Offers, Decisioning, and Personalization
Decisioning in AJO selects the best offer or content for a profile using decision management. The candidate must know the building blocks: offer items (the actual offer), representations (how the offer appears per channel/locale), placements (where the offer appears), collections (groupings), decision rules (eligibility), ranking (priority/order), and fallback offers (what to show when nothing qualifies). Decision scopes tie placements to rules and ranking. Personalization uses the expression editor with profile attributes, event context, offers, and helper functions.
Key concepts: eligibility rules filter offers; ranking formulas or priority order decide among eligible offers; frequency capping limits how often an offer is shown; fallback ensures a message never renders empty. Personalization can be static (attribute), conditional (dynamic content), or decisioning-driven (offer decision activity in a journey).
The traps: (1) confusing offer item (the offer itself) with representation (the channel-specific rendering); (2) forgetting the fallback offer - questions often describe an empty message when no offer qualifies; (3) mixing eligibility rules (can this profile see it?) with ranking (which one wins?); (4) assuming decisioning is only for email - it works across channels; (5) confusing placement (where) with collection (grouping). Another trap: personalization syntax errors - preview and validate before publishing.
Worked example
A bank wants the best credit-card offer in a web banner. Define an offer item ("0% APR for 12 months"), a representation for web, a placement (homepage banner), a decision rule (credit score > 700), a ranking (highest priority wins), and a fallback ("Explore our cards"). The journey's offer decision activity returns the winning offer.
Rule of thumb
Every decision needs a fallback. If no offer qualifies, the fallback prevents a blank message - a frequent exam trap.