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Third Wave of AI at Salesforce

Third Wave of AI at Salesforce

The Third Wave of AI at Salesforce: How Agentforce is Transforming the Landscape At Dreamforce 2024, Salesforce unveiled several exciting innovations, with Agentforce taking center stage. This post explores the key changes and enhancements designed to improve efficiency and elevate customer interactions. Introducing Agentforce Agentforce is a customizable AI agent builder that empowers organizations to create and manage autonomous agents for various business tasks. But what exactly is an agent? An agent is akin to a chatbot but goes beyond traditional capabilities. While typical chatbots are restricted to scripted responses and predefined questions, Agentforce agents leverage large language models (LLMs) and generative AI to comprehend customer inquiries contextually. This enables them to make independent decisions, whether processing requests or resolving issues using real-time data from your company’s customer relationship management (CRM) system. The Role of Atlas At the heart of Agentforce’s functionality lies the Atlas reasoning engine, which acts as the operational brain. Unlike standard assistive tools, Atlas is an agentic system with the autonomy to act on behalf of the user. Atlas formulates a plan based on necessary actions and can adjust that plan based on evaluations or new information. When it’s time to engage, Atlas knows which business processes to activate and connects with customers or employees via their preferred channels. This sophisticated approach allows Agentforce to significantly enhance operational efficiency. By automating routine inquiries, it frees up your team to focus on more complex tasks, delivering a smoother experience for both staff and customers. Speed to Value One of Agentforce’s standout features is its emphasis on rapid implementation. Many AI projects can be resource-intensive and take months or even years to launch. However, Agentforce enables quick deployment by leveraging existing Salesforce infrastructure, allowing organizations to implement solutions rapidly and with greater control. Salesforce also offers pre-built Agentforce agents tailored to specific business needs—such as Service Agent, Sales Development Representative Agent, Sales Coach, Personal Shopper Agent, and Campaign Agent—all customizable with the Agent Builder. Agentforce for Service and Sales will be generally available starting October 25, 2024, with certain elements of the Atlas Reasoning Engine rolling out in February 2025. Pricing begins at $2 per conversation, with volume discounts available. Transforming Customer Insights with Data Cloud and Marketing Cloud Dreamforce also highlighted enhancements to Data Cloud, Salesforce’s backbone for all cloud products. The platform now supports processing unstructured data, which constitutes up to 90% of company data often overlooked by traditional reporting systems. With new capabilities for analyzing various unstructured formats—like video, audio, sales demos, customer service calls, and voicemails—businesses can derive valuable insights and make informed decisions across Customer 360. Furthermore, Data Cloud One enables organizations to connect siloed Salesforce instances effortlessly, promoting seamless data sharing through a no-code, point-and-click setup. The newly announced Marketing Cloud Advanced edition serves as the “big sister” to Marketing Cloud Growth, equipping larger marketing teams with enhanced features like Path Experiment, which tests different content strategies across channels, and Einstein Engagement Scoring for deeper insights into customer behavior. Together, these enhancements empower companies to engage customers more meaningfully and measurably across all touchpoints. Empowering the Workforce Through Education Salesforce is committed to making AI accessible for all. They recently announced free instructor-led courses and AI certifications available through 2025, aimed at equipping the Salesforce community with essential AI and data management skills. To support this initiative, Salesforce is establishing AI centers in major cities, starting with London, to provide hands-on training and resources, fostering AI expertise. They also launched a global Agentforce World Tour to promote understanding and adoption of the new capabilities introduced at Dreamforce, featuring repackaged sessions from the conference and opportunities for specialists to answer questions. The Bottom Line What does this mean for businesses? With the rollout of Agentforce, along with enhancements to Data Cloud and Marketing Cloud, organizations can operate more efficiently and connect with customers in more meaningful ways. Coupled with a focus on education through free courses and global outreach, getting on board has never been easier. If you’d like to discuss how we can help your business maximize its potential with Salesforce through data and AI, connect with us and schedule a meeting with our team. Legacy systems can create significant gaps between operations and employee needs, slowing lead processes and resulting in siloed, out-of-sync data that hampers business efficiency. Responding to inquiries within five minutes offers a 75% chance of converting leads into customers, emphasizing the need for rapid, effective marketing responses. Salesforce aims to help customers strengthen relationships, enhance productivity, and boost margins through its premier AI CRM for sales, service, marketing, and commerce, while also achieving these goals internally. Recognizing the complexity of its decade-old processes, including lead assignment across three systems and 2 million lines of custom code, Salesforce took on the role of “customer zero,” leveraging Data Cloud to create a unified view of customers known as the “Customer 360 Truth Profile.” This consolidation of disparate data laid the groundwork for enterprise-wide AI and automation, improving marketing automation and reducing lead time by 98%. As Michael Andrew, SVP of Marketing Decision Science at Salesforce, noted, this initiative enabled the company to provide high-quality leads to its sales team with enriched data and AI scoring while accelerating time to market and enhancing data quality. Embracing Customer Zero “Almost exactly a year ago, we set out with a beginner’s mind to transform our lead automation process with a solution that would send the best leads to the right sales teams within minutes of capturing their data and support us for the next decade,” said Andrew. The initial success metric was “speed to lead,” aiming to reduce the handoff time from 20 minutes to less than one minute. The focus was also on integrating customer and lead data to develop a more comprehensive 360-degree profile for each prospect, enhancing lead assignment and sales rep productivity. Another objective was to boost business agility by cutting the average time to implement assignment changes from four weeks to mere days. Accelerating Success with

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Engagement Frequency Dashboard

Engagement Frequency Dashboard

The Einstein Engagement Frequency Dashboard The Einstein Engagement Frequency Dashboard provides a comprehensive overview of your contacts’ email saturation levels. By analyzing this data, you can understand how your email sending frequency influences engagement metrics like opens, clicks, and unsubscribes over time. The What-If analyzer is a handy tool within the dashboard, allowing you to experiment with different sending frequencies to maximize your On Target saturation levels. Accessing the Dashboard To access the Einstein Engagement Frequency Dashboard: Once on the dashboard, you can click “View Details” at the top to check your data quality scores and get tips on how to improve them. This will give you an idea of how reliable your email or mobile engagement data is. Note on Data Quality If Einstein lacks sufficient data for certain contacts, it will assign frequency scores based on global model data. This can sometimes cause discrepancies between the Einstein Engagement Frequency dashboard and activity-level analytics in specific journeys. What-If Analyzer The What-If Analyzer is a feature on the dashboard that allows you to test different future saturation levels based on varying message frequencies. The goal is to increase the number of contacts in the “On Target” range for engagement. The analyzer provides a bar chart that predicts how adjusting your email frequency can shift contacts from being “Saturated” or “Undersaturated” to “On Target.” This tool helps you fine-tune your communication strategy to optimize engagement across your contact base. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Salesforce Einstein

Use AI to Prep for Meetings

Sales is fundamentally a relationship-oriented endeavor, where representatives invest substantial time delving into lead interests, needs, and behaviors to fortify connections. What if you could Using AI to prep for meetings? Imagine a tool that assumes this responsibility, endowing you with the ability to swiftly acquaint yourself with pertinent information. Here’s what AI can accomplish: it undertakes the arduous research, analyzing both public and CRM data to succinctly encapsulate vital prospect details essential for pre-meeting preparation. If you have specific queries, just pose a question, and AI promptly provides a powered response. Consider this scenario: A sales representative steps in for a colleague on leave, aiming to catch up on major accounts. They leverage Einstein in Sales Cloud, filtering deals with a revenue exceeding $100,000. Many of these deals boast extensive historical data, a formidable amount to sift through. Einstein streamlines the process by presenting deal summaries encompassing crucial information such as involved parties, recent activities, potential risks, and recommended next steps. How to use AI to prep for meetings Einstein goes a step further, flagging an email from a customer with pricing queries awaiting a response. The rep seeks guidance: “What key information should I know about this customer before addressing the email?” Einstein synthesizes the deal in plain language, offering key account details and insights from past meetings to seamlessly resume the conversation. In other words, Einstein answers the reps question – in seconds. Sales Summaries for Sales Cloud becomes the go-to solution for instant meeting preparation, enabling sellers to navigate meetings with agility. Elevate your selling velocity with integrated AI directly in your CRM. Provide each seller with an AI assistant to turbocharge sales across the cycle, automating tasks, expediting decisions, and steering sellers towards swift closures. Einstein 1 allows effortless customization and integration of AI into various workspaces. Here are some key functionalities: 1. Call Summaries & Exploration: Bid farewell to tedious note-flipping. Ask Einstein to synthesize critical call information swiftly, generating concise summaries or identifying pivotal takeaways and customer sentiment from sales calls. 2. Prospect and Account Research: Streamline research on prospects and accounts. Summarize CRM records to gauge deal viability, competitor involvement, and more. Fetch real-time data updates from the news, and direct Einstein to update lead or opportunity records effortlessly. 3. Call Insights: Identify crucial moments from sales conversations. Instantly recognize objections, pricing attitudes, and questions asked without sifting through entire calls. Accelerate deal progression with conversation insights related to opportunities. 4. Relationship Graphs: Discern relationship networks effortlessly. Grasp prospect and customer networks for each deal, with automatic population of contacts and relevant details to fortify relationships with decision-makers. 5. Relationship Insights: Unearth new relationship insights with support from external data. Gain vital context from diverse sources across the web, seamlessly integrated into your CRM, and automatically update existing records with newfound information. Generative AI for Sales: Generative AI employs straightforward prompts to craft copy (e.g., prospecting emails) and provide recommendations (e.g., suggestions for quick-win deals). It analyzes existing sales and customer data to assist in drafting emails and determining messages or resources that would propel a sales conversation forward. Integration into a CRM, the hub of sales and customer data, is the likely destination for these capabilities. And while we’re at it – Real-Time Improvement of Sales Presentations: Crafting compelling presentations demands significant time and effort. Generative AI, activated through text-based prompts in presentation tools, facilitates the creation of customized decks and pitches within minutes. Early versions of real-time coaching are emerging, where AI-based guidance, embedded in video conferencing tools, evaluates live presentations to ensure they address the prospect’s pain points effectively. This advanced system, triggered by specific keywords, can recommend prospect-specific information, transforming your presentation into a tailored and impactful experience. Like Related Posts Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more Salesforce’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more Sales Cloud Einstein Forecasting Salesforce, the global leader in CRM, recently unveiled the next generation of Sales Cloud Einstein, Sales Cloud Einstein Forecasting, incorporating Read more

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Einstein Predicted Email Engagement

Salesforce Einstein Predicted Email Engagement

Access Einstein predicted email engagement data is on the email dashboard, categorizing contacts into personas based on engagement thresholds. Utilize detail pages to dig into prediction specifics and assess your audience health. Einstein Engagement Scoring is a feature that anticipates how a contact will engage with a brand and the likelihood of them making a purchase. This analysis relies on the contact’s email engagement data from the past 90 days, encompassing metrics like the number of emails sent, clicks, opens, etc. Einstein Predictive Email Engagement Scoring Einstein Predictive Email, specifically the Engagement Scoring aspect, foresees consumer engagement with email and MobilePush messaging. Leveraging customer data and machine learning, it creates predictive model. By assigning scores to contacts it indicates their likelihood to engage with emails and interact with push notifications. Salesforce Marketing Cloud introduces the Einstein Split activity in Journey Builder. Thus enabling marketers to target segments based on predicted email engagement scores. Different decision splits, such as Persona Split, Web Conversion Likelihood Split, Click Likelihood Split, Subscription Likelihood Split, and Open Likelihood Split, allow precise targeting based on various engagement factors. Email Engagement The email engagement heat map classifies subscribers into personas based on predicted email engagement: The clickTime Comparison feature illustrates changes in subscriber personas over time, providing insights into messaging resonance. For instance, an increase of 10,000 subscribers may show a 5,000 increase in the Loyalist bucket, with 70% transitioning from the Selective Subscriber persona. To utilize Einstein Engagement Scoring for Persona changes over time, a minimum of 14 days of active subscriber evaluation in each business unit is required. Einstein Engagement Scoring Einstein Engagement Scoring utilizes existing customer data and machine learning capabilities in Marketing Cloud to predict the probability of a contact engaging with marketing content. This is including emails and push messages. The generated scores indicate the likelihood of the contact opening or clicking emails and engaging with push notifications. Like2 Related Posts 50 Advantages of Salesforce Sales Cloud According to the Salesforce 2017 State of Service report, 85% of executives with service oversight identify customer service as a Read more Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more Salesforce’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more

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Marketing Cloud Growth and Advanced Editions

Marketing Cloud Growth and Advanced Editions

While Growth Edition is tailored to small businesses looking to get started with robust marketing automation, Advanced Edition caters to companies that need more sophisticated tools to scale personalization efforts, improve customer engagement, and streamline workflows. It offers additional features, including real-time journey testing, predictive AI for customer scoring, and advanced SMS capabilities, allowing businesses to enhance every touchpoint with their customers.

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