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Switching to cookieless analytics: what you lose, and how to get it back

Analytics and feedback By 10 min read All posts

The short answer

Cookieless analytics keeps everything you can count within one visit: page views, referrers, UTM campaigns, countries, devices and events. What you lose when you switch from Google Analytics is anything that links one visit to the next: returning visitors, unique visitors across days, multi-visit funnels, attribution windows and demographics. List which of those you actually used for a decision, then replace each with an event per step, a campaign landing page or a question on the page, and drop the rest.

Plenty of sites swap Google Analytics for a cookieless tool to drop a consent banner or keep visitor data out of ad networks. The switch is easy. The surprise comes a few weeks later, when someone asks how many readers came back this month and the new dashboard has no answer.

No cookieless tool counts a person across days

Without a cookie, a tool can't tell that today's visitor is the same person as yesterday's. Each tool works around that in its own way, and the method decides what its "unique visitors" figure means.

From each tool's own documentation
ToolHow it counts unique visitorsRecognises a visitor the next day?
PlausibleA hash of a daily salt, the website domain, the IP address and the user agent. The salt is rotated and deleted every 24 hours, and the raw IP address and user agent are not storedNo
FathomA signature that rotates every 24 hours at midnight UTC. Someone who visits on Monday and again on Tuesday counts as two visitorsNo
Simple AnalyticsNo identifier at all. A page view counts as unique when it has no referrer or the referrer is another site. No cookies or other browser storageNo
Matomo, cookies disabledTurned on with disableCookies in the tracking code. Matomo still works out unique visitors from the IP address and other footprints, and says this is inaccurateNot reliably

So a "unique visitor" means "a visitor on this day" in Plausible and Fathom, and "an arrival from outside the site" in Simple Analytics. Expect the totals to differ from the users figure in Google Analytics, and when you compare the two tools, compare page views, not visitors.

What you keep: pages, sources, campaigns and events

Plausible, for example, keeps the page URL, referrers, campaign parameters, browser, operating system, device type, and an approximate country, region and city worked out from the IP address without storing it. Across the tools that gives you:

  • Page views and top pages, with entry and exit pages and visit duration within a single visit.
  • Referrers, and campaigns tagged with utm_source, utm_medium, utm_campaign and the other UTM parameters.
  • Custom events and conversions, such as a sign-up or a download. Plausible and Fathom have events, and Matomo has goals.
  • Scroll depth in some tools. Plausible tracks it by default; check your own tool before you rely on it.

If your weekly report is "which pages got read, where the readers came from and whether they clicked the button", nothing you need goes missing.

What you lose switching from Google Analytics

Everything that links one visit to another goes:

  • Returning visitors and unique visitors across days. Plausible and Fathom start a fresh count each day, so a reader who comes every morning is a new visitor every morning. Matomo says that with cookies off, new and returning visitor counts become inaccurate, and reports such as days since last visit treat every visit as new.
  • Funnels and cohorts across visits. A reader who reads a guide on Monday and signs up on Thursday is two unrelated visits. Matomo says its Cohorts and Multi Attribution reports show no data without cookies.
  • Attribution windows. Matomo credits a goal to the channel of the visit where it happened, so the newsletter that brought the reader in three days earlier gets nothing.
  • Demographics and interests. In Google Analytics 4 these come from Google signals, which covers consenting signed-in Google users with ads personalisation turned on. No cookieless tool has an equivalent.
  • Cross-device journeys, and remarketing audiences built from analytics visitors. Both need an identifier.

Go through this list and mark only the reports that fed a decision in the last six months. That is usually one or two of them, and they are the only ones worth replacing.

How to get the useful parts back without an identifier

Rebuild each report you marked as a total per page or per step, so nothing has to recognise a reader. Two of the replacements are questions on the page, which also give you what no analytics tool ever had: why a reader left. A reader who found the answer in 20 seconds looks the same in any dashboard as one who gave up after 20 seconds. "Did this page answer your question?" tells them apart, and the answer belongs to a page, not a person.

  1. Returning readers: ask how often they read

    A multiple choice question, "How often do you read this site?" with "First time", "Now and then" and "Most weeks", gives you the share of regular readers per page or section. It is self-reported, so track it over time and label it as such; don't compare it with your old figure.

  2. Sources your referrers miss: ask how they found the page

    "How did you find this page?" catches visits that arrive as direct, such as links shared in chat apps or answers from AI assistants.

  3. Funnels: count each step as an event

    Set an event for every step, such as guide read, pricing viewed and sign-up, and compare the counts for the same dates. You see where the numbers drop, without following anyone through.

  4. Campaigns: tag every link and give it its own landing page

    Put UTM parameters on every link you control, and give a campaign that matters its own landing page, so its conversions need no attribution window.

  5. Audience: one broad optional question, or nothing

    If demographics fed your content plan, ask "Which best describes you?" with four or five broad options on a few pages. Keep the groups large, so no answer narrows down to one person. Otherwise, drop them.

Cookieless doesn't settle the banner question

Article 5(3) of the ePrivacy Directive requires consent to store information on a visitor's device or to read information already stored there, unless it is needed only to send a communication or strictly necessary for a service the visitor asked for. The European Data Protection Board's guidelines say the rule can apply without any cookie: when JavaScript instructs the browser to send information, when HTTP headers such as the user agent are used for fingerprinting, or when an IP address from the visitor's device is used to track them. Falling under Article 5(3) doesn't automatically mean consent is needed, though. Whether an exemption applies is decided case by case, under each country's law and its regulator's guidance.

France is one example. The CNIL, the French regulator, exempts audience measurement trackers from consent when all of these hold:

  • Visitors are told about the trackers and can object to them.
  • The purpose is limited to audience measurement and A/B testing.
  • The data is not cross-checked with other processing.
  • The tracker is limited to a single site or app publisher.
  • The last byte of the IP address is truncated.
  • Trackers last no more than 13 months.

The CNIL also says most large audience measurement offerings don't qualify, whatever their settings, and the GDPR still applies to any personal data the tool handles, an IP address included. So before you remove the banner, read your tool's data policy for what it stores and reads, check every other script on the site, and talk to your DPO or lawyer.

Example: a bike repair site drops its old analytics

Example

Say you run a site of bike repair guides and replace Google Analytics with a cookieless tool. Page views, referrers and top guides look much as before. Two lost reports fed decisions: the share of returning visitors, which you quoted to sponsors, and the age groups you used to choose between beginner and advanced guides.

You add two questions at the end of every guide: "Did this guide get your bike working?" with Yes and No, then "How often do you read this site?" with three options. After four weeks you have 400 answers, and 220 of them say "Most weeks": 55%, which goes in the sponsor deck as "55% of readers who answered say they read most weeks".

The Yes / No answers do more. Your chain guides score well, but on the gear-tuning guide 31 of 48 answers are No, about 65%. Its scroll depth looked healthy, so the old dashboard would never have flagged it. The free-text answers say the photos show an older gear mechanism than most readers have. You reshoot the photos, and the next month 12 of 40 answers are No: 30%.

You drop the age groups: the per-guide answers already tell you which guides to write next.

Where Asklet fits

Asklet is the asking part. You embed one iframe snippet, it shows a short survey on the page, and results are grouped by website and by page path, such as /guides/*. A Yes / No first question gives each page a "found it useful" figure, and free-text answers show up as anonymous comments next to it.

It uses no cookies, no tracking identifiers and no fingerprinting, so it doesn't need a consent banner, and it stores only the answers, the page path and the time. That also means it can't tell you who came back, and as it doesn't count widget loads, take page views from your analytics for the same dates. The free plan covers one website and up to 100 responses a month.

Your next steps

  1. Write a two-column replacement list

    Left: each report from the lost list that fed a decision in the last six months. Right: its replacement (an event, a landing page, a question on the page) or "drop".

  2. Export a baseline before you switch

    Save the old figures for top pages, referrers and conversions, so you can check that the new tool lands in the same range.

  3. Run both tools for a few weeks

    Compare page views and referrers for the same dates. Don't expect visitor counts to match, because each tool defines a visitor differently.

  4. Set up events and UTM tags before you turn the old tool off

    One event for each funnel step on your list, and UTM parameters on every link in your next newsletter and social posts.

  5. Check the banner question last

    Read what the new tool stores and reads, list the other scripts on the site, check your national rules, and update your cookie policy before you change the banner.

Try these steps on your own site. Asklet adds the questions to every page with one snippet. Compare the plans.

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Common questions

Can cookieless analytics track returning visitors? Not reliably. Plausible and Fathom rotate their visitor hash or signature every 24 hours, so a reader who comes back the next day counts as new. Simple Analytics doesn't recognise a person across visits at all, and Matomo with cookies disabled guesses from the IP address and says the result is inaccurate.

Does cookieless analytics need a cookie banner? It depends on what the tool stores or reads on the visitor's device, and on your country's rules. Article 5(3) of the ePrivacy Directive covers more than cookies, and regulators such as the CNIL set their own conditions for exempting audience measurement.

Can I still measure campaigns without cookies? Yes. Cookieless tools read UTM parameters and referrers, and count events and conversions. Without a cookie, a tool cannot link a later visit back to the campaign that first brought someone in: Matomo, for one, credits a goal to the channel of the visit where it happened. Give important campaigns their own landing page.

Sources

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