Automation · Operations and reporting
Ask on WhatsApp where your customers get stuck at checkout, with Fullstory
Ask on WhatsApp what blocks your customers at checkout: an AI agent finds frustration signals in Fullstory and shows you a session.
How do I learn why customers abandon checkout in my store without reviewing recordings one by one?
You write to your Met "what is blocking people at checkout this week?". The Met finds the checkout page in Fullstory, looks for the strongest frustration signals there compared with the previous period and computes how many users the main one affects. Then it brings real sessions where it happened, opens one and takes the screenshot of the moment of the problem to tell you what the customer saw: a button that did not respond, an error, a field that cleared itself. It answers with the signal, its size and what the session shows, and it changes nothing in your account.
What starts it
When someone asks for it
It starts when someone on the team asks the Met on WhatsApp what is blocking checkout. Each query runs on request; this procedure does not leave a scheduled report.
A manual task: someone on the team runs it with a button, or asks the Met for it in chat.
Who runs it
Site analytics Met with Fullstory
This is not a named, seeded Met. It is an internal Met with Fullstory connected: its work ends when it tells you the main frustration signal at checkout, how many users it affects and what a session shows, or when it tells you it did not find the page.
Channels: WhatsApp
What you need connected
- Fullstory Research and analyze
5 steps · 7 tools
The procedure, step by step
Each step shows the tool that runs. They belong to the real connector: if one of them stopped existing, this page would not build.
- 1
Find the checkout page
The Met looks through Fullstory's page definitions for the one that matches checkout, by name or by pattern. If several look alike, it asks you which one is the payment page.
- 2
Find the frustration signals
With the page identified, the Met asks for the strongest frustration signals on that page and compares them with the previous period, to know whether the problem is new or older.
- 3
Measure how many it affects
For the main signal, the Met computes the affected users and their breakdown by page, domain and device. That tells you whether it only happens on mobile or everywhere.
- 4
Bring real sessions
The Met brings sessions where that signal was observed. Session tools return 10 by default and 50 at most, so it works with a sample, not with all of them.
- 5
See what the customer saw
The Met opens one of those sessions, takes the screenshot of the moment of the problem and describes what appears on screen. When done it closes the session, because Fullstory asks for it to be closed to free its resources.
Before you start
What you need ready
The Met solves none of these for you. If one is missing, the automation stops there.
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Fullstory installed on your store with StoryAI enabled
Your site already sends sessions to Fullstory and an admin enabled StoryAI in Settings, StoryAI Features. Without StoryAI the connector connects but shows no tools.
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Fullstory connected in Met
In Met, open Connections → FullStory → Connect and sign in with an account that can see your store's org.
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An internal Met the team writes to
A Met with Fullstory enabled and a WhatsApp line your team writes to. It is an internal query, not a conversation with customers.
The limits
What this automation does NOT solve
Better said here than discovered halfway through the rollout.
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It does not fix checkout. The Met tells you what it sees and how many it affects; fixing the button or the form is work for whoever maintains your store.
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It does not review every session: it works with a sample of up to 50, so the screenshot it describes is an example of the problem, not proof of every case.
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It does not send you the session video. It describes the screenshot; you watch the full replay in Fullstory.
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It does not see stores that do not send data to Fullstory, or other orgs: each connection sees a single org.
FAQ
Questions about this automation
Not for this procedure: it starts from the checkout page. If you already have a purchase funnel, the Met can also look for the frustration signals of people who dropped off it.
Yes. Fullstory can compare signals with the previous period, so the Met tells you whether the problem showed up recently or was already there.
Not in this procedure: it only queries. Opening a session does not change it, and the Met closes it when done.
Each connection sees a single Fullstory org. If your stores live in different orgs, you need one connection for each.
Keep going
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Want this automation running on your own data?
We will show it to you with your accounts connected, not with a canned demo.