Trailblazer community - Einstein for Service.pdf

1. Einstein for Service Reduce service costs by driving agent productivity at scale with AI Kamaly Sammandamourthy, Solution Engineer Gerald Ehret Franck, Solution Engineer

2. Thank You

3. Agenda 01. Context and Salesforce value proposition 02. Einstein for Service 03. Demo 04. Customer stories 05. Quizz

4. The Need for Eﬃcient Service has Accelerated Service Costs Customer loyalty Economic Uncertainty

5. Customers Want Quality Service, FAST *Salesforce, State of the Connected Customer, May 2022 83% of customers expect to interact with someone immediately* of customers expect companies to understand their unique needs & expectations* 79%

6. The Importance of Intelligent Service has Increased Tomorrow Today Optimized Service, Faster Resolutions 1 Empowered Agents, Consistent Service 2 Growth Engine, Personalized Engagement 3 Fragmented, Transactional Service 2 Cost Center, Declining Loyalty 3 Growing Case Numbers & Complexity 1 79% expect companies to understand their unique needs & expectations* *2022 Salesforce State of Service Report

7. Source: 2022 Salesforce Customer Success Metrics Survey Einstein for Service Cloud Intelligent service that your customers love - at scale 27% support cost reduction Drive Agent Eﬃciencies Empower agents to do more with less with relevant articles and recommendations Agent Console • Self-Service• Chat Bots for SMS, Chat, WhatsApp, Facebook Messenger Personalize Every Engagement Unify the customer journey so agents can engage empathetically - at scale Agent Console • Next Best Action • Recommendation Builder • CRM Analytics Scale Service Processes Automate simple processes & tasks so teams can focus on the customer experience Agent Console • Case Classiﬁcation, Routing, & Wrap Up • Article & Reply Recommendations • Conversation Mining** In Pilot +175B Predictions processed daily

8. Increase Customer Satisfaction Service & Support Cost Savings Increase Agent Productivity Intelligent Service Delivers Better Experiences and Faster Resolutions 32% 27% increase in customer satisfaction decrease in service & support costs

9. Let Humans Do Human Things Automate simple tasks to control costs and do more with less Supercharge agent productivity with real-time, contextual AI assistance Empower agents to provide personalized service that builds loyalty Scale Agent Customer

10. Only Service Cloud Spans Digital Service, Contact Centers, and Field Service in One Solution High-Touch Low-Touch No-Touch Device & Channel CDP Incidents Knowledge Cases Privacy & Preferences Communities Recommendations & NBA Events, Monitoring & 3rd Party Apps Assets Chatbots Messaging & Chat Self-Service Portals & Help Centers AI and Automation Voice Visual Remote Assistant Field Service Mobile App

11. Drive Efficiency with Built-in AI Triage cases faster with real-time, intelligent recommendations Maximize Every Interaction Combine business rules and AI to surface personalized offers and next best actions in real time Einstein Next Best Action Quickly Triage with Accuracy Automatically classify incoming cases and route them to the right queue faster Einstein Case Classification & Routing Find Answers Fast Surface the most relevant knowledge articles based on the context of the case Einstein Article Recommendations Speed Up Conversation Responses Empower agents with pre-populated responses even as the context of the conversation changes Einstein Reply Recommendations >100B Einstein predictions per day Salesforce Platform (September 2021)

12. Einstein Classiﬁcation Apps Case Classiﬁcation, Routing & Wrap-Up

13. Source: 2022 Salesforce Customer Success Metrics Survey 27% support cost reduction +175B Predictions processed daily Boost Productivity for Agents and Admins Einstein Case Classiﬁcation & Case Routing Intelligently triage cases Classify cases by predicting relevant case details in any language with machine learning Automatically route work in real-time Use your existing routing rules to deliver cases from any channel to the right queue Accelerate time-to-value Intuitive, point and click setup to build predictive model and deploy intelligence in less than a day

14. How Einstein Case Classification Works High case volume Standard and custom fields Ingest feedback & push predictions Build the model monthly Populate recommended fields Requirements Minimum of 1,000 cases in the last 6 months Improved performance with 10,000 cases Non-empty subject & description Available in Lightning & Classic All languages supported ISO, SOC2 & HIPAA compliant Not FedRamp compliant

15. How Einstein Case Classification & Case Routing Works Customer creates a case Einstein predicts case fields in real-time Einstein verifies Prediction Confidence Pre-Select Best Prediction Auto-Triage and Route (Omni) Recommend Top 3 Predictions Meets Threshold Below Threshold Above Threshold

16. Source: 2022 Salesforce Customer Success Metrics Survey 27% support cost reduction +175B Predictions processed daily Einstein Case Classification in Flow Bring automagic to case triage Build workflows based on case fields Use Flow and machine learning to triage cases based on AI-powered recommendations Classify cases at the right time Intelligently reclassify cases based on updates from the agent Build fast with clicks, not code Create workflows with low code tools that make it easy to quickly adjust and scale with changing needs Introducing

17. Source: 2022 Salesforce Customer Success Metrics Survey 27% support cost reduction +175B Predictions processed daily Close Cases Quickly and Consistently Einstein Case Wrap-Up Intelligently predict case field values Leverage machine learning to suggest field values based on closed cases and chat transcripts Increase agent efficiency and field completion Remove the guesswork in completing case fields and improve reporting with accurate case details Easily setup and deploy AI Follow simple, guided steps to configure and build a predictive model, then rollout to agents

18. How It Works: Einstein Case Wrap-Up High live case & chat volume Standard and custom ﬁelds Ingest feedback & push predictions Build the model monthly Populate recommended ﬁelds Requirements Minimum of 400 cases in the last 6 months Improved performance with closed cases that include live chat transcripts Improved performance with case subject and description Available in Lightning All languages supported

19. Einstein Article Recommendations

20. Source: 2022 Salesforce Customer Success Metrics Survey 27% support cost reduction Decrease Time Spent Searching for Answers Einstein Article Recommendations Proactively review incoming cases Leverage machine learning to review case details and text to identify relevant articles Intelligently surface the best article Leverage machine learning to recommend the best article to agents as they work in the console, based on how articles were used on past cases Quickly train and deploy Select the details on cases and knowledge most relevant for your business to train the model within hours and deploy to agents or start with a pre-trained model Included in UE and EE Service Cloud licenses

21. How It Works: Einstein Article Recommendations Knowledge articles Requirements Salesforce Knowledge 100+ knowledge articles Improved performance with 500+ knowledge attaches Available in Lightning only Available in English, Dutch, French, German, Italian, Portuguese, and Spanish Surface recommendations in real-time to agents >500 article attachments on cases = Activate pre-trained model 500+ article attachments on cases = Build org-speciﬁc model

22. Source: 2022 Salesforce Customer Success Metrics Survey 27% support cost reduction Einstein Article Recommendations in Flow Build smart email auto-response workflows Leverage machine learning and Flow to auto-respond to cases with knowledge articles Surface articles at case submission Display relevant, recommended knowledge articles during case submission Build fast with clicks, not code Create workflows with low code tools that make it easy to quickly adjust and scale with changing needs Deflect cases with automagic Introducing

23. Demo - Einstein Case classiﬁcation & Article Recommandation

24. Einstein Reply Recommendations

25. Source: 2022 Salesforce Customer Success Metrics Survey 27% support cost reduction Empower Agents with Responses to Common Questions Einstein Reply Recommendations Build a library of approved responses Leverage deep learning and NLP to create a catalog of common replies based on historic chat transcripts Surface responses to agents in real-time Intelligently recommend the right response based on the context of the chat conversation Assist agents to respond and resolve faster Enable agents to eliminate time spent typing common responses, personalize messages and train model with feedback

26. How It Works: Einstein Reply Recommendations Chat Transcripts Requirements Minimum of 1,000 closed chat transcripts with 4+ chat turns per language Available in Lightning only Build recommendation model Build template generation model Surface recommendations from template library in real-time to agents

27. How It Works: The Agent Experience Einstein Reply Recommendations Agent accepts chat request Customer sends message Based on the chat conversation, Einstein recommends the 3 most-relevant replies Agent edits the recommended reply and personalizes the message before sending to the customer Agent posts the recommended reply and the message is sent to the customer Agent identiﬁes that the recommendation is not helpful and feedback is captured to improve the model Reply Recommendations refresh with every customer message

28. Einstein Reply Recommendations Architecture Included in Service Cloud Einstein Add-on Salesforce Data Center Kleiner/EP on AWS (US/EU/Asia/Australia) 1. Admin conﬁgures Reply Recommendations and triggers model training, which in turns pulls existing Live Chat Transcript records from core DB to Einstein Platform data lake. 2. Recommendation serving model is created as part of training which runs on Kleiner, which uses data pulled into Einstein Platform Data lake. 3. When new chat starts, agents sees recommendations in Einstein Reply Recommendation UI component which uses Serving model running on Kleiner. Reply Recommendations Setup Chat started Data Puller Training/Modeling Reply Recommendation Vectors Einstein Platform Data Lake Quick Text Agent Runtime UI Serving Reply Recommendations Container Reply Recommendations UI component 1 2 3

29. Einstein Next Best Action & Recommendation Builder

30. Source: 2022 Salesforce Customer Success Metrics Survey 27% support cost reduction Recommendations at the Point of Maximum Impact Einstein Next Best Action Unify your sources of insight Combine business rules with powerful predictive models, using Salesforce and non-Salesforce data Surface actionable intelligence Assist employees and customers with personalized recommendations even as the context changes Connect recommendations to automation Enhance business processes with automated workﬂows and triggered actions across systems

31. Bring AI-Powered Recommendations Into Every Workﬂow Improve business outcomes Deploy real-time, personalized recommendations to drive revenue, CSAT, and more Build faster with clicks Create intelligent recommendations quickly using a point-and-click interface Accelerate decision-making Surface actionable recommendations by combining the power of machine learning with Einstein Next Best Action Introducing Einstein Recommendation Builder

32. How It Works: Einstein Next Best Action Deﬁne Recommendations Create Strategies Surface Recommendations Connect to Automation Integrate Sources of Insights Salesforce Data Partner Data Send Email Load Record POST to Service Show Screen Collect Data Update Database Create Marketing Journey Update Case Send Contract

33. Einstein Next Best Action Use Cases Upsell / Cross-Sell Account Info & Data Collection Reservation Modiﬁcations Shipment Inquiries & Actions High Bill Inquiries Technical Troubleshooting Customer Onboarding Applicable across many industries

34. Continuous learning loop enables better personalization Deliver Smarter Recommendations Products Accounts Order History Recommendation Builder (AI) AI-Driven Recommendations Next Best Action Strategy Builder (Business Rules) Workﬂow Automation

35. Demo - Einstein Reply Recommendations & Einstein Next Best Action

36. Service Analytics

37. Source: 2022 Salesforce Customer Success Metrics Survey 27% support cost reduction Optimize AI Performance Service Analytics App Discover insights at a glance Easy-to-use analytics for customer and ﬁeld service Advanced Einstein metrics and take action Prebuilt dashboards Access insights from anywhere Service Analytics Mobile App

38. Customer Stories

39. Zenconnect Achieves Smarter Sales and Service with Einstein AI Challenge: Scaling and maximizing process efficiency due to rapid growth Automating case routing and accelerating case resolution time Increasing productivity with time being a scarce resource Deepening insights into company data and providing predictive analytics Solution: Einstein Case Classification predicts case field values reducing manual entry Einstein Activity Capture detects useful information to accelerate sales cycles Field Service Lightning connects field technicians with real-time data Einstein Discovery aggregates customer service data to predict key figures for execs “Einstein Case Classification reduced time saved per ticket by 25%.” Yohann Lecornet, CTO 3x Increase in case fields completed, now at 95% 25% time saved per ticket SERVICE SALES PLATFORM EINSTEIN

40. Hapag-Lloyd: Improved service worldwide thanks to automation and AI Consolidation and standardization enable customers from over 100 countries to interact more easily Continuous automation and process integration simplify holistic interaction with our customers Salesforce plays key role in customer service optimization Faster resolution of issues worldwide as a basis for a higher-quality customer experience "Salesforce ﬁts perfectly with our quality carrier strategy to put the customer at the center of our processes." Thomas Elling, Global Head of Revenue Management and CRM Higher First case resolutions >100K Cases currently per day - with multiple expansion stage 92% Accuracy in case routing in interaction with Einstein / ERP / FIS SERVICE EINSTEIN AUTOMATION

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