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ROI and risk model

This page explains ROI and risk model and how it fits into the RecSys suite.

Who this is for

  • Stakeholders evaluating whether a RecSys pilot is “worth doing”
  • Product and analytics teams who need a simple measurement plan
  • Engineering leads who want to de-risk ownership and rollout

What you will get

  • A lightweight ROI template you can adapt to your domain
  • A concrete “what to measure” checklist (with links to the right docs)
  • A risk checklist with mitigations and escalation cues

ROI (template, not a promise)

Recommendations only create value if they move a business KPI while keeping guardrails healthy.

Start with one primary KPI per surface:

  • ecommerce: conversion rate, revenue per session, add-to-cart rate
  • content: time spent, return rate, completion rate

Then define 2–4 guardrails:

  • latency / error rate
  • empty-recs rate
  • user complaints or negative feedback signals
  • diversity / coverage constraints (if applicable)

A simple ROI framing:

  • Incremental value = (KPI lift) × (eligible traffic) × (value per action)
  • Cost = engineering time + operational load + infrastructure

Your pilot goal is to decide whether the incremental value is large enough to justify a production rollout.

Measurement plan (what we need from you)

To measure lift reliably, you need consistent logging and joins:

  • Exposure logs: what was shown (with ranks)
  • Outcome logs: what the user did
  • Stable join IDs: request_id and a pseudonymous user_id or session id

Start here:

Risks and mitigations (practical)