Turn Salesforce Experience Cloud Into an Intelligent Customer Experience With AI

Most Salesforce Experience Cloud sites launch with promise but quickly plateau. EverAfter's AI Suite transforms Experience Cloud into a living, intelligent experience that personalizes every interaction, automates engagement, and drives measurable outcomes without adding development resources.

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The Experience Cloud Reality Check

Your Salesforce Experience Cloud site launched with strong engagement. Customers loved the centralized hub. Your team built something powerful. But six months in, you're noticing the same pattern many Experience Cloud admins see: engagement is plateauing, and your team is still doing a lot of manual work to keep customers moving forward. Here's what I've seen after working with dozens of Experience Cloud deployments. You've probably invested significant time customizing Lightning components, setting up your Community navigation, configuring audiences and permissions, maybe even building custom Flows to automate parts of the customer journey. Experience Cloud gives you an incredibly robust foundation: secure authentication, Salesforce data integration, mobile responsiveness, and enterprise-grade infrastructure.

But there's a gap most admins hit around month six. Your customers log into a portal that shows everyone the same resources, regardless of where they are in their journey, what their goals are, or how they're actually using your product. Your CSMs are manually following up on tasks that should trigger automatically based on customer behavior. The Community feed has activity, but it's not personalized to what each user needs right now. Your knowledge articles are comprehensive, but customers still can't find the specific answer to their specific situation. Support tickets pile up for questions that should have been self-served. It's not a limitation of Experience Cloud itself. The platform is powerful. The challenge is making it intelligent and adaptive at the individual customer level, without requiring constant manual work from your team or extensive custom development.

Experience Cloud gives you the infrastructure and the data model. The question is: how do you layer intelligence on top to make every interaction personalized, automated, and contextual?

What Makes Experience Cloud "Intelligent"

The answer is an AI engagement layer that works with your existing Experience Cloud setup. I've talked to enough Experience Cloud admins to know that you're not looking to rip and replace what you've built. You've invested in setting up your Community templates, configuring record access, building custom components, and integrating with your Salesforce org. That infrastructure is valuable.

EverAfter sits on top of Experience Cloud as an embedded intelligence layer. It connects to the data you already have in Salesforce, uses the authentication and security you've already configured, and surfaces inside the Community interface your customers already use. The difference is what happens next: instead of showing static content, every interaction becomes personalized based on customer data, contextual based on where they are in their journey, and automated based on the signals coming from your tech stack. Think of Experience Cloud as your secure, scalable foundation with all the infrastructure capabilities Salesforce is known for. EverAfter is the layer that makes that foundation intelligent, reading customer signals in real time and adapting the experience automatically.

Take Okta, for example. They had built a strong Customer Success Hub on Experience Cloud with all the right infrastructure pieces. But they had no way to capture what each customer was trying to achieve or personalize the experience at scale. By embedding EverAfter into their existing Experience Cloud site, they transformed their Community from a resource library into a goal-based, intelligent system. More on how they did it in a moment. The shift happens through four integrated AI capabilities. Each one solves a specific challenge that Experience Cloud admins deal with regularly.

The Four AI Capabilities That Multiply Experience Cloud Value

EverAfter's AI Suite consists of four integrated capabilities. I'll walk through each one, what Experience Cloud challenge it solves, and what it looks like in practice. Together, they turn your Community into an intelligent system that reads customer signals, adapts in real time, and takes action automatically.

AI Studio: Build Any Experience You Imagine, Instantly

AI Studio brings vibe coding to post-sale experiences. Instead of waiting on developers or being limited by pre-built Lightning components, you describe what you want, and AI builds it.

The Experience Cloud challenge it solves: Most admins hit the same wall. You know exactly what experience you want to build for customers, but executing it means one of three things: spending weeks learning to customize Lightning components yourself, getting in the dev queue and waiting, or settling for something generic that doesn't quite fit your use case.

Here's what it looks like in practice: Let's say you need a custom renewal health tracker that pulls opportunity data from Salesforce, usage metrics from your data warehouse, and displays it all in your brand style with conditional formatting based on renewal risk. In a traditional Experience Cloud setup, that's a custom component build with Apex controllers, SOQL queries, and front-end work. With AI Studio, you describe what you need, and it's built in minutes.

Same thing with an interactive product adoption dashboard that's specific to enterprise customers, or a goal-setting interface that adapts based on customer maturity level. These are the kinds of interfaces that used to require custom development, but now post-sale teams can build them directly.

What's changed is that you're not limited to the out-of-the-box Lightning components or generic templates anymore. Every interface can be purpose-built for your specific use case, branded to your standards, and connected to your live Salesforce data without writing code.

The impact: You get unlimited creation capability with enterprise-grade security and true personalization. Your Experience Cloud Community becomes as dynamic and adaptable as your customers need it to be, without the development bottleneck.

AI Builder: Create Personalized Journeys, Fast

AI Builder is an AI-powered interface builder that creates complete, personalized customer programs based on your inputs. Think onboarding flows, success plans, QBR templates, renewal journeys.

The Experience Cloud challenge it solves: You've probably built audience-based experiences in Experience Cloud before. You set up different page layouts for different profiles, maybe use dynamic components that show or hide based on field values. It works, but it's time-intensive to set up and maintain. Every new customer segment means duplicating work, and keeping everything in sync across hundreds or thousands of customer records is a manual nightmare.

Here's what it looks like in practice: You upload your onboarding playbook, connect to your Salesforce data, and configure what personalization matters most: customer goals, product edition, industry vertical, company size, user role. AI Builder generates personalized interfaces for each segment automatically. SMB customers see a different journey than Enterprise. Technical admins see different content than business stakeholders. All of it syncs in real time with your Salesforce records.

The real value comes when things change. When you update your product or refine your process, AI Builder adapts every customer interface at once. You're not hunting through audience definitions or manually updating hundreds of Community pages. You update the logic once, and personalization propagates automatically.

The impact: You can launch fully branded, context-aware customer interfaces in hours instead of the weeks it typically takes to build and configure audience-based experiences. You build the logic once, and AI Builder handles the personalization for every customer record in your org.

AI Expert: Turn Your Portal Into a Self-Learning Knowledge Hub

AI Expert connects to your entire knowledge ecosystem (documentation, past implementations, internal tools, support tickets, Community discussions) and delivers contextual, accurate answers in real time.

The Experience Cloud challenge it solves: You've probably spent time organizing your Knowledge articles in Experience Cloud, setting up article types, configuring search, maybe even implementing Einstein Search. But there's still a gap. Customers search for things using their language, not your taxonomy. They don't know which article category to look in. The search returns 47 results, but which one actually answers their specific question in their specific context? Most customers give up and open a case.

Here's what it looks like in practice: A customer logs into your Experience Cloud Community mid-implementation. Instead of searching through articles or posting in the Community feed, they ask a direct question: "How do I configure SSO for my team?" AI Expert pulls from your Knowledge base, looks at past successful implementations for similar customers, checks your internal documentation, and delivers a personalized, step-by-step answer that's relevant to their specific setup. All of it surfaces right there in the portal, in context, when they need it.

What makes this different from basic search or a standalone chatbot is the integration. AI Expert understands where each customer is in their journey, what products they've purchased, what their technical setup looks like, and what problems similar customers have solved. It's using all that context to surface not just any answer, but the right answer for this customer right now. And because it connects to your live systems, the answers stay current automatically as your documentation and processes evolve.

The impact: Customers get expert-level guidance instantly without opening a case. You see fewer support tickets, better self-service adoption, and faster time-to-value. Your knowledge ecosystem finally works the way it should, with intelligence that understands context and intent.

AI Agent: Engage Every Customer in Real Time

AI Agent is intelligent automation that detects signals from across your tech stack and takes customer-facing action automatically.

The Experience Cloud challenge it solves: You've probably set up some Process Builder flows or Flow automations in Experience Cloud. Maybe you trigger a Community notification when a case status changes, or send an email when someone completes a task. But those are simple if/then rules. What about the more nuanced scenarios? A customer who's gone quiet for three days in the middle of onboarding, but only if they're in a specific product tier and haven't hit a certain usage threshold. Or a renewal that's 45 days out, but only for customers who haven't engaged with their latest feature release. Building that level of conditional logic in Flows gets complex fast, and maintaining it across hundreds of scenarios becomes unmanageable.

Here's what it looks like in practice: A customer hasn't completed their onboarding checklist in three days. AI Agent detects the stall, checks their engagement history and product usage data, and determines this customer needs a nudge. It automatically posts a personalized message in their Experience Cloud hub, updates the CSM record in Salesforce, and triggers a contextual email sequence. No one had to manually monitor the dashboard or set a reminder.

Or another scenario: a customer reaches a major milestone (first successful API call, completed their first workflow, hit 100 active users). AI Agent recognizes it in real time, celebrates it with a banner in their Community interface, surfaces the logical next action based on similar customer paths, and notifies the account team. It's reading signals from your product, your data warehouse, your support system, understanding what matters, and taking action accordingly.

The impact: Your team sees a 40% reduction in manual follow-ups. Customers get 24/7 engagement that keeps momentum high. You deliver consistent experiences at scale without burning out your CSMs on repetitive tasks. The team focuses on strategic accounts and complex situations while AI Agent handles the execution layer.

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Real-World Proof: How Okta Transformed Their Experience Cloud

The best way to understand how these four capabilities work together is to see them in action. Okta's story shows what's possible when you layer intelligence on top of Experience Cloud infrastructure.

The Challenge

Okta's Digital Acceleration & Growth team had already built a solid foundation. They had a Customer Success Hub running on Salesforce Experience Cloud, with onboarding flows, lifecycle email automation, in-app messaging through Pendo, and well-organized Community content. From an infrastructure perspective, they were doing everything right.

But there was a critical gap in their data model. "We had no way of knowing what customers wanted to achieve," said Alana Stoltzfus, Senior Manager of Automation & Scaled Insights at Okta. Business goals were captured during pre-sales conversations, sometimes documented in Salesforce notes or opportunity records, but then effectively lost. There was no structured field to capture them, no way to surface them in the customer journey, and no mechanism to use them for personalization at scale.

Their digital customers (accounts without dedicated CSM coverage) all saw the same generic experience in Experience Cloud because the system had no way to know what each customer was trying to accomplish or where they were in their maturity journey.

The Solution

Okta embedded EverAfter directly into their existing Experience Cloud Community and restructured the entire model around customer goals. Instead of starting with resources and hoping customers found what they needed, they flipped it: capture the goal first, then dynamically surface the right path.

Here's how the four AI capabilities came together in their Experience Cloud environment:

AI Studio built custom interfaces that didn't exist in standard Experience Cloud components. A goal-selection interface where customers choose their business objectives from Okta's Identity Maturity Model. A maturity assessment dashboard that visualizes where they are and what's next. All of it branded to Okta's standards and embedded directly in the Community interface customers already knew.

AI Builder automated the creation of personalized success plans for each account based on their declared goals and live product usage data from Databricks. When a customer selects "Improve Security Posture" as their goal and the system sees they're at maturity level 2, AI Builder generates a tailored set of recommendations, tasks, and resources specific to that combination. Every customer gets a different plan, but Okta's team doesn't build any of them manually.

AI Expert surfaces contextual guidance throughout the journey. When a customer is working through their success plan, AI Expert pulls from Okta's Knowledge base, internal best practices, and past successful implementations to provide just-in-time answers without forcing customers to leave their current context.

AI Agent monitors progress and triggers automated interventions. When a customer completes a key task, AI Agent celebrates the milestone and surfaces the next logical action. When a task goes overdue or a customer shows signs of stalling, AI Agent posts a nudge in the Experience Cloud interface and alerts the team in Salesforce.

The entire system connects Databricks, Gainsight, Salesforce, and Pendo through EverAfter. No new data silos, no added manual work for CSMs, just intelligence layered on top of the infrastructure they'd already built.

The Results

Okta scaled their digital success motion to unmanaged accounts without adding headcount. Customers weren't just accessing resources anymore, they were working toward goals they had explicitly chosen, with every recommendation tied to their current maturity level and product usage patterns.

"EverAfter checked all the boxes. It let us capture business goals and sync with our entire stack. No new silos. No added CSM work," said Joshua K. Pritchett, Director of Scaled CS at Okta.

The model worked so well that Okta is now expanding it beyond digital customers. They're building CSM-supported versions for high-touch accounts, pre-sales experiences to help prospects visualize their path to value, and guided onboarding flows for newly activated customers. The same infrastructure, the same AI capabilities, just applied across more use cases.

Read the full Okta case study

Three Steps to Get Started

You don't need to overhaul your entire Experience Cloud setup to see results. Most admins I've worked with start small, prove value, then expand. Here's a practical roadmap.

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Step 1: Audit Your Current Experience Cloud Engagement

Start by understanding where you are today. Pull some basic metrics:

• What's your average login frequency per user? Look at your Community analytics.
• Where do customers drop off? Check your funnel metrics for onboarding or key journeys.
• What manual work is your CS team still doing that should be automated? Ask your CSMs where they spend time.
• What questions come up repeatedly in support cases? Run a report on case subjects or Knowledge article searches with no clicks.

These gaps tell you exactly where AI can have immediate impact. If customers are logging in but not progressing, you need better guidance (AI Expert). If your team is manually following up on everything, you need automation (AI Agent). If every customer sees the same thing despite having different needs, you need personalization (AI Builder).

Step 2: Identify Your Highest-Impact Use Case

Don't try to solve everything at once. Pick one area where you'll see measurable improvement in the next 30-60 days:

Onboarding journeys are usually the best starting point if you're dealing with low completion rates or inconsistent time-to-value across customer segments. The data is clear (did they finish or not), and the ROI is obvious (faster activation, better retention).

QBRs and renewals make sense if you have scale challenges. You've got 200 renewals coming up but only have capacity to do QBRs for 30 of them. That's where automation and AI-powered insights help you serve more customers without adding headcount.

Knowledge gaps are the right focus if your support case volume is dominated by questions that should have been self-served. Look at your case data. If 40% of cases are "how do I" questions, AI Expert will directly reduce that load.

Task follow-ups are the priority if your CSMs are drowning in manual work just keeping customers moving. If they're spending more time updating Salesforce and sending nudge emails than they are on strategic work, AI Agent addresses that directly.

Most Experience Cloud admins I talk to start with either AI Builder (to create personalized journeys fast) or AI Agent (to automate follow-ups and engagement). Both integrate directly with your existing Experience Cloud setup and deliver quick wins that justify expanding to the other capabilities.

Step 3: Layer in AI Capabilities as You Scale

Once your first use case is live and showing results, you can expand systematically:

Start by adding AI Expert to surface Knowledge articles and documentation contextually instead of making customers search. Then use AI Studio to build the custom interfaces and dashboards your customers have been requesting. As you get more sophisticated, connect more data sources (your data warehouse, product analytics, support system) to make everything smarter.

All four capabilities integrate directly with Experience Cloud through the same authentication, same data model, same security controls you already have configured. You're building on the foundation you already have, not replacing it or creating parallel systems.

The key is to prove value fast with one focused use case, then expand methodically based on what's working.

The Bottom Line

Salesforce Experience Cloud gives you enterprise-grade infrastructure: secure authentication, flexible data models, mobile-responsive templates, Lightning components, and deep Salesforce integration. That foundation is solid. Thousands of organizations trust it for customer-facing experiences.

EverAfter builds on that foundation by adding the intelligence layer. It makes every interaction personalized based on customer data, automated based on behavioral signals, and contextual based on where each customer is in their journey. The infrastructure stays the same. What changes is that it becomes adaptive instead of static, proactive instead of reactive, and intelligent instead of generic.

Together, they deliver what B2B customers expect in 2025: an experience that understands their goals, adapts to their needs, and guides them to success without requiring constant CSM intervention. Not a portal filled with links. Not a Community feed that's the same for everyone. A living customer experience that evolves with every interaction.

Experience Cloud is the infrastructure. EverAfter is the intelligence. The combination is what lets you scale customer success without scaling headcount.

Ready to See It in Action?

See how EverAfter enhances Experience Cloud

Read the Okta case study

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