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I Built Check Analytic Because Privacy Turned Analytics into a Liability! 🔥

I didn’t start CheckAnalytic.com because I wanted to compete with Google Analytics.

I built it because analytics stopped feeling like a tool — and started feeling like a risk.

Not a theoretical risk.

A practical one.

Analytics used to be simple. Then privacy changed everything.

A few years ago, analytics meant:

• add a script,

• see traffic,

• understand behavior,

• make decisions.

Today, especially in the EU, analytics means:

• consent banners,

• partial data,

• legal uncertainty,

• constant trade-offs.

The problem isn’t that teams don’t care about privacy.

It’s that most analytics tools were not designed for this environment.

Consent banners don’t solve the real problem

I implemented consent banners like everyone else.

What I got:

• fewer usable metrics,

• worse UX,

• and the uncomfortable feeling that compliance was still fragile.

Users clicked “Reject”.

Data disappeared.

Funnels broke.

And yet, the responsibility still stayed with me as the product owner.

That’s when I realized: consent is not a technical solution — it’s a legal workaround.

GDPR changed the cost structure of analytics

Under GDPR, you don’t just collect data — you defend it.

You need to justify:

• why you collect it,

• how long you keep it,

• who processes it,

• and how it’s protected.

For a small SaaS, that’s not just overhead.

It’s cognitive load that steals focus from the product.

I didn’t want analytics to be the most legally complex part of my stack.

Privacy-first stopped being an ideal. It became a constraint.

At some point, I stopped asking “How can we track more?”

And started asking:

“What do we actually need to know to run this business?”

The answer was surprisingly small:

• how many people visit,

• what pages and features matter,

• what converts,

• what doesn’t.

None of that required tracking individuals.

That’s why CheckAnalytic is intentionally minimal

CheckAnalytic is built around a simple idea:

If you don’t collect personal data, you don’t need to manage consent or defend collection.

So it:

• doesn’t use cookies,

• doesn’t identify users,

• doesn’t build profiles,

• doesn’t require consent banners.

It focuses on aggregate behavior, not people.

That’s a conscious trade-off — and I’m okay with it.

What I gave up — and why it was worth it

Yes, I lost:

• user-level journeys,

• long-term identifiers,

• hyper-granular attribution.

But I gained:

• predictable data,

• cleaner UX,

• lower legal stress,

• faster setup,

• and more trust in the numbers I see.

For my use cases, that was a net win.

I don’t think CheckAnalytic.com is for everyone

If you need:

• individual user tracking,

• advanced attribution models,

• deep personalization, you’ll need heavier tools.

But if you’re a SaaS founder who wants:

• clarity without surveillance,

• analytics without consent fatigue,

• insight without legal anxiety, then this approach might resonate.

The question I keep coming back to

If a SaaS product can:

• grow,

• iterate,

• and make solid decisions without tracking individuals…

Why do we still assume that invasive tracking is the default?

I don’t have a universal answer.

I just built the tool I needed — and it turns out others needed it too.

on January 1, 2026
  1. 3

    Love the minimalistic approach to analytics you described. With privacy regulations tightening and consent banners becoming the norm, it's refreshing to see a solution that focuses on aggregate metrics rather than intrusive tracking.

    I'm curious how CheckAnalytic captures event-based insights like button clicks or funnel steps without using cookies or user identifiers. Do you model flows purely at the page level, or are you intentionally avoiding funnel analytics altogether? Also, how have your users responded to the trade-off of losing individual-level detail – is the aggregate data enough for most SaaS founders?

    1. 2

      We deliberately shifted the abstraction level.

      We don’t track “users”, we track states and transitions. Events are modeled as business-relevant moments (e.g. signup_completed, pricing_viewed) and aggregated server-side. No identifiers, no stitching, no retroactive attribution. Button clicks are only useful if they represent a state change — otherwise they’re noise and we don’t recommend tracking them.

      Funnels
      Yes, funnels exist, but they’re event-based, not user-based. Think: “X% of sessions reached state B after state A within a time window”, not “user 123 did this”. This avoids consent dependency and keeps data stable under privacy constraints.

      Trade-off: no individual-level data
      This is intentional. Individual-level data creates false precision and legal risk. Most SaaS founders don’t actually need user replays or per-user paths to make decisions — they need to know:
      • where value is leaking
      • which steps are bottlenecks
      • whether changes move core metrics

      Aggregate data answers that reliably. The feedback we get is consistent: less data, fewer knobs, but higher trust in the numbers. For teams operating in the EU or planning long-term, this isn’t a compromise — it’s future-proofing.

  2. 2

    Do you think most SaaS actually needs user-level tracking, or is aggregate data enough?

    1. 1

      Decisions are made based on aggregates (conversion, drops, retention). User-level data gives the illusion of accuracy, complicates analytics, and breaks down due to privacy issues. It is only needed in narrow cases (enterprise, support). Aggregated data is sufficient for product growth.

  3. 1

    The aggregate vs. individual trade-off hits a deeper problem: most analytics show what users are doing, not whether they understand what they're doing.

    You can see someone clicked through your funnel, but did they know why? Did they understand the value at each step, or just follow the UI hoping it makes sense eventually?

    We're building voice agents that help users understand products in real-time, so they're not just clicking through — they're making informed decisions. The clarity gap matters more than the tracking gap.

    Curious if you've noticed a difference in user confidence when the product itself explains value instead of just measuring behavior: demogod.me

  4. 0

    Looks like the whole thing was written by AI

    1. 3

      You registered today to write me this comment) Thank you)

      1. 2

        The main thing is that you are helpful, and fortunately for me, I am communicating with a real person in your support team!

        P.S. - I hate it when I write to support and get a reply from a bot that is completely off-topic or similar, just to make it look like it answered my question!

      2. 0

        nah, i saw a YouTube video where some Russian dude made a similar product and thought it might be you

        1. 1

          Anything is possible, I don't deny that there may be similar projects and even designs! Everything can be copied, downloaded, bought! It is important that my clients feel a sense of privacy, receive constant support, and know that we are reliable!

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