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AI agent for chief digital officers

Customer Journey Friction Agent

Find the biggest friction points in key journeys and confirm fixes with tests

AnalysisDecisionsIT and developmentManagementExecutives and strategy
See how it worksGet access
Customer Journey Friction Agent: what goes in, what the agent does and what you get

What it does

Online journeys like sign-up, checkout or claims lose customers at specific steps, and fixes are often guessed. Each week this agent reads funnel analytics, finds steps where drop-off rose beyond normal variation, and first checks that tracking still works so a broken tag is not mistaken for customer behavior. It then pulls session notes, error logs and customer feedback for the affected step. It forms a likely cause and proposes one small test, such as removing a field or changing a service. After a test runs, it checks whether the result is statistically clear. If not, it loops back and proposes a different fix based on the next most likely cause. You approve which tests go live and which winning changes become permanent. Edge case: a drop caused by a broken tracking tag is reported as a data problem, not a customer problem.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedYes, continueNoNo 1 STARTS WHEN Weekly funnel review 2 USES A TOOL Pull funnel data for each key journey 3 DOES Find steps with drop-off outside the normal range 4 CHECKS THE RESULT Is tracking working correctly on that step? If not: report a tracking issue to the analytics teamand recheck after the fix. Back to step 2. 5 USES A TOOL Read error logs and feedback for the step 6 DOES Propose a cause and a small test 7 YOU APPROVE CDO approves the test going live 8 CHECKS THE RESULT Did the test give a clear improvement? If not: record the result and propose the next mostlikely fix. Back to step 6. 9 RESULT Confirmed fix recommended for full rollout
Read the steps as a list
  1. Weekly funnel review
  2. Pull funnel data for each key journey
  3. Find steps with drop-off outside the normal range
  4. Is tracking working correctly on that step?If not: report a tracking issue to the analytics team and recheck after the fix. Back to step 2.
  5. Read error logs and feedback for the step
  6. Propose a cause and a small test
  7. CDO approves the test going liveThe agent waits here for your OK.
  8. Did the test give a clear improvement?If not: record the result and propose the next most likely fix. Back to step 6.
  9. Confirmed fix recommended for full rollout

How it decides

A step is investigated when its drop-off moves outside the normal weekly range. A fix is confirmed only when the test reaches the set confidence level.

  • Investigate when drop-off exceeds the normal range by two standard deviations
  • Prefer the smallest change that tests the cause
  • Stop a test early if conversion falls sharply

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Journeys to monitor
  • Confidence level for a clear result (default 95%)
  • Maximum tests per month
  • Who approves tests

What keeps you in control

It always asks you first

  • Launching any test to customers
  • Rolling out a fix

Hard limits

  • Never launches tests or changes the live site without approval
  • Uses aggregated data only, no personal details in reports

It stops when

  • Done: fix confirmed or three tests tried
  • Stop: analytics data unavailable

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensAt Bluefin Outdoor, checkout step three fell from 72% to 61% completion in the week of March 4. Tracking was fine. Error logs showed address lookup timeouts on mobile. The first test, a manual address option, showed no clear lift after two weeks, so the check failed. The agent proposed a faster lookup service instead. Completion rose to 70%, and the digital lead approved the permanent change.

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