Start with the business question and the evidence you have. Follow the decision tree in the right guide, then read the matching recommendation: which model to start with, why it fits, what data and evidence it needs, and what to validate before adding complexity.
| Use case | Model-selection decision tree | The distinction to resolve first |
|---|---|---|
| Offer recommendation | Choose an offer approach | Product relevance, response prediction, or the incremental effect of an incentive |
| Price recommendation | Choose a pricing approach | Forecast demand at observed prices, or estimate demand under a price change |
| Churn and retention | Choose a churn approach | Predict fixed-horizon risk, estimate event timing, or learn a retention action's effect |
You can combine branches. A recommender can retrieve candidates and estimate offer effects. A churn system can estimate both risk and retention effects. The final business policy still applies costs, eligibility, budget, capacity and the approved fallback.
Each model branch starts with a baseline and has an evidence gate for promotion. If timestamps, outcomes, costs or action support are missing, do the data-collection step first. Recent research challengers stay in the detailed model sections, with their reproduction and evaluation conditions.