Fix my checkout abandonment
Your AI CEO finds the leak, ships the patch, and proves the lift.
You'd think this needs a CRO consultant and a 6-week rebuild — Astra finds the actual leak in 90 minutes from PostHog session data.
The short answer
Astra fixes checkout abandonment by diagnosing the exact failure point, not by guessing at "best practices." She pulls every session that started checkout in the last 30 days from PostHog and Stripe, builds a step-level funnel (landed on /checkout → entered email → entered card → clicked submit → succeeded), and identifies which step has the biggest drop. Then she replays 20 abandoned sessions to spot the actual cause — slow card validation, confusing copy, broken Apple Pay, hidden tax surprise, missing trust badges. She drafts a specific fix (code change, copy tweak, new payment method, or trust signal), opens a PR, and after deploy runs a 7-day A/B comparison to prove lift. Most teams recover 8-22% of abandoned checkouts within 2 weeks. The deliverable is a Lark report with the diagnosis, the PR, and the post-fix conversion delta.
How Astra actually does it
- 1Build the funnel
Pull last 30d sessions from PostHog. Build steps: landed → email → card → submit → success. Compute drop% at each step. Compare to industry benchmarks.
PostHogStripe - 2Replay abandoned sessions
PostHog session replay on 20 random abandoned sessions at the worst-drop step. Look for: errors, hesitation, copy confusion, mobile bugs, payment failures.
PostHog - 3Diagnose root cause
Categorize drop reason: tech failure / UX confusion / pricing surprise / payment method / trust deficit. Pick the highest-impact single fix.
- 4Ship the fix
Open PR with code change, copy tweak, or config update. Include before/after screenshots. Deploy after your approval.
LinearGitHub - 5Measure the lift
7-day A/B with 50/50 split. Report daily conversion deltas in Lark. If lift > 5% → keep. If null or negative → revert and try the next-highest hypothesis.
What it looks like in chat
A Lark report with funnel diagnosis, session replays, the deployed PR, and a 7-day A/B comparison proving (or disproving) the lift in checkout completion rate.
One-shot fix per leak; re-runs whenever the funnel shifts > 5%.
Ask Astra this right now
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Try this with AstraFrequently asked questions
What if the fix doesn't work?
After 7 days of A/B with no lift (or worse, a drop), Astra reverts and moves to the next-ranked hypothesis. The funnel diagnosis usually surfaces 2-3 candidate causes; she works them in order until one lands. Average successful fix: 2nd attempt.
What if I don't have PostHog session replay?
Astra works with whatever observability you have. With Stripe alone she can pinpoint card-step failures (declined cards, 3DS drops). With Datadog RUM or Mixpanel funnels she can do the funnel breakdown. Session replay just makes the diagnosis 10× faster.
Will the A/B test slow my decision?
Astra shows you live conversion delta from day 1. If the lift is overwhelming (>30%) by day 3 she recommends ending the test early. If it's null or marginal she'll suggest extending to 14 days for statistical confidence. You always make the call.
Can Astra ship the code fix herself?
She opens the PR with full code changes, screenshots, and test plan. Merge and deploy stay yours unless you've granted GitHub merge permissions. Once you merge, the deploy pipeline takes over and Astra resumes monitoring.
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