Salesforce is ever-expanding its product offerings, and this year, the most fantastic features of the platform are all things artificial intelligence (AI). Have you started exploring capabilities? Are you truly getting the most from the features?
In this post, we’ll cover five ways to make your sales and service reps’ lives easier with AI.
Scenario: Think about your recent transactions as a customer. Perhaps you needed to return an item, check on the status of an order, or get a quick answer about a product. As system administrators, we understand the nuts and bolts behind building workflows to address these interactions, but AI lets us grow — from creating logical decision trees with layered binary decisions, to teaching models how to respond to inputs through the power of machine learning. The cool thing is, Salesforce has been equipped with these capabilities long before AI became a cool buzzword. So, what’s arguably the most straightforward, powerful way to unleash the power of AI to increase customer satisfaction and enhance service agent productivity?
Solution: BOTS! Okay, before you quote me, this is my (very strong) opinion as a former call center rep in a service center. However, the data is agreeable with my opinion. A study published in the Journal of Theoretical and Applied Electronic Commerce Research found that “Human-like chatbots lead to greater satisfaction and trust among customers, leading to greater adoption of the chatbot.” Effective chatbots have also been found to hold a positive relationship with the customer experience. And in a world where the majority of customers expect 24/7 customer service, chatbots offer wait-free assistance while reducing volumes in the queue during quiet hours. Bots significantly boost agent efficiency, enabling the creation of automated, highly personalized responses with minimal human interaction.
Implementing bots shouldn’t require drastic process changes or cause team disruptions. It’s a straightforward win-win, internally and externally, so long as the bots are designed to tackle specific use cases, thoroughly tested, and reviewed with a security lens.
Skills Required:
Beginner Experience Cloud Knowledge
Intermediate Automation (Flow) Knowledge
Intermediate Data Model Knowledge
Intermediate Service Cloud Knowledge
Level of Effort for a Solo Admin: Low to medium, depending on the complexity of your use cases and Salesforce implementation. Budget at least 1-2 weeks building demo bots before deploying “easy” use cases, such as fetching an order status.
Where to Start: First, learn more about the capabilities of Einstein Bots and build a basic bot strategy that returns data about a record, like status, when it’s given a unique identifier, such as a case ID. We recommend listening to this soundtrack for the build process! Once you’ve mastered this use case, it’s time to tackle creating bots that return Article Answers.
Extending Einstein Bot strategy to your knowledge base will lead to increased case deflection, faster resolution, and improved customer satisfaction.
Before we jump into the scenario, let’s highlight something: The same bots that help agents focus on customer experience and impact drive the return on investment (ROI) by ensuring agents never need to spend unwarranted time on a case that requires zero or little human interaction. To avoid chatting (LOL, chatting, get it?) about the same features over and over, we’ll cover a different feature for each section of this blog. Okay, back to our scenario!
Scenario: The year is 2024 and it’s official: If you work with a computer to track customer interactions, there’s a high probability that you’ve copy and pasted, or keyed and re-keyed, the same information into separate forms or systems. You’ve also likely crafted introductory messages and follow-up emails, while double-checking any personalizations to ensure you remembered to change the first name.
Solution: For Service, enable Service Reply Recommendations which is generally available (GA). Einstein for Sales provides sales agents the ability to quickly send personalized, or grounded, correspondence to significantly reduce manual workload.
Level of Effort for a Solo Admin: Medium. Expect to spend at least 2-4 weeks for a minimum viable product, or up to a full quarter implementing various use cases depending on complexity and stakeholder engagement. You’ll learn a sizable amount of net-new AI skills to enable Sales Email with Generative AI, unless you’ve already adopted this capability.
Skills Required:
Beginner Experience Cloud Knowledge
Intermediate Automation (Flow) Knowledge
Intermediate Data Model Knowledge
You will learn Prompt Builder for Sales Emails.
Where to Start:
Enable Einstein Reply Recommendations which helps agents quickly respond to chats without any copy-paste action. Since these replies are identified while training the model, work with your subject matter experts (SMEs) and key agents to identify common responses, and ensure you have a feedback mechanism as responses need updating.
Every Awesome Admin will learn about Prompt Builder to enable and personalize Sales Emails. For best results, ensure prompts follow guidance in the Prompt Builder Pilot Guide.
Scenario: We’ve all received the occasional dreadful, inaccurate email littered with spelling errors and missing information. What’s worse, our favorite colleagues might have sent similar emails to our customers while focused on hastily completing their prospecting touch-points. Yikes!
Solution: Say goodbye to the worry that reps are sending these unfortunate disasters, with Einstein Service Replies for Chat and Email. Soon, reps can focus on interactions that matter and leave decisions like word choice and spelling to the machine. Admins can create prompts that include the most recent data, and make use of merge fields, while keeping data secure.
Einstein Service Replies for Chat and Email uses generative AI to scale customer support, allowing service teams to provide personalized and relevant answers across various channels like email, SMS, live chat, and social media. Einstein Copilot can automatically generate sales emails, draft contractual clauses, and provide recommended steps to close deals quickly, thereby reducing sales cycles.
Then, with Generative AI to Populate Field Values with Prompt Builder (Pilot), gone are the days of sales and service leaders begging their teams to clean up account summaries. Now, admins are able to help sales and service team members stay in sync by creating a prompt to populate a custom field with short summaries of the latest tasks, highest priority cases, big deal alerts, customer sentiment changes, or any relevant integrated data with just a few simple clicks. Talk about Customer 360!
Level of Effort for a Solo Admin: Medium to High. For Service Replies for Email and Generative AI to Populate Field Values with Prompt Builder, the level of effort is higher if prerequisite implementations (described in Where to Start) are not already completed, or if use cases require revisiting prior implementation decisions such as changes to how specific fields are used or what data is collected.
Skills Required:
Beginner Experience Cloud Knowledge
Intermediate Automation (Flow) Knowledge
Intermediate Data Model Knowledge
Intermediate Service Cloud Knowledge
You will learn Prompt Builder.
Where to Start: Enable Einstein Generative AI in Setup, then follow the instructions to implement Einstein Service Replies for Chat and enable Einstein Service Replies.
After enabling for chat, enable Einstein Service Replies for Email which will be more involved. These steps include setting up Salesforce Knowledge, Service AI Grounding. You’ll need to allow public article sharing.
To enable Generative AI to Populate Field Values with Prompt Builder, you’ll need to join the Pilot. Then, create prompt templates which will be used to populate specific fields. Complexity will depend on the business requirement.
As always, refer to the above links to ensure the current availability of these features for your org. If you have questions about your availability or eligibility for Pilots, contact your Account Executive (AE).
Scenario: As a system admin, you want to quickly identify patterns in your conversation data so that you can recommend processes for refinement that will achieve the highest ROI.
Sorry for the agile joke. I had to. But, seriously, as curious admins, how often do we get to look at large sets of data with the sole purpose of identifying patterns? If you answered, “rarely,” you’re not alone. Can you imagine the gifts you would receive from your favorite service agents if you helped them reduce the volume of chat cases coming from a rogue webpage link? Let’s say you learned that the time to close for cases generated via a specific webpage link was 6x longer, and escalation risk equally higher? It might indicate that the page where these cases are generated suffers from incorrect information.
If you’re hoping for an invite to your company’s lavish Sales Kickoff, implement Einstein Lead and Opportunity Scoring. These tools do what it sounds like: they help sales team members identify which leads and opportunities are more likely to convert and close.
Solution: Einstein Conversation Mining + Data Cloud for Service empowers your Service organization to focus on providing excellent customer experiences by identifying trends to address with process changes and updates. Einstein Lead Scoring and Einstein Opportunity Scoring are the starting line for making data-driven decisions in Sales. With Einstein Lead Scoring, reps can focus on leads that are most likely to convert, and with Opportunity Scoring, reps focus on deals likely to close.
Level of Effort for a Solo Admin: Medium to High. For Einstein Conversation Mining, expect to take a few weeks to set up the precursory clouds, Data Cloud and Service Intelligence, if you haven’t already done so. Then, it depends on the complexity of actions you’d like to take when trends are identified. Lead and Opportunity Scoring are extra flexible, allowing up to 100 field filters to score, and the complexity of your use cases will determine the effort required for setup.
Skills Required:
Beginner Experience Cloud Knowledge
Beginner Data Cloud Knowledge
Intermediate Automation (Flow) Knowledge
Intermediate Data Model Knowledge
Intermediate Service Cloud Knowledge
You will learn Prompt Builder for Sales Emails.
Where to Start:
Set up Einstein Conversation Mining (Beta), which will help admins transform conversation data into insights and bot intents to streamline customer-centric, unique Service workflows. HOWEVER, it requires that you set up Data Cloud and Service Intelligence first. Then, you need to have at least 2,500 chat or email messages created in order to set up Einstein Conversation Mining reports, which are the first step in setting up actions. Since there are several steps, here’s the recommended order for successful setup.
To positively impact your company’s Sales org, enable Einstein Lead Scoring. You’ll need at least 1,000 records created and 200 recently converted before Einstein can score them. More considerations are explained in this Help article. Once you’ve enabled Lead Scoring and collected feedback on list views, use your learnings to accelerate enabling Einstein Opportunity Scoring. Since scores should incentivize reps to spend more time on a subset of records within their territories, we recommend thoughtfully planning your rollout to ensure scores are accurate and forecasts aren’t negatively impacted. Another approach may be to enable both Lead and Opportunity Scoring for a subset of end users to review and ensure accuracy.
Note: If you’re using Einstein Account Insights or Einstein Opportunity Insights, be aware that these are scheduled for retirement.
Scenario: Okay, this is bonus content. If we chip away at use cases 1-4 by implementing AI solutions, we should reduce operational costs and streamline the customer experience. Count the number of clicks needed to complete a “happy path” business process in the platform. How successful, or accurate, is the process? What is the process’s impact on the customer experience? What is the impact on the employee experience? Imagine reducing the steps by 30%. Imagine reducing the steps by 95%. Now imagine if the steps were no longer necessary. How much time and money is saved?
Solution: All of the above! It’s estimated that $139 billion will be saved in the next 5 years by implementing AI capabilities for CRM.
If you’re ready to reduce the time spent building applications on the platform, check out Einstein for Flow (Pilot) and Einstein for Developers (Open Beta), which bring generative capabilities to admins who create flows and write code during standard IT processes.
As Salesforce continues to innovate with AI-driven solutions, it’s clear that the platform’s latest features are not just enhancing but revolutionizing the way sales and service teams operate. From transforming customer interactions in Service Cloud with Einstein to streamlining sales processes in Sales Cloud by populating fields via Prompt Builder, AI tools not only improve efficiency and productivity but also reshape customer experiences. By harnessing the power of AI, Salesforce Admins empower their colleagues to make smarter, data-driven decisions, reduce operational costs, and stay ahead in the competitive landscape. The future of CRM is here, and it’s AI-powered by Salesforce.
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