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Out-of-the-box Clarity gives you "all sessions, all devices, all sources." That is useless. Segmentation is where Clarity goes from "looks cool" to "actually changes decisions." This is the segment library specialists build.
Who this is forOperators already using Clarity who keep asking 'how do I see just the [mobile shoppers from paid ads who hit checkout]?' If you have ever wished you could slice recordings by 3+ dimensions at once, this tutorial teaches the segment system that makes it routine.
What you'll need
Step 1
Filters combine via AND. Multiple values in a single filter combine via OR. Save filter combinations as named presets ("Segments").
In Recordings or Heatmaps, click "Filters" (top of page). The filter panel opens.
Each filter row applies a constraint. Multiple rows combine via AND — meaning "all conditions must be true."
Within a single filter row (e.g., Device), you can select multiple values — these combine via OR.
Save a useful combination as a preset via "Save filter" → name it. Presets become reusable "Segments" you can apply with one click.
Clarity's filter dimensions: Device, Country, Browser, OS, Page, Smart Event, UTM source/medium/campaign, Session duration, Page count, Referrer, Rage clicks, Dead clicks, Quick back, Excessive scrolling, JavaScript errors.
In 2026, you can also filter by GA4 Audience if the integration is configured (see GA4 integration tutorial).
Step 2
Save 4 segments: Paid Search, Paid Social, Organic Search, Direct. Each surfaces a different user mindset.
Segment 1 — "Paid Search": Filter UTM medium = `cpc` OR `paid-search`. Save.
Segment 2 — "Paid Social": Filter UTM medium = `paid-social` OR `social-paid` OR Referrer contains `facebook.com` AND has UTM. Save.
Segment 3 — "Organic Search": Filter Referrer contains `google.com` OR `bing.com` AND has NO UTM. Save.
Segment 4 — "Direct/Type-in": Filter Referrer = (empty) AND no UTM. Save.
Why these matter: paid-search users have high purchase intent + need fast answers. Paid-social users browse with low intent + need persuasion. Organic searchers are mid-funnel. Direct visitors are returning customers or branded searches.
Watch 5 recordings from each segment monthly. The behavioral differences inform which CRO tests to prioritize per channel.
Step 3
Save 3 segments: High intent, Mid intent, Low intent. Defined by session duration + page count + Smart Events.
Segment 1 — "High Intent": Session duration > 180s AND (Page count >= 5 OR Smart Event = `add_to_cart` OR Smart Event = `pricing_page_visit`). Save.
Segment 2 — "Mid Intent": Session duration 60-180s AND Page count 2-4. Save.
Segment 3 — "Low Intent / Bouncing": Session duration < 30s OR Page count = 1. Save.
Why these matter: high-intent users who do not convert are your highest-leverage CRO target — they wanted to buy and you failed to close. Low-intent bouncers need different fixes (better page-to-search match, faster load times).
Cross with traffic source: "High Intent + Paid Search" is the segment most worth watching weekly. Watch 5 recordings → identify the friction that prevented conversion.
Step 4
Save 4-5 segments matching your funnel: Awareness (any visit), Consideration (pricing/features visit), Decision (cart/signup-form visit), Action (conversion).
For ecommerce: Awareness (any session), Consideration (Smart Event = `product_view`), Decision (Smart Event = `add_to_cart`), Action (Smart Event = `purchase`).
For SaaS: Awareness (any session), Consideration (Smart Event = `pricing_view` OR `features_view`), Decision (Smart Event = `signup_start`), Action (Smart Event = `signup_complete`).
For lead gen: Awareness, Service-page-visit, Form-started, Form-submitted.
Save each as a Segment. The value is in comparing adjacent stages: who is in Consideration but never reaches Decision? That is your biggest leak.
Funnel segments + recordings = the most actionable analysis Clarity supports. Use weekly.
Step 5
Save 4 segments: Rage Click sessions, Dead Click sessions, Error sessions, Quick-Back sessions.
Segment 1 — "Rage Click sessions": Filter "Rage click" = Yes. Save.
Segment 2 — "Dead Click sessions": Filter "Dead click" = Yes. Save.
Segment 3 — "Error sessions": Filter "JavaScript error" = Yes. Save.
Segment 4 — "Quick Back sessions": Filter "Quick back" = Yes (user navigated forward then immediately back). Save.
Each segment surfaces a different friction signal. Quick Back is especially underused — it often signals a page that loaded wrong (broken layout, slow images, wrong content).
Combine with funnel: "Rage Click + Decision stage" is the highest-priority cluster — users actively trying to convert and failing.
Step 6
Save 2 segments: Mobile + Desktop. Every other segment should be cross-applied with one of these.
Segment 1 — "Mobile": Filter Device = Mobile. Save.
Segment 2 — "Desktop": Filter Device = Desktop. Save.
Tablet is usually noise — combine with Mobile or ignore unless tablet is >10% of traffic.
Best practice: apply Mobile or Desktop on top of any other segment before analyzing. Pooled-device data hides device-specific patterns (see heatmap tutorial for why).
Pro tip: in Clarity Settings → Default filters, you can default new sessions/heatmaps to a specific device. If your team analyzes mobile 80% of the time, set Mobile as default to avoid the constant filter-switching.
Step 7
Write down: segment name, filter definition, when to use it, who owns it. Keeps the library usable across team changes.
Create a "Clarity Segments" doc in your team wiki / Notion / Google Docs.
For each segment: name, filter logic (e.g., "UTM medium = cpc"), use case (when do you apply this?), owner (who updates it if business model changes?).
When a new team member joins, they read this doc and have working filters in 10 minutes — without it, they spend a week reinventing the wheel.
Quarterly: review and prune unused segments. If a segment has not been applied in 90 days, archive it. Lean segment library beats sprawling one.
Common mistakes
Building 30 segments and using 3
What goes wrong: You spend 4 hours building elaborate segment libraries, then default back to 'All sessions' because it is faster. The unused segments clutter the UI and make finding the useful ones harder. Time spent: 4 hours; value extracted: $0.
How to avoid: Start with the 4-5 segments most relevant to your funnel. Add new ones only when a specific analysis demands it. Quarterly: prune anything unused in 90 days.
Inconsistent UTM tagging breaks every traffic-source segment
What goes wrong: Your team uses `cpc`, `paid`, and `paid-search` interchangeably across campaigns. Your 'Paid Search' segment captures one-third of paid sessions. Three months of decisions based on incomplete data. Estimated wasted A/B test cost: $3K-8K.
How to avoid: Standardize UTM conventions in a team runbook. Audit UTMs monthly. Common standard: `medium=cpc` for all paid search, `medium=paid-social` for all paid social, `medium=email` for all email, etc.
Applying segments to too small a date range
What goes wrong: You apply 'High Intent + Paid Search + Decision Stage' on 7 days of data. Result: 12 sessions. Patterns at this sample size are random noise. You make a CRO decision on 12 sessions → A/B test does not move conversion → you blame Clarity.
How to avoid: For tight segments (3+ filters), use 30-90 day date range to maintain sample size. If you cannot reach 100 sessions in 90 days with the segment applied, the segment is too narrow to drive decisions.
Not documenting segments — owner leaves and library breaks
What goes wrong: The contractor who built the segment library leaves. New team members do not know what each segment means or which to use when. Within 3 months, the library is abandoned and everyone defaults to 'All sessions' again.
How to avoid: Document every segment in a shared doc with name, filter logic, use case, and owner. Treat the doc as a contract — segment changes get logged.
Filtering by GA4 Audience without testing audience sync
What goes wrong: You build a segment using a GA4 Audience that has not actually synced (audience size too small, or sync delay >48 hours). The segment returns zero sessions. You assume Clarity is broken when the GA4 audience is the problem. Lost: 2-3 hours of debugging the wrong tool.
How to avoid: Before depending on GA4 Audience segments, verify the audience has 30+ users in GA4 AND that the sync timestamp in Clarity is within the last 48 hours.
Recap
Done — what's next
How to set up Clarity session recordings without drowning in noise
Read the next tutorial
Hand it off
The segment library is a one-time build. Using it weekly to inform CRO decisions is an ongoing job. A CRO specialist builds custom segments for your business model in one session, then runs the weekly rhythm of "watch 10 sessions from each priority segment." From $14-16/hr on EverestX.
Get a CRO specialist
10-15 is the sweet spot. Below 5: too coarse to surface patterns. Above 20: you spend more time choosing segments than analyzing data. Prune ruthlessly.
Yes — segments saved at the Project level are visible to all Team members with Member or Admin role. Viewers see segments but cannot edit them. Use this to enforce a single shared library across the team.
Three usual causes: (1) date range too narrow combined with tight filters, (2) one of the filter values is misspelled or no longer matches data (common with renamed Smart Events), (3) a GA4 Audience filter referencing an audience that has not synced. Loosen filters one at a time to isolate the issue.
Yes — push custom tags via the Clarity JavaScript API: `clarity('set', 'plan', 'enterprise')`. These appear as filter values in Clarity. Use sparingly — 5-10 custom tags is plenty; 50+ is unmanageable.
Apply the segment → modify the filters → click 'Save' (the existing segment name will be offered with 'Update'). To save a variant as a new segment, choose 'Save as new' and rename.
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