Offers change the price the customer actually pays. Retention offers use the same customer attention and often the same subsidy budget. If each system maximises its own score alone, a customer can get competing discounts, a campaign can contaminate a pricing test, and the same revenue can be counted twice.
Log list price, recommended price, final paid price, subsidy source and every concurrent campaign assignment. Start with mutually exclusive experiments or one shared assignment plan. Give one coordinator ownership of the final action, including no change/no contact. Cap total spend, contact frequency and allowed price movement. Treat customer-level policy effects and inventory spillovers as part of experiment design.
Optimise combined actions only after you have data supporting them. Separate offer and price models cannot identify the effect of an untested discount-plus-price change. Use a factorial design (testing the combinations) where it fits, or test the combined policy directly. Report total net contribution once, with component metrics to explain it.
For logged policy evaluation, record the coordinator's joint assignment probability, or its stage-by-stage rule, with pre-decision budget, stock and contact state. Separate marginal probabilities do not usually describe a combined action. A new policy can also change future inventory and eligibility, so a one-decision evaluation cannot show the whole system's long-term value. The shared policy evaluation protocol sets out these limits and the controlled-test path.