Find Repeated Conversion Issues With Monolytics Assistant
On this page
Use Monolytics natural-language Record Search when you need relevant sessions for a conversion question. Describe the flow and observed outcome, inspect the returned evidence, and compare successful sessions before proposing a change.
Use Record Campaigns when you want to collect sessions for an already defined flow. Missing activity or completion signals remain a limit on either investigation.
Why repeated patterns matter more than isolated replays
One replay can make almost any hypothesis look believable. Repeated patterns are much harder to ignore. If several high-intent users hesitate in the same place, miss the same cue, or abandon after the same unresolved question, the team has a better reason to prioritize the fix.
That is why natural-language Record Search is useful after the basic funnel signal is already visible. The assistant helps you move from “we know users are dropping” to “we know which friction pattern keeps causing the drop.”
When natural-language Record Search is the better tool
- You need to compare many failed sessions, not inspect one by one at random.
- The conversion problem appears across a larger segment or repeated query set.
- The team wants to isolate behavioral patterns before changing the page or flow.
- You need a stronger bridge from qualitative replay evidence to prioritization.
A practical natural-language Record Search workflow
1. Define the failed segment clearly
Start with a precise business question such as “users who reached pricing but did not start a trial” or “high-intent visitors who opened the demo flow but never submitted.” Natural-language Record Search works better when the segment is grounded in a real outcome gap.
2. Describe the session pattern you want to find
Use natural-language prompts that focus on the friction behavior, not the hoped-for answer. Ask for hesitation, repeated comparison, form avoidance, backtracking, or other patterns that would explain the failure.
If the question is still vague, use product questions to ask your session replay assistant to reshape it around a journey, failed outcome, and observable behavior.
3. Review the returned clusters, not just one session
The point is not to find a single dramatic replay. The point is to see whether the same friction pattern appears often enough to justify action.
4. Compare failed patterns with successful behavior
The most useful contrast is often between one failure cluster and a small set of successful sessions from the same journey. That difference helps the team see what information or interaction the failed users did not get.
5. Convert the pattern into a fix hypothesis
Every pattern should end as a scoped hypothesis with an owner and a testable change. Otherwise the analysis stays descriptive and never improves the page.
Example: high-intent users who did not convert
A common use case is a page where visitors show real purchase or signup intent but still fail to complete the action. Natural-language Record Search can isolate the repeated differences between those failed sessions and the successful ones. In practice, the answer is often not “the CTA color is wrong.” It is more often missing information, unearned trust, unclear next-step cost, or hidden interaction friction.
What a useful output should include
- The failed segment that was reviewed.
- The recurring friction pattern in plain language.
- A few representative sessions that support the pattern.
- The likely cause hypothesis at page, form, or workflow level.
- The smallest testable change the team should run next.
When the output is only a short summary, treat it as triage. Use session replay summaries vs evidence review and the session replay evidence confidence matrix before turning the pattern into a product decision.
How this fits with Record Campaigns
Use Record Campaigns when the path is already sharply defined and you want targeted capture. Use natural-language Record Search when the team needs grouped evidence across many sessions and wants to compare repeated failure modes instead of reviewing isolated replays.
Continue in Monolytics Assistant
If the failed segment is already clear, move directly into Monolytics Assistant to turn the behavioral question into a session search and review the returned evidence set.
Choose your next step
- Define the question. Use the product-question guide to name the journey, outcome, and behavior you want to review.
- Choose search or an answer. Record Search finds sessions for manual review. For an answer to a defined site question, use Monolytics Assistant, then check its scope and sources.
- Review the recordings. Follow the session review workflow to compare relevant sessions and record what you observe.
- Check what the evidence supports. Use the evidence confidence matrix before choosing a fix.