing whether the data is reliable, understanding what behaviour lies behind it, and deciding what you change on Monday morning. A dashboard full of charts that does not alter a single decision is an expensive ornament.

That is why the first thing we do in any project is not to build reports, but to audit the measurement you already have. Something almost always turns up.

And when I say almost always, I say it from experience. In March 2026 we audited our own website and discovered that our Google Analytics 4 was recording one session on the same day that Microsoft Clarity was recording seventy. Seventy to one. We had spent months looking at a number that meant nothing.

It is not pleasant to admit, least of all as an analytics consultancy. But it illustrates the point well: if it happened to us — and we do this for a living — imagine how many businesses are making decisions today based on broken data without knowing it.

Hence our first rule. Before analysing anything, we verify that what has been measured is true — and we verify it by cross-referencing two independent sources, which is the only way to discover that one of them is lying.

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Why hire a digital analytics consultancy?

The best reason is the one least mentioned in proposals: to stop arguing over opinions.

When measurement is reliable, meetings change tone. You no longer debate whether the campaign worked — you look. And decisions stop depending on who speaks loudest in the room.

With sound measurement you know three things you previously only intuited: what actually happened, why it happened, and what to do next.

Let me give you the correct order, which is almost always applied in reverse. First you define the decisions you want to be able to make. Then the questions that feed those decisions. And only at the end, the metrics and the tagging plan. Starting with tagging is how you end up with two hundred events that nobody looks at.

That is why we always start from business objectives, not from the tool. An ecommerce site, a lead-generation website and a media outlet that lives off advertising need to measure different things, even though all three have the same Analytics installed.

I would suggest distrusting any proposal that starts with ‘we install’ rather than ‘what do you need to decide’.

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Digital analytics tools

Matomo Analytics

Google Analytics 4

Google Tag Manager

Looker Studio

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What changes in your business when analytics works?

The decisions change, which is the only thing that justifies the cost. A pretty report has never made anyone money; what does is the decision taken afterwards. These are the concrete effects we see in the projects we manage:

Seeing which pages sustain the business and which merely take up space. Without that, investing in a redesign or new content is a coin toss.

Understanding why people abandon just before converting — which is the raw material for any serious conversion optimisation work.

Distributing credit across channels with judgement and stopping paying twice for the same sale in your paid campaigns.

Spotting opportunities invisible in the aggregate: a small segment that converts at three times the rate, a device where the funnel collapses entirely, a country that buys from you even though you have never paid it any attention.

And avoiding investments the data does not support. I would recommend measuring before increasing budget, not afterwards. It works out considerably cheaper.

This same principle is beginning to apply to AI visibility, which can also be measured — though almost nobody is doing it yet: we cover this ir AI search engine optimisation. 

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Frequently Asked Questions

Everything that leaves a trace: where people come from, what they do inside, where they get stuck, and what they end up buying or requesting.

Put like that it sounds like everything and nothing, so here is the useful cut. There are essentially three layers: acquisition — where they come from; behaviour — what they do once inside; and conversion — what they achieve and what you achieve. Most dashboards stop at the first, which is the easiest to pull and the one that decides the least.

The ones tied to a decision. Everything else is expensive entertainment.

Here is the filter we use at AMDT: if a metric rises or falls by 30% and you would not know what to do differently tomorrow, that metric should not occupy space in your report. Apply that criterion and dashboards slim down considerably — and you will be grateful.

In practice, what almost always remains is conversions and their value, the cost of acquisition per channel, and two or three friction indicators specific to the business. Sessions and page views are useful for diagnosis, not for decisions.

Matomo, Google Analytics 4, Google Tag Manager and Looker Studio — and we choose based on the case, not out of habit.

Without mixing things up: GA4 is powerful and free, but it samples, keeps limited history, and ties you to cookie consent. Matomo gives you full data ownership, no sampling and the option to measure without cookies, in exchange for someone maintaining it. For quite a few Spanish businesses the second option works out better, and we explain it in detail on its own page.

On top of that we add behavioural tools like Clarity when you need to see the session, not just count it. And yes, they are also useful for catching your Analytics telling fibs.

We start by doubting the data — including our own.

Any consultancy will tell you it analyses. Before analysing, we verify: we cross-reference at least two independent sources to check that what has been measured is true. It is a dull step, almost everyone skips it, and it is precisely where the nasty surprises appear.

The second thing is that we put in writing which part of a result is attributable to the work and which to the market. When we reviewed fourteen years of case files, we found that only 8 out of 137 had a genuinely extractable before-and-after; in the rest, the figures lived inside screenshots. We have changed that habit in-house, and it is the one we apply externally. This is in line with our commitment to Ethical SEO. 

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