Build a Return Abuse Detection Tool for Mid-Market Retailers

1. 1

   Start inside one commerce platform's data

   Orders, returns, refunds, exchanges, addresses, payment tokens, and fulfillment events from a single major platform give you everything needed for a first version, without asking a retailer to build a data pipeline. Ship as an app in that platform's ecosystem so installation is a click.

2. 2

   Detect the patterns retailers already recognize

   Serial ordering and returning of the same item in multiple sizes, returns that arrive underweight or empty, claims of missing items concentrated on one address or courier, repeated receipt-free returns, and refund requests that spike right at policy boundaries. Name each pattern in the language a returns manager uses.

3. 3

   Make every flag explainable and appealable

   Show the specific orders and events behind a flag, let staff mark false positives, and require a human decision for anything that denies a customer. An unexplainable score is unusable in a store, indefensible with a customer, and dangerous as policy.

4. 4

   Draw the consumer data line early and get counsel

   Keep scoring on the retailer's own first-party relationship with its own customers. The moment you consider building cross-retailer consumer profiles that influence whether a person is granted a refund, you are near consumer-reporting obligations under federal fair credit reporting rules and a patchwork of state privacy laws. Get a lawyer before that feature, not after, and design dispute and correction paths regardless.

5. 5

   Prove recovered margin with two design partners

   Run in observe-only mode on historical data first and produce a number: how much refunded value matched abuse patterns last year. That retrospective figure is your entire sales pitch and it costs the retailer nothing to let you calculate it.

6. 6

   Add warehouse evidence capture

   Weight on receipt, photos at the return station, and serial or tag verification turn suspicion into proof and settle disputes instantly. Retailers with a returns dock will pay more for this than for any model, because it also resolves honest mistakes in the customer's favor quickly.

7. 7

   Sell policy simulation, not just enforcement

   Let a retailer test what happens if the window changes, if free returns end for a category, or if a restocking fee appears, using their own history. Policy is the lever executives actually pull, and being the tool that informs it makes you strategic rather than another rules engine.

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