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ecommerce · analytics

Low conversion logic tree

This logic tree separates a conversion decline into traffic quality and the purchase flow. A shift in channel mix can lower conversion even if the site itself has not changed. If traffic is stable, funnel data can show whether the failure occurs on the landing page, product page, checkout, or payment step. The tree also keeps shipping cost, stock, and offer clarity visible as distinct explanations. Use comparable cohorts and dates when testing the branches, because seasonality and campaigns can distort headline conversion. The output should be a short list of supported hypotheses ready for experiments or fixes. It gives readers a concise reference they can reuse when discussing the result with colleagues.

Type Decision treeStandard Howard-Raiffa / CART-sklearn / taxonomyEngine schematex-decisiontreeUpdated 9/24/2026
Low conversion diagnosis
Drawing preview
The request

“A logic tree for falling ecommerce conversion: split into Traffic quality and Purchase flow, with channel mix, landing pages, checkout completion, payment errors, shipping costs, price, stock, and product pages.”

Then tryAdd a mobile performance branchSplit payment errors by payment method
What is in this drawing

Read the decisions behind it.

01Traffic

Check whether visitor intent changed.

02Flow

Locate the funnel stage with the largest drop.

03Offer

Test price, stock, and message only after the data supports it.

Use to structure a conversion-rate investigation before selecting experiments.

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FAQ

Common questions

What is traffic quality?

How closely visitors match the audience and intent likely to purchase.

Why use cohorts?

They separate changes in visitor mix from changes in site performance.

What is a purchase-flow check?

Comparing completion rates at each step from landing to payment.