Key Metrics To Track For Checkout Success

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Summary

Tracking the right key metrics for checkout success is crucial for understanding customer behavior and improving conversions. These metrics go beyond simple click data, focusing on actions that signal genuine purchase intent and identifying specific points in the buyer's journey where drop-offs occur.

  • Monitor high-friction actions: Pay attention to behaviors like initiating checkout, entering payment information, or revisiting product pages, as they indicate stronger purchase intent compared to simply adding items to the cart.
  • Analyze conversion flow: Dig into the sequence of actions customers take, such as moving from cart to checkout or engaging with shipping and payment options, to uncover potential pain points.
  • Focus on post-click insights: Examine metrics like time spent on return policies, size charts, or product comparisons, as these indicate customers are weighing decisions and nearing a purchase.
Summarized by AI based on LinkedIn member posts
  • View profile for Sarah Levinger

    I help DTC brands generate better ROI with psychology-based creative. 🧠 Talks about: consumer psychology, behavior science, paid ads. Founder @ Tether Insights

    12,390 followers

    🛒 You can’t track purchase intent by tracking ATCs. 𝟭. “𝗔𝗧𝗖” 𝗷𝘂𝘀𝘁 𝗺𝗲𝗮𝗻𝘀 “𝘀𝗮𝘃𝗲 𝗳𝗼𝗿 𝗹𝗮𝘁𝗲𝗿”. It’s a placeholder, not a promise. 𝟮. 𝗣𝗲𝗼𝗽𝗹𝗲 𝘂𝘀𝗲 𝘁𝗵𝗲 𝗰𝗮𝗿𝘁 𝗹𝗶𝗸𝗲 𝗣𝗶𝗻𝘁𝗲𝗿𝗲𝘀𝘁. It’s a tool for collecting, not committing. 𝟯. 𝗧𝗵𝗲 𝗰𝗮𝗿𝘁 𝗵𝗲𝗹𝗽𝘀 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗲, 𝗻𝗼𝘁 𝗽𝗿𝗶𝗼𝗿𝗶𝘁𝗶𝘇𝗲. It helps them compare…not decide. 𝟰. 𝗡𝗼 𝗳𝗿𝗶𝗰𝘁𝗶𝗼𝗻 = 𝗻𝗼 𝗰𝗼𝗺𝗺𝗶𝘁𝗺𝗲𝗻𝘁. Clicking isn’t buying. It costs nothing to put something in an online cart. 𝟱. 𝗔𝗧𝗖𝘀 𝗺𝗲𝗮𝘀𝘂𝗿𝗲 𝗰𝘂𝗿𝗶𝗼𝘀𝗶𝘁𝘆 𝗼𝗻𝗹𝘆. Interest? Yes. Intent? Not even close. If you really want to track intent, do this instead: ✅ 1. Track high-friction actions Not all clicks are equal. Look for: • Initiate Checkout • Payment Info Entered • Return Visitor → PDP → Checkout • Product added after reading reviews These behaviors show someone is moving past curiosity into commitment. ✅ 2. Analyze sequence, not single actions One ATC means nothing. But: 𝘈𝘛𝘊 → 𝘝𝘪𝘦𝘸 𝘴𝘩𝘪𝘱𝘱𝘪𝘯𝘨 𝘱𝘰𝘭𝘪𝘤𝘺 → 𝘈𝘥𝘥 𝘢𝘥𝘥𝘳𝘦𝘴𝘴? Now we’re talkin’ intent. Watch the flow, not the isolated click. ✅ 3. Measure time spent on key friction points If someone lingers on: • Product comparisons • Return policy pages • Size charts or FAQs They’re mentally preparing to convert. They’re not just browsing at that point, they’re weighing the trade-offs. ✅ 4. Look for repeat product interactions If someone revisits the same PDP 2–3 times in a week, that’s real consideration. Bonus points if they come back from an email or ad reminder. ✅ 5. Use survey overlays or post-exit polls Ask simple, direct questions like: “Are you planning to buy today?” “What’s stopping you from checking out?” Self-reported “logic” + behavioral data = gold. 𝘛𝘓𝘋𝘙: 𝘈𝘛𝘊 𝘪𝘴 𝘪𝘯𝘵𝘦𝘳𝘦𝘴𝘵-𝘭𝘦𝘷𝘦𝘭 𝘣𝘦𝘩𝘢𝘷𝘪𝘰𝘳 𝘰𝘯𝘭𝘺. 𝘐𝘵 𝘸𝘰𝘯’𝘵 𝘵𝘦𝘭𝘭 𝘺𝘰𝘶 𝘪𝘧 𝘺𝘰𝘶𝘳 𝘤𝘶𝘴𝘵𝘰𝘮𝘦𝘳𝘴 𝘢𝘳𝘦 𝘵𝘳𝘶𝘭𝘺 𝘳𝘦𝘢𝘥𝘺 𝘵𝘰 𝘣𝘶𝘺. 𝘛𝘰 𝘵𝘳𝘶𝘭𝘺 𝘵𝘳𝘢𝘤𝘬 𝘪𝘯𝘵𝘦𝘯𝘵, 𝘮𝘰𝘯𝘪𝘵𝘰𝘳 𝘤𝘩𝘦𝘤𝘬𝘰𝘶𝘵 𝘮𝘰𝘮𝘦𝘯𝘵𝘶𝘮.

  • View profile for Dmitry Nekrasov

    Co-founder @ jetmetrics.io | Like Google Maps, but for Shopify metrics

    41,132 followers

    What CR doesn’t tell you But 7 components do You fixed the Conversion Rate, but nothing changed. Because CR is just the tip of the iceberg. It doesn’t explain the customers' journey. And definitely not the drop-offs. With Nick Valiotti, PhD we mapped 7 elements of conversion that reveal where your funnel actually leaks. That's what's under the water: 1/ 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗜𝗻𝘁𝗲𝗿𝗲𝘀𝘁 𝗥𝗮𝘁𝗲 = Product page views / Sessions Shows if users are landing on high-interest products or generic pages. 2/ 𝗖𝗮𝗿𝘁-𝘁𝗼-𝗩𝗶𝗲𝘄 𝗥𝗮𝘁𝗲 = Add to carts / Product views Reveals product appeal + pricing clarity. 3/ 𝗖𝗮𝗿𝘁 𝗢𝗽𝗲𝗻 → 𝗖𝗵𝗲𝗰𝗸𝗼𝘂𝘁 𝗦𝘁𝗮𝗿𝘁 = Checkout starts / Carts opened Do people commit after opening the cart? 4/ 𝗦𝗵𝗶𝗽𝗽𝗶𝗻𝗴 𝗠𝗲𝘁𝗵𝗼𝗱 → 𝗣𝘂𝗿𝗰𝗵𝗮𝘀𝗲 = Purchases / Shipping method selected Highlights issues with delivery cost, speed, or trust. 5/ 𝗣𝗮𝘆𝗺𝗲𝗻𝘁 𝗠𝗲𝘁𝗵𝗼𝗱 → 𝗣𝘂𝗿𝗰𝗵𝗮𝘀𝗲 = Purchases / Payment method selected Do people quit after choosing how to pay? 6/ 𝗣𝗿𝗼𝗺𝗼 𝗖𝗼𝗱𝗲 → 𝗣𝘂𝗿𝗰𝗵𝗮𝘀𝗲 = Purchases / Promo code applied Reveals whether discounts drive actual commitment. 7/ 𝗣𝘂𝗿𝗰𝗵𝗮𝘀𝗲-𝘁𝗼-𝗩𝗶𝗲𝘄 𝗥𝗮𝘁𝗲 = Purchases / Product views The real conversion beyond CR. These metrics tell you why CR changed. Not just that it did. 🤓 Save this if you want to audit your funnel like a pro

  • View profile for Juan Pablo Ortega

    Co-Founder and CEO at Yuno, Co-Founder at Rappi

    22,333 followers

    When AI agents start shopping for us, will your checkout make the cut? Very soon, your assistant will book travel, restock groceries, and tweak subscriptions on its own. Agents don’t care about brands. They optimize a simple scoring function: probability of success × speed × total cost (price, fees, fraud/friction, returns risk). If your flow underperforms, they’ll route to someone else, automatically and forever. What agents will measure: ⚡ Speed: sub‑second pages, low API latency, reliable inventory/tax/shipping quotes. 🔒 Trust: strong auth without captchas, passkeys/SPC, consistent identity for card‑on‑file.  💳 Payment performance: high approval rates, smart retries, 3DS that’s mostly frictionless, network tokens and wallets. 🧠 Machine readability: structured product/offer data and a clean checkout API with idempotency and webhooks. 🔁 Aftercare: predictable refunds, cancellations, and status updates via API. Translation: If an agent tries two travel sites and one is 2× faster with fewer payment failures, it will learn to prefer that route next time. The “winner” keeps compounding—everyone else gets screened out. Don’t get screened out. Make your checkout agent‑ready now: 👉 Make offers machine‑readable. 👉 Expose a minimal “quote → pay → confirm” API. 👉 Remove human-only blockers (captchas) from trusted agent flows. 👉 Orchestrate payments for speed and approvals, not just cost. 👉 Publish structured returns, delivery promises, and fees. In the agent era, the easiest place to buy wins.

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