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so things don't slip past you.

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Squash· just now

Promo discounts applied client-side but never persisted to payment gateway

34 customers charged full price despite promo codes showing as applied in the UI. The discount is registered client-side but the order payload sent to the payment service omits the discount object, resulting in ₹3.8L in overcharges across 4 enterprise accounts over 72 hours.

₹3.8L overcharged34 tickets · 28 users · 72h
  1. Ticket clustering08:12 IST

    Scanned 142 new tickets from the last 72h. Identified 34 mentioning promo/coupon failures at checkout. All describe the same pattern.

    Zendesk
  2. Verified discount not reaching payment08:18 IST

    Cross-referenced 12 user IDs with Mixpanel events. All fired checkout.promo.applied but BigQuery order totals match pre-discount price.

    MixpanelBigQuery
  3. Promo codes themselves are valid08:22 IST

    Queried the promotions table. SUMMER25, FLAT15, WELCOME10 are all active, within validity dates. Codes aren't the problem.

    BigQuery
  4. Reviewed 6 session replays08:28 IST

    In all 6 sessions, cart summary updates with discount but final confirmation reverts to original total.

    PostHog
Sources
94% confidence

Suggested action

Create Linear issue · escalate to Payments

Create

Plugs into your existing product stack

Mixpanel
PostHog
Amplitude
Hotjar
Zendesk
Intercom
Linear
Jira
BigQuery
Slack

The Problem

The problem

PMs spend 30-40% of their time on manual data work.

Five tools open. Cross-referencing funnels. Watching recordings. Pulling reports.

Conversion dropped on Tuesday. Found on Friday. Fix ships next sprint.

10,000 sessions recorded. 50 reviewed. Your team acts on less than 5% of your data.

The data was always there. Nobody had time to find it.

1
Mixpanel72h ago

Checkout funnel ↓19%

Drop at promo-apply step

142
Sentry72h ago

TypeError spike: 142

discount.amount undefined

12
Zendesksince Tue

12 tickets, promo issue

Users charged full price

47
Hotjar3d

Rage clicks at checkout

47 sessions retrying promo

Squash solves the attention problem, not the data problem.

How it works

Your product stack, monitored. Issues resolved before they escalate.

Squash continuously watches your analytics, session replays, support tickets and error logs. When it spots something, it investigates across every tool and hands your team a fix, not just an alert.

Squash · Findings
Needs Review · 6

Ask Squash

And when you do have a question, ask the teammate that's already read everything.

Squash is wired into your analytics, sessions, tickets, calls, and backlog. Ask a funnel question, draft a ticket, summarise complaints. It answers like someone who's already read everything.

  • Ask a data question. Squash writes the SQL, runs it, and visualises the answer.
  • Draft a Jira / Linear ticket grounded in real session and ticket evidence.
  • Summarise what customers are complaining about most this month, with sources.
squash.ai / checkout-analysis
Why is checkout conversion down on Android this week? Can you figure out what's going on and draft a Jira for the fix?
Analysis complete · 4 tools used
Querying BigQuery · checkout_events
Clustering 412 Zendesk tickets
Scanning 38 session recordings for rage clicks
Drafting Jira ticket SQ-519

Android checkout conversion dropped to 2.1% (↓0.9 pts) this week. Root cause: payment-step crash on Android 14 after the 4.2.1 release. 38% of affected users rage-clicked the Pay button 3+ times before exiting.

Android CVR

2.1%

−0.9 pts

Rage clicks

38%

+24 pts

Tickets

412

3× normal

Daily conversion · last 14 days

BigQuery
Jira · Draft
Ready

[P1] Android 14 payment-step crash after 4.2.1 release

SQ-519 · Squash Web · Linked: 412 tickets · 38 sessions

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