Next Best Action Strategy
A declarative strategy built in Strategy Builder that defines the logic for Einstein Next Best Action recommendations, combining data filters, recommendation sources, AI models, and business rules to determine which offers or actions to suggest.
Definition
A declarative strategy built in Strategy Builder that defines the logic for Einstein Next Best Action recommendations, combining data filters, recommendation sources, AI models, and business rules to determine which offers or actions to suggest.
In plain English
“A Next Best Action Strategy is a declarative recipe built in Strategy Builder that defines how Einstein Next Best Action recommendations are determined. It combines data filters, recommendation sources, AI models, and business rules to decide which offers or actions to suggest in any given context.”
Worked example
An admin at Brookwell Capital builds a Next Best Action Strategy in Strategy Builder for the customer-success team. The Strategy combines: a data filter (Active Customers only), a Predictive Model (churn-risk score above 70), a Business Rule (account hasn't been contacted in 30+ days), and recommendation sources (the company's Save-Offer catalog). The Strategy returns ranked recommendations to surface in the Next Best Action component on each customer's Account page. When the data scientist tunes the churn model or the analyst updates the offer catalog, the Strategy automatically incorporates the changes. Strategies are the composable recipes for Next Best Action recommendations.
Why Next Best Action Strategy matters
A Next Best Action Strategy is a declarative strategy built in Strategy Builder that defines the logic for Einstein Next Best Action recommendations. It combines data filters (which records to consider), recommendation sources (where the candidate recommendations come from), AI models (which can score or rank candidates), and business rules (which can require, prioritize, or filter recommendations) to determine which offers or actions to suggest. The strategy runs at the moment a recommendation is needed and outputs the ranked list of recommendations to display to the user.
Strategy Builder is the visual designer for Next Best Action strategies, providing a flowchart-like interface for combining elements. The declarative nature means admins or business analysts can build and modify strategies without writing code. Mature programs maintain strategies thoughtfully: starting simple, measuring outcomes, refining based on what works, and gradually adding sophistication as the team learns. Over-engineering strategies up front before measuring real results is a common mistake.
How to set up Next Best Action Strategy
Next Best Action Strategy is the declarative "flowchart" that decides which Recommendations to surface for a given record — load recommendations, filter by context, optionally rank with Einstein scores, output a list. Built in Strategy Builder. The companion piece to Recommendation records and the NBA Lightning component.
- Open Setup → Next Best Action → Strategy Builder
Setup gear → Quick Find: Strategy → Strategy Builder.
- Click New Strategy
Top-right. Wizard prompts for Strategy Name, Description, and Object scope.
- Pick the Object the Strategy operates on
Account / Case / Custom Object. Strategy reads context from current record of this type.
- Drag elements onto the canvas
Element types: Load Recommendations / Filter / Generate / Map / Branch / Sort / Predict / Limit / Output. Connect with arrows.
- For Load Recommendations: pick the source object
Usually Recommendation but can be any object. Filters narrow which records load.
- For Filter: configure criteria
Drop Recommendations not relevant to this record.
- For Predict: bind an Einstein Discovery model
Optional — score recommendations using a predictive model and rank by score.
- For Output: set the final list
Output is what the NBA Lightning component shows. Up to N recommendations.
- Save and Activate
Strategies must be activated to fire. Inactive strategies return nothing.
- Bind to a Lightning Page via the Einstein Next Best Action component
Lightning App Builder → Account / Case page → drop NBA component → bind to this Strategy.
Load / Filter / Generate / Map / Branch / Sort / Predict / Limit / Output.
Rank by Einstein Discovery model output.
Conditional paths based on record context.
Cap the output list size.
- Strategies must be activated. Built-but-inactive strategies return zero recommendations — the most common debug issue.
- Predict element requires a deployed Einstein Discovery model bound to the Strategy. Without one, ranking is rules-only.
- Heavy Load Recommendations + Filter operations can be slow. Strategies running on every record page load add latency — keep them lean.
How organizations use Next Best Action Strategy
Built a strategy for upsell recommendations that combines Einstein scoring with business rules requiring eligibility checks.
Maintains separate strategies for different service contexts, each tailored to the specific recommendation needs.
Uses Strategy Builder to operationalize data science work into actionable recommendations within Salesforce.
Trust & references
Straight from the source - Salesforce's reference material on Next Best Action Strategy.
- Strategy BuilderSalesforce Help
Test your knowledge
Q1. What is a Next Best Action Strategy?
Q2. What does Strategy Builder combine?
Q3. What's a common mistake?
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