Recommendation Strategy
In Salesforce Einstein Next Best Action, a strategy built in Strategy Builder that defines the decision logic for which recommendations to surface, combining data sources, filters, AI models, and business rules.
Definition
In Salesforce Einstein Next Best Action, a strategy built in Strategy Builder that defines the decision logic for which recommendations to surface, combining data sources, filters, AI models, and business rules.
In plain English
“A Recommendation Strategy in Einstein Next Best Action is a strategy built in Strategy Builder that defines which recommendations to surface. It combines data sources, filters, AI models, and business rules to decide what to suggest to users.”
Worked example
Pinegrove Capital builds a Recommendation Strategy in Einstein Strategy Builder for their Next Best Action panel. The Strategy combines three signals: a Predictive Model that scores the customer's churn risk, a business rule that flags VIP customer-segment, and a filter that excludes customers with active escalations. When all three converge on "high-risk VIP without escalation," the Strategy surfaces a "Schedule Save Call" recommendation. The Strategy is editable visually - the data scientist can tune the model weight or the business analyst can update the segment criteria without rewriting the whole Strategy. Strategies are how AI models, business rules, and filters compose into actionable recommendations.
Why Recommendation Strategy matters
In Salesforce Einstein Next Best Action, a Recommendation Strategy is a strategy built in Strategy Builder that defines the decision logic for which recommendations to surface, combining data sources, filters, AI models, and business rules. The strategy is evaluated at runtime when a recommendation is needed, producing the ranked list of recommendations to display based on current context.
Strategy design is where the intelligence of Next Best Action lives. Simple strategies might just filter recommendations by eligibility; sophisticated strategies combine multiple data sources, AI scoring, and business rules for context-aware recommendations. Mature programs start simple and iterate based on measured results rather than over-engineering up front.
How organizations use Recommendation Strategy
Built a strategy combining opportunity data filters with Einstein scoring for context-aware sales recommendations.
Maintains multiple strategies for different service scenarios, each tuned to that context.
Uses Strategy Builder to operationalize analytics insights as actionable recommendations.
Trust & references
Straight from the source - Salesforce's reference material on Recommendation Strategy.
- Strategy BuilderSalesforce Help
About the Author
Dipojjal Chakrabarti is a B2C Solution Architect with 29 Salesforce certifications and over 13 years in the Salesforce ecosystem. He runs salesforcedictionary.com to help admins, developers, architects, and cert/interview candidates sharpen their fundamentals. More about Dipojjal.
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