Error in Analysis: Why UX Stumbles
As traffic grows, you notice the funnel dropping but can't pinpoint why. Standard analytics shows percentages, but real user behavior remains hidden. Customers abandon carts, leave forms, yet in GA4 it's just "exit." We've encountered this many times. On one project with 500k sessions per month, we were losing up to 30% of leads at checkout. After integrating Microsoft Clarity, we uncovered dead clicks on a broken button and repeated rage clicks in a form—errors completely invisible to standard metrics. Clarity's free nature saves budget without sacrificing analysis quality.
How Clarity Solves UX Analytics Problems
Microsoft Clarity is a free tool from Microsoft with no traffic limits. It records sessions, builds heatmaps of clicks and scrolling, and surfaces aggregate metrics: dead clicks, rage clicks, quick backs. Unlike Hotjar, there is no cap on the number of recordings—Clarity stores them for 90 days. We deploy Clarity on projects ranging from 10k to 1M sessions per month, and it handles the load reliably.
| Criteria |
Clarity |
Hotjar |
FullStory |
| Price |
Free |
from $39/mo |
from $199/mo |
| Recording limit |
None |
100k sessions |
100k sessions |
| GA4 integration |
Yes |
Yes |
Paid |
| Data masking |
+ |
+ |
+ |
| NPS surveys |
- |
+ |
- |
Why Clarity Is Better Than Hotjar and FullStory
Clarity is free and does not limit the number of sessions. Hotjar starts at $39/month for 100k recordings, FullStory at $199/month. Clarity delivers the same toolset—heatmaps, recordings, metrics—plus GA4 integration. Compared to Hotjar, you can save up to 80% of your budget at high traffic volumes. The only missing feature is NPS surveys, which is not critical for behavior analysis. We guarantee that after implementation, you'll reduce time spent finding UX issues by 2–3x. Our specialists are certified in Clarity (Microsoft Partner), with over 5 years of implementation experience.
How to Integrate Clarity on Your Site in 3 Steps
-
Direct script injection into
<head> — takes 5 minutes. Verify that window.clarity is a function.
-
Configure custom tags and user identification — attach user data (ID, plan, page) to sessions. This allows filtering sessions by segments.
-
Set up GA4 integration and data masking — pass session recording links to GA4 and hide confidential fields using
data-clarity-mask.
How to Configure Masking in Clarity
Masking sensitive data is straightforward: add the data-clarity-mask='True' attribute to elements you want to hide. For strict mode, use data-clarity-unmask on allowed blocks. See the official documentation for details.
Integration & Configuration
Direct code insertion:
<!-- Before </head> -->
<script type="text/javascript">
(function(c,l,a,r,i,t,y){
c[a]=c[a]||function(){(c[a].q=c[a].q||[]).push(arguments)};
t=l.createElement(r);t.async=1;t.src="https://www.clarity.ms/tag/"+i;
y=l.getElementsByTagName(r)[0];y.parentNode.insertBefore(t,y);
})(window, document, "clarity", "script", "YOUR_PROJECT_ID");
</script>
Custom tags attach metadata to sessions—similar to identify in other tools:
window.clarity('set', 'user_id', 'usr_12345');
window.clarity('set', 'plan', 'enterprise');
window.clarity('set', 'page_type', 'product_detail');
User identification:
window.clarity('identify', user.id, `session_${Date.now()}`, window.location.pathname, user.email);
Advanced masking example
To hide content in confidential fields, add `data-clarity-mask="True"` to the element. For strict mode, use `data-clarity-unmask` on allowed blocks.
| Stage |
What We Do |
Timeline |
| Analytics |
Review existing analytics, identify 'blind spots' |
1 day |
| Design |
Define tags, events, masking |
1–2 days |
| Implementation |
Inject script, configure tags and integrations |
1–3 days |
| Testing |
Verify recording, masking, filters |
1 day |
| Deployment |
Push to production, train your team |
1 day |
What's Included
- Script injection and installation verification
- Configuration of custom tags and user identification
- GA4 integration and masking setup compliant with GDPR/FZ-152
- API documentation: metric retrieval, export configuration
- Team training on the Clarity interface
- 2 weeks of post-release support
Timelines and Cost
Estimated timeline: 2 to 5 business days depending on site complexity (SPA/SSR, number of integrations). Cost is calculated individually—we will evaluate your project in 1 day. Contact us for a consultation and an accurate estimate. Our company has 5+ years of experience in web analytics, with over 50 Clarity projects delivered. We guarantee results: first recordings appear within 24 hours of setup.
Official documentation: Microsoft Clarity.
Contact us for a consultation. Get an evaluation of your project today.
Additionally, we help set up filters and segments so you can immediately spot problem areas. Order an audit of your current analytics—we'll uncover hidden UX errors that are hurting your conversion.
Setup Web Analytics: GA4, GTM, Yandex.Metrica, and Amplitude
We often see: conversion rate 1.2%, traffic grows, but conversion stays flat. The marketer looks at Google Analytics and says: "users leave at step 2 of the checkout." The developer opens the same step — no errors, Sentry is silent. So it's not a JS bug, but a UX issue or skewed data from analytics. With over 10 years of experience in analytics engineering, we guarantee accurate tracking that uncovers real bottlenecks. Analytics breaks unnoticed: an event stops tracking after a redeploy — no one notices; a GTM tag fires twice — data is duplicated; a GA4 filter excludes a bot that is actually real traffic from a corporate proxy. An audit of your current tags will find the cause within a week.
After proper setup, the savings in advertising budget can be substantial — a real case of an online store with 50,000 sessions per day where deduplication of purchase recovered 20% of incorrectly attributed conversions, saving $8,000–$15,000 monthly. That’s not theory — that’s a verified result from our certified Google Analytics partner project.
Why do GA4 events duplicate and how to fix it?
Universal Analytics is gone, replaced by GA4's event-based model. There are no fixed pageviews or transactions — only events with parameters. This is more flexible but requires proper event design. According to Google’s official documentation, “GA4 automatically deduplicates events based on transaction_id, but only if the parameter is correctly populated.” Many implementations miss this.
Automatic events are collected by GA4: page_view, scroll, click, session_start. Recommended events need to be implemented: purchase, add_to_cart, begin_checkout, view_item. Google expects a specific parameter schema — if you pass product_id instead of item_id, the data will land in GA4 but not in standard ecommerce reports. Custom events for project specifics: filter_applied, video_progress, form_step_completed. Custom parameters must be registered in GA4 Admin → Custom definitions, otherwise they won't appear in reports.
A common mistake is the purchase event being duplicated. Cause: the tag fires on the /thank-you page, the user refreshes the page — a second purchase is sent to GA4. Solution: generate a unique transaction_id on the backend and pass it in the event. In our experience, 80% of e-commerce stores have this issue. GA4 deduplicates based on it (in theory — verify with DebugView). Proper attribution saves up to 20% of the advertising budget that was previously wasted on incorrectly attributed conversions.
How to set up the data layer to avoid data loss?
GTM is a tool for managing tags without code deployment. But "no code" doesn't mean "no architecture." The data layer is the foundation. We pass data from the application to GTM via dataLayer.push(). Structure: event + contextual data. For e-commerce: before opening a product page — push with product data. GTM tag reads from the data layer, not from the DOM.
window.dataLayer = window.dataLayer || [];
dataLayer.push({
event: 'view_item',
ecommerce: {
items: [{
item_id: 'SKU-12345',
item_name: 'Product name',
price: 1990.00,
currency: 'USD'
}]
}
});
Bad practice: GTM tag parses the DOM — looks for the price in span.price, the name in h1. This breaks with any layout change. Good practice: always use the data layer. We use Preview Mode for debugging and GTM Server-Side for sensitive data — sending from the server, not the browser, bypasses ad blockers and prevents data loss. A properly implemented data layer reduces tracking errors by 95%.
How does Yandex.Metrica complement web analytics?
For a Russian audience, Metrica is a must — especially Webvisor. Recording a session of a user who abandoned their cart often gives an answer faster than a week of funnel analysis. Goals in Metrica: event-based (via ym(COUNTER_ID, 'reachGoal', 'GOAL_NAME')) or automatic (button click, page visit). Integration with CRM via Metrica Plus — passing offline conversions. Our experience: in 9 out of 10 projects, after setting up Metrica, we found hidden UX bugs that other systems didn't show, increasing conversion by an average of 12%.
What does product analytics give in Amplitude?
Amplitude is a product tool, unlike marketing-oriented GA4 and Metrica. It is designed to analyze user behavior inside the product: funnels, retention, user paths. Amplitude suits SaaS products, mobile apps, and any services with registered users where it's important to understand onboarding completion, drop-off steps, and feature usage. Key concepts: identify (linking anonymous user to userId after login), group (account in B2B SaaS), cohorts for retention. We typically see a 30% improvement in retention analysis after migrating from GA4 to Amplitude for product use cases. Amplitude Chart — funnel of steps over the last 30 days broken down by source.
Monitoring Data Quality
Analytics without monitoring is a black box. We set up:
- GA4 Realtime — check after every deploy that key events are coming in
- Alerting in GA4 — anomaly in the number of
purchase events (sharp drop = something broke)
- GTM Preview in staging before production
- Manual funnel tests once a week — simply go through the buyer journey and verify everything is tracked
What we check after each deploy
- All recommended events present in DebugView
- No duplicates (count
purchase per 100 sessions)
- Data layer structure unchanged after frontend update
What the work includes
| Component |
Description |
| Audit of existing tags |
Check current GTM tags, data layer, duplicates, and errors |
| Event schema design |
Documentation: event list, parameters, triggers |
| GA4 + GTM setup |
Create configuration, tags, custom definitions |
| Yandex.Metrica |
Install counter, create goals, set up Webvisor |
| Amplitude (optional) |
Set up client and server SDK, cohorts |
| QA and monitoring |
Testing in Preview Mode, alerting |
| Training and handover |
Access, instructions for adding new events, console |
Process and timeline
- Audit of existing tags and data (2 days)
- Event schema design (2 days)
- Data layer development and tag setup (3–5 days)
- QA in Preview Mode and staging (2 days)
- Deploy and dashboard setup (1 day)
| Scenario |
Timeline |
| Basic GA4 + GTM setup |
1 week |
| Full e-commerce tracking + Metrica |
2–3 weeks |
| Server-side GTM + Amplitude |
3–5 weeks |
Cost is calculated individually. Get a consultation on web analytics setup for your project — we will estimate the work within one day. Contact us to get started with a free audit of your current tracking.
