Marketing · Analyze & Recommend
Know WHY revenue changed, not only that it did
Each morning, Shopify order volume and inventory levels are compared against Stripe payment logs. Statistical deviations trigger a root-cause investigation, and a report with severity ratings and specific fixes lands in Slack before standup.
Works acrossShopifyStripeSlack
What you get.
Daily cross-referencing of Shopify and Stripe data surfaces revenue anomalies, traces root causes, and delivers investigation reports with recommended actions before your team starts their day.
The dashboard is red but nobody knows why
Revenue dropped 18% yesterday on your Shopify dashboard. Is it a payment processing issue? A stockout on your best-selling SKU? A pricing page that broke after the last deploy? A refund cluster from a bad batch? You don't know, and finding out means opening Shopify admin, cross-referencing order data with Stripe's payment logs, checking inventory levels, and reviewing product page analytics, all in separate tabs with different time formats.
The investigation takes 2-3 hours across two platforms, and the answer is usually something painfully obvious in hindsight: a popular variant went out of stock, or Stripe's fraud filter started declining legitimate cards after a rule change. By the time you figure it out, you've lost a full day of sales and your team has been running on anxiety instead of answers.
What changes.
- 01Time to diagnoseBefore · 2-3 hours of cross-referencing Shopify and StripeWith Doe · Root cause report delivered by 7 AM with specific actions
- 02Root cause accuracyBefore · Guesswork until someone checks every possible causeWith Doe · Data-backed diagnosis correlating inventory, payments, and conversion data
- 03Stockout preventionBefore · Noticed after sales already droppedWith Doe · Flagged when inventory hits critical levels, before revenue impact compounds
- 04Payment issue detectionBefore · Discovered days later in Stripe reportsWith Doe · Failed payment patterns identified within 24 hours
How Doe investigates e-commerce anomalies
- 01Pulls order volume, revenue by product, and inventory levels for the past 24 hoursShopifySales, stock counts, and conversion rates collected across all active listings
- 02Pulls charges, failures, and disputes for the same periodStripe14 failed payments, 3 disputed charges, and a 40% spike in declines on one payment method
- 03Flags anomalies by comparing against historical baselinesDoeThree anomalies flagged: a 23% revenue dip in one product category, a refund cluster on a specific SKU, and a conversion rate drop on mobile checkout
- 04Investigates each anomaly and traces the root causeDoeRevenue dip traced to a stockout on the #2 best-seller at 2 PM yesterday. Refund cluster linked to a sizing issue. Mobile drop correlated with a Stripe 3D Secure rule change.
- 05Delivers the investigation report with recommended fixes to your teamSlackRoot causes, severity ratings, and specific actions posted: restock SKU-4421, add sizing guidance to the product page, review Stripe 3DS settings
- 06RecurringEvery day at 7:00 AMRuns every morning at 7 AM. When everything looks normal, you hear nothing. When something is off, you get a full investigation report with root causes and recommended fixes before your team starts their day. Report delivered to Slack, only when anomalies are detected.
Up and running in under ten minutes.
- 01Connect your toolsOne-click OAuth for each integration. No API keys, no engineering.
- 02Describe what you need“Monitor our Shopify store daily for revenue, conversion rate, and refund volume. If revenue drops below $5K, refunds spike above 3%, or conversion dips under 1.5%, investigate and send a root-cause summary to #ecommerce.”
- 03It runs on scheduleMonitors daily and delivers an investigation report to your channel only when anomalies are detected.
Before you delegate.
- 01What counts as an anomaly?Doe establishes baselines from your historical data and flags statistically significant deviations: revenue drops beyond normal variance, refund rates above your average, payment failure spikes, sudden conversion rate changes, and inventory stockouts on high-volume products. You can adjust sensitivity thresholds during setup.
- 02Does it work with multiple Shopify stores?Yes. Doe can connect to multiple Shopify stores and cross-reference them. Each store gets its own anomaly baselines, and the report clearly separates findings by store so you know exactly where the issue is.
- 03Can it detect payment fraud?Doe flags unusual payment patterns (chargeback spikes, geographic mismatches, velocity anomalies) that may indicate fraud. It is a pattern-recognition layer on top of Stripe's built-in fraud detection, not a replacement. Use both together.
- 04Does it recommend specific actions or just report problems?Every anomaly comes with a recommended action. A stockout gets a restock recommendation with the affected SKU. A payment failure pattern gets a suggestion to review Stripe settings. A refund cluster gets a link to the product page and a note to investigate quality or listing issues.
- 05What about WooCommerce or other e-commerce platforms?Doe currently integrates most deeply with Shopify and Stripe. WooCommerce support is on the roadmap. In the meantime, if your WooCommerce store uses Stripe for payments, Doe can still analyze the payment side of the equation.