Most teams turn on Einstein features in week one and forget about them. The teams that get sustained value pick specific KPIs per feature, measure baselines, run controlled tests of placements and modes, and revisit weekly. The features pay back; the discipline of measuring them is what separates real lift from theoretical.
- Confirm prerequisites and licensing
Einstein is bundled with most Commerce Cloud editions. Confirm your edition in Business Manager. Commerce Agentforce is a separate Agentforce SKU. Without 30 days of shopper behavior data, Einstein features run on global defaults that are weaker than personalized models.
- Enable Einstein in Business Manager
Business Manager, Administration, Site Development, Einstein Configuration. Enable the bundle. Pick which features to activate first; most teams start with Product Recommendations and Predictive Sort, add Search Recommendations after a month, and evaluate Commerce Agentforce once the core features are tuned.
- Place recommender carousels in your storefront templates
The storefront templates ship with recommender carousel components. Add them to product detail, cart, homepage, and category pages. Pick strategy per placement (Also Bought on PDP, Recently Viewed on cart, Top in Category on category landing).
- Pick a Predictive Sort mode per category
Hybrid is the safest default. Test Full on long-tail categories where personalization has the most room to lift. Keep Off on categories with strong brand storytelling reasons for manual order.
- Wire Search Recommendations and approve the first synonym batch
Turn on Search Recommendations. Open Einstein Search Insights, sort by zero-result query frequency, and approve synonyms for the top 10 to 20. Repeat weekly.
- Build a weekly Commerce Insights review
Schedule 30 minutes weekly with the merchandising lead. Review recommendation acceptance rate, search zero-result rate, predictive sort lift by category. The review drives the next week's tuning.
- Test Commerce Agentforce on one category before broad rollout
Pick a high-consideration category (electronics, gifting, fashion) where conversational guidance helps. Pilot for four weeks. Compare conversion against a control before broad rollout.
Which Einstein features are enabled (Product Recommendations, Predictive Sort, Search Recommendations, Content Recommendations, Commerce Insights, Commerce Agentforce). Most teams enable in waves.
Which algorithm (Also Bought, Recently Viewed, Top Sellers, etc.) drives each carousel. Configurable in Business Manager without code.
Off, Hybrid, or Full. Drives how aggressively the algorithm overrides merchandiser pinned order.
Merchandiser-curated synonyms based on Einstein suggestions from zero-result queries. Highest-ROI underused feature.
Compliance and merchandising rules that override the algorithm (exclude out-of-stock, pin sale items, exclude restricted products). Configurable per feature.
- Einstein features need a minimum of 30 days of shopper behavior data to produce useful personalization. New storefronts run on global defaults that often underperform manual merchandising.
- Predictive Sort Full mode can boost raw conversion at the cost of brand storytelling control. Most teams settle on Hybrid for a reason.
- Search synonym suggestions accumulate quickly if no one reviews them. The weekly approval cadence is the discipline that turns the feature on; turning it on without the cadence wastes the data.
- Recommendation acceptance rate per placement varies widely. A carousel that converts on PDP can fail on cart. Test each placement individually rather than assuming the recommender works equally well everywhere.
- Commerce Agentforce is licensed separately from the Einstein bundle. Confirm SKU before assuming it ships with your Commerce Cloud edition.