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Product & web analytics

Nobody trusts the analytics numbers

Two dashboards disagree, the cookie banner ate a third of the traffic, and every meeting starts by arguing about whether the data is right.

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Recognise this?

What it looks like from the inside

If three of these are true, the tool has stopped fitting the team. If one is, it is probably worth waiting.

  • 01

    Two tools report different numbers for the same week

  • 02

    Consent refusals mean you are extrapolating from partial data

  • 03

    Nobody can answer a product question without a developer writing a query

  • 04

    The reporting nobody trusts still takes someone a day a month to produce

What separates the options

The questions that actually decide a analytics tool

Everyone asks about price and seat count. These are the ones specific to this category — and the ones our questionnaire asks you.

  1. 01

    What question are you actually trying to answer?

    How much traffic are we getting, and from where · What people do inside the product · Why people get stuck

  2. 02

    How much does the cookie banner matter to you?

    We want to avoid needing one · We have one, but data must stay in the EU · Not a concern

  3. 03

    Who reads the numbers?

    Anyone in the company, unaided · Product and engineering · Someone who will query the raw data

  4. 04

    Do you need the raw events in your own warehouse?

    Yes, we model data ourselves · Eventually · No

Questions

Before you move

Is switching analytics tool actually the fix?

Sometimes, and sometimes not. If the symptoms are about a capability the tool does not have — retention controls it cannot enforce, a price that scales the wrong way, an integration that does not exist — then switching solves it. If they are about how your team uses the tool, a new one will reproduce the same mess in a fresh interface within six months. The questionnaire asks what is driving the change precisely to separate those two cases.

Which analytics tool should we move to?

The credible options are Fathom Analytics, Google Analytics 4, Matomo, Plausible, PostHog. Which is right depends on your team size, budget and non-negotiables — a 12-person team with no compliance requirement and a 400-person team that needs EU data residency should not end up with the same answer. The questionnaire ranks all 5 against your specific situation.

What does it cost to fix?

Two numbers matter: the licence difference and the cost of the move itself. This category is priced on usage or a flat fee rather than seats, so the licence difference depends on volume rather than headcount. The migration is the bigger number, and it scales with history, integrations and headcount rather than with the tool you pick. The questionnaire estimates both.

How long does a switch like this take?

For a team under 50 with a handful of integrations, a few weeks of elapsed time and one to two weeks of actual work. Above 200 people, or with compliance in scope, plan a quarter. The single biggest variable is not the tool — it is how much history has to come with you, and how many other systems are wired into the one you are leaving.

Get the 5 options ranked for your team

About a dozen questions — team size, budget, timeline, what is non-negotiable — and you get a shortlist with the reasoning shown, plus what the move would cost.

Get my shortlist