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Understand how a feature is being used

Ask Fullstory MCP how your users are engaging with any part of your product and it will pull the data, surface behavioral patterns, and tell you what's working and what isn't — with session evidence where it matters.

Example questions​

How is our wishlist feature being used in the last 30 days? Adoption, repeat usage, and impact on conversion.
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Of users who hit /signup in the last 30 days, what percent completed account creation? Break it down by traffic source.
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Compare first-time visitors vs. returning users on our pricing page. Do they convert differently?
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Daily trend of new account signups for the last 60 days. Flag any meaningful dips.
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What you get back​

A structured report with the key numbers, behavioral patterns, friction points, and what's working. For example:

AI Response

Wishlist feature usage (last 30 days)

By the numbers

  • 3,200 unique users added at least one item
  • 41% returned within 7 days and added more
  • 18% of wishlist creators later completed a purchase (vs. 9% baseline conversion for non-wishlist users)

How people use it

  • 62% add a single item, never return
  • 24% build a list of 3 or more items across multiple sessions
  • 14% use it as a comparison tool: add, remove, then buy outside it

Friction

  • Removing an item requires 3 clicks. 11% of users attempt removal twice before succeeding.
  • Wishlist link is hidden in the account menu on mobile. Mobile return-to-wishlist rate is 19% lower than desktop.

What's working

  • The "added to wishlist" toast is reliably effective. Click-through to the wishlist via the toast is 34%.
  • Users who add 3 or more items convert at 2.4x the baseline rate.

Follow-up questions​

Drill into that 3-click removal flow. Show me what users do when they get stuck.
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Compare the conversion lift on mobile vs. desktop for wishlist users.
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What's the average time between adding an item and purchasing it?
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Example follow-up​

Fullstory MCP
Drill into that 3-click removal flow. Show me what users do when they get stuck.
Fullstory MCP
AI Response

Reviewed 8 sessions where users attempted to remove a wishlist item.

Pattern A (5 of 8 sessions): heart icon confusion

  • Users click the heart icon expecting it to remove the item
  • The heart icon is decorative; the actual remove control is a small "x" in the upper corner
  • Users click the heart 2 to 4 times, scan the page, then find the "x"

Pattern B (3 of 8 sessions): confirm-dialog hesitation

  • Users find the "x" on the first try
  • A confirm dialog appears asking "Remove this item?"
  • Users hesitate 6 to 14 seconds before confirming, suggesting the dialog is doing work the button placement could do better

Suggested investigation: A/B test removing the confirm dialog and making the heart icon itself the toggle.

Behind the scenes​

The MCP routes the chain above through: build_segment, build_metric, compute_metric, update_metric, and get_sessions.