What Is Einstein Next Best Action in Salesforce and How It Works? 

14 min Updated: 05.09.2025
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CTO, Founder | Salesforce Architect

Pavel Klachkou

If your team has worked with Salesforce for a while, you’ve probably seen at least one or two of them staring at a record and hesitating. There’s a lead with no recent activity, a case that’s been open too long, or a customer account that looks off. But what’s the next move? 

Most of the time, people guess. Or they wait around until someone tells them what to do. This hesitation, this in-between space where nobody’s quite sure what should happen next: it adds up. Across dozens of users and hundreds of interactions, it drags down productivity and chips away at the customer experience. 

Next Best Action Salesforce

Salesforce Einstein Next Best Action was built for that moment. It looks at what’s happening right now, applies the logic you’ve given it, and offers a clear next step: “Send a follow-up,” “Escalate this case,” “Offer a discount,” “Schedule a call.” Whatever makes sense, based on the data. 

It’s structured logic, powered by your business rules, layered with Salesforce AI tools and agents only where it helps. At Routine Automation, we help teams build these Salesforce NBA strategies from scratch. Not just “what should pop up,” but why, when, and for whom. When it’s done well, Einstein NBA doesn’t just save time. It prevents bad decisions, and helps teams operate smoother.  

What Is Next Best Action in Salesforce?  

Next Best Action in Salesforce is exactly what it sounds like: the system that recommends what a user should do next, based on the situation they’re in. The recommendations given by Salesforce NBA aren’t static. They respond to context. Who the user is. What kind of record they’re looking at. What’s happened recently. What hasn’t happened yet. 

You define the logic. Salesforce runs it in real time. 

Here’s how it breaks down: 

  • Recommendations are the actions you want to offer. These live in the Recommendation Builder. You might have one for “Upgrade Plan,” one for “Check-in Call,” and so on. 
  • Action Strategies are where you decide when each recommendation should show up. You can rank them, filter them, or build branching logic that adapts to different situations. 
  • Flows (or Apex, if you want more control) handle what happens when someone clicks. You might launch a screen flow, send a Slack notification, or update a field. 

All of this happens inside Salesforce. You don’t need an external platform or a third-party integration for Einstein next best action, and you don’t need to guess whether it’s working.  

Salesforce gives every org 5,000 strategy requests per month at no cost, tracked in Setup.  

You can also connect Salesforce Einstein NBA to Einstein Prediction Builder if you want to factor in AI-generated scores for things like churn risk, lifetime value, or likelihood to convert.  

How Does Einstein NBA Work?  

There are three core pieces to how Salesforce Einstein Next Best Action actually works: Recommendation Builder, Action Strategies, and Flows. Each one does a very specific job, and together, they form a flexible system that works across almost every Salesforce Cloud. 

1. Recommendation Builder 

This is where you create the list of actions you want to suggest, the things your team might need to do in specific scenarios. Each recommendation is a record. It has: 

  • A label (what the user sees) 
  • A description (optional, but helpful context) 
  • A category (for grouping) 
  • A defined action (what happens when clicked) 

That action can launch a Flow, redirect to a URL, update a record, or do something custom with Apex. These are the “cards” that get surfaced on screen. You can create as many as you want, and reuse them in different strategies. 

2. Action Strategy (Built in Flow Builder) 

This is the logic layer, or the decision engine. It decides which recommendation to show, to whom, when, and why. As of now, Salesforce strongly recommends using Flow Builder to author your strategy, not the older Strategy Builder UI. Flow is more stable, has better support, and gives you full access to: 

  • Decision branches 
  • Record filters 
  • User conditions 
  • Priority scoring 
  • Categories and ranking 

You can think of this like a filtering pipeline. A user opens a record, and Salesforce runs through your logic:  

  • Is this user in Sales or Support? 
  • Does the record meet the conditions? 
  • Have they seen this recommendation before? 
  • Which one has the highest priority right now? 

Only the cards that pass through those filters will appear. 

3. Flows (or Apex Logic) 

Once a user sees a recommendation and clicks it, the action fires. Most teams use Screen Flows for this. It’s fast, easy to maintain, and plays nicely with the rest of Salesforce. For more complex use cases, like triggering external APIs, calculating real-time pricing, or integrating with third-party platforms you can also use Apex. 

There’s also a variable called IsRecommendationAccepted. This flag lets you branch logic depending on how users respond: 

  • If they accept it, trigger a sequence. 
  • If they ignore it or dismiss it, take a different route (or do nothing). 

This kind of branching logic is how NBA becomes more than just a hint — it becomes a real part of your automation engine. 

Unlock Smarter Workflows with Einstein NBA
Our team at Routine Automation helps you implement and customize Einstein Next Best Action from day one. We implement smart, contextual decisioning that actually fits your business. 

Salesforce Next Best Action Use Cases 

Salesforce Next Best Action isn’t just a tool for one type of team. It fits wherever people are making repeated, time-sensitive decisions, which is most departments, most days. 

Let’s consider some real-world use cases across different Salesforce Clouds where we’ve seen Einstein NBA make a measurable impact. 

Salesforce Next Best Action Use Cases 

Sales Cloud: Helping Reps Focus on What Moves the Deal 

Sales reps usually have a list of leads and accounts in front of them. The question is always: which ones are worth acting on today? 

With Next Best Action in Salesforce Sales Cloud, reps don’t have to guess. 

Use case example

  • A rep opens a lead record. NBA recommends: “Send product demo invite,” based on engagement history and stage. 
  • An opportunity’s close date is slipping. NBA says: “Loop in legal team,” or “Escalate to manager.” 
  • The customer hasn’t responded in two weeks. NBA triggers: “Send re-engagement email with time-limited offer.” 

These cards show up right inside the opportunity or lead page. No dashboards. No extra clicks. Just clear, contextual prompts. 

Service Cloud: Guiding Agents in Real-Time Conversations 

Customer support is full of unpredictable scenarios. Einstein NBA brings structure to opportunities within Salesforce Service Cloud.  

Examples: 

  • A case hits a certain severity or SLA threshold. NBA suggests: “Offer expedited resolution,” or “Escalate to Tier 2.” 
  • A customer calls in about a billing issue. Based on account history, NBA offers: “Apply courtesy credit,” or “Send usage summary.” 
  • A product return request is logged. NBA displays: “Suggest upgrade instead of refund,” based on previous purchases. 

These recommendations can appear in the Omni-Channel console, agent scripts, or even inside chat workflows. Agents don’t have to search for what to do, it’s already there. 

Marketing Cloud: Personalizing Outreach at Scale 

NBA isn’t just for users inside Salesforce, it can guide how you interact with customers on the outside, too. Within Salesforce Marketing Cloud Einstein NBA guides promotions. 

Examples: 

  • A customer abandons their cart. NBA triggers a Flow that recommends: “Send limited-time discount with product reviews.” 
  • A subscriber reaches 90% of their engagement threshold. NBA says: “Send loyalty offer with tier upgrade CTA.” 
  • Customer hasn’t interacted in 60 days. NBA triggers: “Send reactivation email,” or “Survey feedback on content relevance.” 

These are built as backend Flows, not user-facing cards, but they run on the same logic engine. 

Healthcare, Insurance, and Financial Services: Compliance + Personalization 

In regulated industries, timing and context are always table stakes. 

Use cases we’ve built at RA: 

  • For a healthcare provider: NBA prompts front-desk staff to verify insurance if a patient’s plan shows high denial risk. 
  • For a bank: NBA surfaces “Schedule annual review call” when a client account hits a certain balance change. 
  • For an insurer: NBA recommends “Send policy upgrade email” to policyholders within 30 days of renewal. 

These are all workflows running live in Salesforce right now, saving agents time and keeping organizations compliant and consistent. 

Internal Ops and Revenue Teams: Nudging the Back Office 

It’s not just customer-facing teams that benefit. Salesforce NBA is also powerful behind the scenes. 

Examples: 

  • Finance sees a large invoice unpaid past due date. NBA recommends: “Escalate to account exec.” 
  • Legal receives a new contract upload. NBA prompts: “Check for missing e-signature.” 
  • RevOps sees a drop in product usage. NBA says: “Trigger QBR scheduling flow.” 

Internal prompts like this reduce delay and prevent things from falling through the cracks — without adding another Slack bot or reminder system. Need more RevOps automation ideas? Check out our RevOps best practices guide

Next Best Action Salesforce Examples 

Still uncertain about the potential of Einstein Next Best Action? Let’s look at some grounded examples, pulled from real-world implementations.  

Example: Service Cloud: What Should the Agent Do First? 

A customer calls in about a failed order delivery. The support agent opens the case record. Here’s what Einstein NBA shows: 

Top recommendation: 

“Offer complimentary shipping credit.” 

Why?

👉 The system sees this customer had a late shipment three months ago. 
👉 Their CSAT score dropped. 
👉 The current issue is marked as high priority. 

Second recommendation: 

“Escalate to Logistics Tier 2.”

Why?

👉The case topic matches a known supply chain issue flagged last week. 
👉There’s an open flag from operations.

The agent doesn’t need to dig through history. The system surfaces relevant actions, right in the Omni-Channel console, using a Salesforce Next Best Action component on the case page. 

When the agent accepts the recommendation, a Flow kicks off: 

  • Applies a credit 
  • Notifies the logistics manager 
  • Updates the case with a standardized resolution note 

That’s three steps automated, triggered by a click. 

Example: Sales Cloud: Which Lead Should I Call Next?

A rep opens their lead queue on a Tuesday morning. Normally, it’s a mess: 50 leads, no clear signal. 

This time, Einstein NBA is active. 

They open a lead record. A card at the top says: 

Recommendation

Call now – engagement score trending down.

What triggered it? 

👉 The lead interacted with a pricing page twice last week. 
👉 But hasn’t opened the last two emails. 
👉 They’re in a late stage of the nurture sequence, and scoring has dropped 15%. 

The card links to a Flow that: 

  • Launches a call script with recent interaction notes 
  • Logs the call 
  • Updates a custom “touched” field 

Meanwhile, NBA limits this prompt to once every 48 hours, so the same rep doesn’t get spammed with repeat actions. Reps start making contact at the right moment, not days too late.

Example: Marketing Cloud: A Quiet Customer Comes Back 

A returning customer visits a subscription product page but doesn’t complete checkout. They have a past history of purchasing add-ons. 

Salesforce NBA is working behind the scenes. 

A Flow runs in the background, triggered by their behavior. It passes through the strategy logic and fires the top action: 

“Send dynamic email: Welcome back + personalized offer” 

The email includes: 

👉 A 10% discount 
👉 Suggested add-ons based on last purchase 
👉 A pre-filled checkout button  

The customer gets the message within 10 minutes of leaving the site. 

No human built or launched this campaign manually. NBA made the decision, based on: 

  • Activity timestamp 
  • Known product history 
  • Abandoned cart signal 

Routine Automation built this for a subscription brand using NBA + Marketing Cloud Engagement, connected via Flow and external events. 

Build Smarter Salesforce Workflows 

From first strategy to advanced multi-cloud automation, Routine Automation helps you get more from Einstein Next Best Action with recommendations your team will actually use.

Key Advantages of Intelligent Recommendation Tools 

The main promise of Einstein Next Best Action isn’t just “more AI.” It’s fewer bad decisions, made faster, and with more context. With NBA, Salesforce ensures teams don’t have to pause and think, “What do I do now?” They act faster, more consistently, and with better results.  

The benefits of Einstein Next Best Action in Salesforce include: 

Einstein Next Best Action
  • Improved Experiences: When someone opens a support case or a sales opportunity, the system doesn’t just show a generic message. It pulls from that customer’s history, recent behavior, and status to recommend actions that fit their context. It enables personalization at scale, improving customer loyalty.  
  • Enhanced Efficiency: Salesforce Einstein NBA doesn’t replace your team, it supports them. You can design logic once, then scale it across hundreds of records and users. Whether it’s guiding junior support agents or nudging sales reps through a complex deal cycle, you’re reducing the number of things people have to remember or figure out manually. 
  • Adaptability: NBA logic lives in Flows. That means no need to write code, submit tickets, or wait on a dev sprint to change a strategy. You stay in control, without depending on a technical team to make small changes. 
  • Governance and Consistency: One of the hidden advantages of NBA is that it standardizes decisions across the team. Whether you have five agents or 500, they’re working off the same logic, not individual habits or hunches. 

NBA isn’t limited to one part of Salesforce either. It works across every cloud, showing up wherever your team members are. If you’re already using other Salesforce AI tools, NBA ties in smoothly. It can pull from predictions, trigger flows, and even connect to external data via MuleSoft or API calls. 

How to Set Up NBA in Salesforce  

You don’t need a developer. You don’t need a full sprint. But you do need to think through the logic before you start clicking. 

Setting up Salesforce Einstein Next Best Action isn’t complicated. The hard part is making sure your recommendations actually reflect how your team works. 

Below is a clear, step-by-step process we follow at Routine Automation when implementing NBA for clients. This gets you up and running, without building something that collects dust. 

Step 1: Create Your Recommendations 

Start in Recommendation Builder. This is where you define the actual suggestions that will appear to users. 

Each recommendation includes: 

  • A title (what appears on the card) 
  • An action label (the call-to-action button) 
  • A description (optional – good for training or context) 
  • An associated Flow, screen, or URL 
  • Optional: a category for grouping/filtering 
  • Optional: expiration or recurrence settings 

These are just records. You can create them manually or import in bulk if needed.

Step 2: Build the Strategy Logic 

This is where your logic lives. You’ll do this in Flow Builder, which Salesforce now recommends over the older Strategy Builder UI. 

Inside Flow Builder, you’ll: 

  • Set entry conditions (when the strategy runs) 
  • Add Load elements (which Recommendations to include) 
  • Apply filters and decisions (based on user role, record type, status, etc.) 
  • Use priority fields to sort which card shows up first 
  • Group recommendations by category or audience 
  • Set limits (e.g., one card per user per day, only once per record, etc.) 

Tip from the field: Add a condition to prevent duplicate logic paths, especially if a recommendation can be triggered in multiple ways. 

Step 3: Attach the Recommendations to the Right Records 

Once your strategy is live, you need to decide where it actually appears. 

Most teams start with Lightning record pages: leads, opportunities, accounts, cases. From there, you can expand into: 

  • Omni-Channel consoles 
  • Experience Cloud pages 
  • Custom components or mobile 
  • Embedded dashboards 

All you do is drop in the Salesforce Next Best Action component, then point it to the right strategy. Yo

Step 4: Test Your Flow Before You Launch 

Always test your NBA setup with real data. At RA, we use record-level test cases to simulate edge conditions like: 

  • Users with multiple matching recommendations 
  • Records that meet multiple strategy paths 
  • Cases where no recommendation should show up 

You should also test: 

  • Card visibility on different devices 
  • Flow execution paths for accepted vs. ignored recommendations 
  • Load time and responsiveness on high-volume pages 

Once everything’s working as expected, activate the strategy and go live.

Step 5: Monitor, Measure, and Improve 

NBA isn’t something you set once and forget. Salesforce gives you detailed reporting on: 

  • Which recommendations are shown most 
  • Which ones are clicked (accepted) 
  • Which ones are dismissed 
  • What’s triggering vs. not triggering 

From there, you can: 

  • Retire low-value cards 
  • Adjust priority scoring 
  • Split test recommendation timing or placement 

Strategic Decision-Making with Salesforce NBA 

Salesforce Einstein Next Best Action isn’t about adding another layer of automation just because the platform supports it. It’s about giving your teams fewer choices, with better outcomes. When done right, Salesforce NBA doesn’t just make Salesforce more useful. It makes your operations more consistent, your customer experience more responsive, and your teams more focused.  

At Routine Automation, this is our zone. We don’t just wire up recommendations. We help you figure out where they belong, how they drive business value, and how to maintain them over time. 

Whether you’re using Sales Cloud, Service Cloud, Marketing Cloud, or building something industry-specific, we can help you make Next Best Action in Salesforce not just functional, but foundational. 

FAQs

It’s a recommendation engine in Salesforce that suggests the most relevant next step based on business logic, filters, and (optionally) AI predictions. Companies use it as a way to guide users in real time, without relying on guesses.  

Teams use it across sales, service, marketing, and operations to trigger the right action at the right time, like offering a discount, sending a follow-up, escalating a case, or launching a custom Flow. You define the logic. Salesforce delivers the prompt. 

No. Most of the setup happens inside Salesforce’s Flow Builder and Recommendation Builder, both are admin-friendly, with drag-and-drop interfaces. If you want to extend it with Apex or APIs, Routine Automation can handle the technical side. 

NBA works across Sales Cloud, Service Cloud, Experience Cloud, Health Cloud, and Marketing Cloud, depending on your edition and configuration. It’s included in most Enterprise and Unlimited orgs, with 5,000 free strategy requests per month. 

Popular use cases include: 

  • Suggesting next outreach steps in Sales 
  • Guiding agents through complex support workflows 
  • Recommending upsell offers based on customer behavior 
  • Reducing churn with proactive retention actions 
  • Helping internal teams follow process and compliance rules 

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We help you design, build, and optimize Einstein Next Best Action strategies that actually match your workflows, with intelligent automation, governed logic, and measurable results. Schedule a strategy session with our Salesforce-certified experts today.