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 has been poorly collected and nobody has checked it.
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What does digital analytics involve?
Digital analytics involves measuring what happens on your website or app, 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.
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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-checking 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.
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With sound measurement you know three things you previously only sensed: what really happened, why it happened and what to do next.
Let me give you the right order, which is almost always applied the other way round. First you define the decisions you want to be able to make. Then, the questions that answer those decisions. And only at the end, the metrics and the tagging plan. Starting with the tagging is how you end up with two hundred events that nobody looks at.
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.
Read more >
That is why we always start from the business objectives and not from the tool. An e-commerce site, a lead-generation website and a media outlet that lives off advertising need to measure different things, even if 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 clearly never made anyone money; what does is the decision taken afterwards. These are the concrete effects we see in the projects we run:
Seeing which pages hold up the business and which merely take up space. Without that, investing in a redesign or in new content is a coin toss.
Understanding why people drop out just before converting, which is the raw material for any serious conversion optimisation work.
Sharing out the credit between channels with judgement and no longer paying twice for the same sale in your paid campaigns.
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Spotting opportunities that cannot be seen 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 that the data does not back up. I would recommend measuring before increasing the budget, not afterwards. It works out considerably cheaper.
The same is starting to apply to AI visibility, which can also be measured, although almost nobody is doing it yet: we cover it in AI search engine optimisation.
What it costs and what it includes
From €850 per project. I am telling you up front because almost nobody publishes prices in this sector, and that forces you to request three quotes before you know whether it is a fit.
It is a project price, not a monthly fee: implementation or a one-off audit, with a fixed deliverable. If you then want ongoing support, we discuss it separately.
What is included
- An audit of what you already have. Before touching anything, we check whether your analytics measures what you think it measures. It is the part that brings the most surprises.
- Measurement plan. Which events, which conversions and which KPIs, written down before they are configured. Without this, what gets set up is an expensive visit counter.
- Configuration and verification of the appropriate tool, with consent and privacy compliance resolved, not pending.
- Dashboard with the figures you look at to make decisions, not the forty the tool comes with as standard.
- Attribution. Where each sale really comes from, including visits arriving from AI assistants: they are already a channel and almost nobody tracks them separately.
- Handover session so that your team can read it without depending on us.
Why we work with GA4 and with Matomo
Because they are not for the same thing. Google Analytics 4 is the standard and you need to know how to handle it. Matomo is the alternative when the data cannot leave Europe, when the company wants to own its own information, or when consent is leaving it blind in half of its sessions.
Clearly, almost anyone will set up GA4 for you and leave it at that. We tell you which of the two suits you, and why, before charging you for the implementation.
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Frequently asked questions
What exactly is analysed in web analytics?
Everything that leaves a trace: where people come from, what they do once 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 breakdown. There are basically three layers: acquisition, or where they come from; behaviour, or what they do once inside; and conversion, or 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.
Which metrics are genuinely worth watching?
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 take up space in your report. With that criterion, dashboards slim down enormously, and that is welcome.
In practice, what almost always remains is conversions and their value, the acquisition cost per channel and two or three friction indicators specific to the business. Sessions and page views are useful for diagnosis, not for decisions.
What digital analytics tools do you use?
Matomo, Google Analytics 4, Google Tag Manager and Looker Studio, and we choose according to the case, not out of habit.
Without mixing apples and oranges: GA4 is powerful and free, but it samples, keeps little history and ties you to cookie consent. Matomo leaves you owning the data, with 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 behaviour tools such as Clarity when you need to see the session and not just count it. And yes, they are also useful for catching your Analytics lying.
What makes AMDT different from other analytics consultancies?
That we start by doubting the data, including our own.
Any consultancy will tell you it analyses. Before analysing, we verify: we cross-check at least two independent sources to confirm that what has been measured is true. It is a boring step, almost everyone skips it, and it is exactly where the nasty surprises appear.
The second thing is that we put in writing which part of a result can be attributed to the work and which to the market. When we reviewed fourteen years of case files, we found that only 8 of 131 cases had a before and after that could genuinely be extracted; in the rest, the figures lived inside screenshots. We have changed that habit in-house, and it is the one we apply to client work. It is in line with our commitment to Ethical SEO.
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