[{"data":1,"prerenderedAt":330},["ShallowReactive",2],{"navigation":3,"page-\u002Fen\u002Ffoundations\u002Fthe-intelligence-layer":88,"\u002Fen\u002Ffoundations\u002Fthe-intelligence-layer-surround":324,"comments-\u002Fen\u002Ffoundations\u002Fthe-intelligence-layer":329},[4],{"title":5,"path":6,"stem":7,"children":8,"page":87},"En","\u002Fen","en",[9,53],{"title":10,"path":11,"stem":12,"children":13,"icon":52},"CRM Analytics Foundations","\u002Fen\u002Ffoundations","en\u002F1.foundations\u002F1.index",[14,16,20,24,28,32,36,40,44,48],{"title":15,"path":11,"stem":12},"Welcome & Dev Org",{"title":17,"path":18,"stem":19},"Graded Quiz","\u002Fen\u002Ffoundations\u002Fquiz","en\u002F1.foundations\u002F10.quiz",{"title":21,"path":22,"stem":23},"What Is CRM Analytics?","\u002Fen\u002Ffoundations\u002Fwhat-is-crm-analytics","en\u002F1.foundations\u002F2.what-is-crm-analytics",{"title":25,"path":26,"stem":27},"Architecture","\u002Fen\u002Ffoundations\u002Farchitecture-and-data-flow","en\u002F1.foundations\u002F3.architecture-and-data-flow",{"title":29,"path":30,"stem":31},"The Data Layer","\u002Fen\u002Ffoundations\u002Fthe-data-layer","en\u002F1.foundations\u002F4.the-data-layer",{"title":33,"path":34,"stem":35},"The Design Layer","\u002Fen\u002Ffoundations\u002Fthe-design-layer","en\u002F1.foundations\u002F5.the-design-layer",{"title":37,"path":38,"stem":39},"The Intelligence Layer","\u002Fen\u002Ffoundations\u002Fthe-intelligence-layer","en\u002F1.foundations\u002F6.the-intelligence-layer",{"title":41,"path":42,"stem":43},"Hands-On Tour","\u002Fen\u002Ffoundations\u002Fhands-on-tour","en\u002F1.foundations\u002F7.hands-on-tour",{"title":45,"path":46,"stem":47},"Six Adoption Steps","\u002Fen\u002Ffoundations\u002Fsix-steps-and-interview-prep","en\u002F1.foundations\u002F8.six-steps-and-interview-prep",{"title":49,"path":50,"stem":51},"Interview Questions","\u002Fen\u002Ffoundations\u002Finterview-questions","en\u002F1.foundations\u002F9.interview-questions","i-lucide-compass",{"title":54,"path":55,"stem":56,"children":57,"icon":86},"Setup & User Provisioning","\u002Fen\u002Fsetup","en\u002F2.setup\u002F1.index",[58,60,64,68,72,76,80,83],{"title":59,"path":55,"stem":56},"Provisioning Users",{"title":61,"path":62,"stem":63},"Licenses & Permissions","\u002Fen\u002Fsetup\u002Flicenses-and-permission-sets","en\u002F2.setup\u002F2.licenses-and-permission-sets",{"title":65,"path":66,"stem":67},"Integration User","\u002Fen\u002Fsetup\u002Fthe-integration-user","en\u002F2.setup\u002F3.the-integration-user",{"title":69,"path":70,"stem":71},"Security User","\u002Fen\u002Fsetup\u002Fthe-security-user","en\u002F2.setup\u002F4.the-security-user",{"title":73,"path":74,"stem":75},"Analytics Settings","\u002Fen\u002Fsetup\u002Fanalytics-settings","en\u002F2.setup\u002F5.analytics-settings",{"title":77,"path":78,"stem":79},"Hands-On Access","\u002Fen\u002Fsetup\u002Fhands-on-assigning-access","en\u002F2.setup\u002F6.hands-on-assigning-access",{"title":17,"path":81,"stem":82},"\u002Fen\u002Fsetup\u002Fquiz","en\u002F2.setup\u002F7.quiz",{"title":49,"path":84,"stem":85},"\u002Fen\u002Fsetup\u002Finterview-questions","en\u002F2.setup\u002F8.interview-questions","i-lucide-settings-2",false,{"id":89,"title":90,"access":91,"body":92,"description":314,"extension":315,"interview":91,"links":91,"meta":316,"navigation":317,"passScore":91,"path":38,"quiz":91,"seo":318,"stem":39,"video":319,"__hash__":323},"docs\u002Fen\u002F1.foundations\u002F6.the-intelligence-layer.md","The Intelligence Layer: Einstein Discovery, Stories & Models",null,{"type":93,"value":94,"toc":303},"minimark",[95,99,117,122,129,132,154,165,169,176,180,187,209,220,223,227,234,254,257,261,276,283,287,290,294,300],[96,97,90],"h1",{"id":98},"the-intelligence-layer-einstein-discovery-stories-models",[100,101,102,103,107,108,112,113,116],"p",{},"We have moved data in, shaped it into datasets, and designed lenses and dashboards to display it. Now comes the part that makes CRM Analytics genuinely ",[104,105,106],"em",{},"intelligent",": the ",[109,110,111],"strong",{},"intelligence layer",", powered by ",[109,114,115],{},"Einstein Discovery",". This is where the platform stops merely describing the past and starts predicting the future — and, importantly, explaining itself along the way.",[118,119,121],"h2",{"id":120},"stories-insights-on-autopilot","Stories: insights on autopilot",[100,123,124,125,128],{},"Point Einstein Discovery at a dataset and it produces a ",[109,126,127],{},"story"," — an automatically generated analysis of what drives an outcome you care about (won deals, churned customers, resolved cases). You do not write formulas; Einstein does the statistical heavy lifting and hands you plain-language findings.",[100,130,131],{},"A story typically surfaces:",[133,134,135,142,148],"ul",{},[136,137,138,141],"li",{},[109,139,140],{},"Top predictors"," — the factors most strongly associated with the outcome.",[136,143,144,147],{},[109,145,146],{},"Top influencers"," — how specific field values push the result up or down.",[136,149,150,153],{},[109,151,152],{},"Explanations"," — human-readable reasons you can trust and share.",[155,156,158],"tip",{"icon":157},"i-lucide-sparkles",[100,159,160,161,164],{},"A story answers three questions at once: ",[104,162,163],{},"What is going on? Why? And what could improve it?"," All from a dataset you already built.",[118,166,168],{"id":167},"the-model-behind-the-story","The model behind the story",[100,170,171,172,175],{},"Every story is backed by a ",[109,173,174],{},"model"," — the machine-learning engine that learned the patterns in your data. The story is the friendly, explorable surface; the model is the predictive core underneath. When you are happy with a story's quality, you turn its model into something operational.",[118,177,179],{"id":178},"deploying-predictions-to-score-records","Deploying predictions to score records",[100,181,182,183,186],{},"A model is only valuable when it touches real work. ",[109,184,185],{},"Deploying"," a model pushes its predictions onto live records, so that when a user opens an opportunity, case, or account, they see:",[133,188,189,196,203],{},[136,190,191,192,195],{},"A ",[109,193,194],{},"score"," — the prediction (a probability, a likely value).",[136,197,198,199,202],{},"An ",[109,200,201],{},"explanation"," — why the score is what it is.",[136,204,198,205,208],{},[109,206,207],{},"action"," — a recommended next step to improve the outcome.",[210,211,213],"note",{"icon":212},"i-lucide-eye-off",[100,214,215,216,219],{},"Deployment deliberately ",[109,217,218],{},"masks the complexity",". The data scientist's model, features, and math stay behind the curtain. The end user simply sees a clear score, a reason, and a suggested action, right where they work.",[100,221,222],{},"This is the whole philosophy from Lesson 2 made real: intelligence delivered to the CRM end user, understandable and actionable, not locked in a lab.",[118,224,226],{"id":225},"monitoring-models","Monitoring models",[100,228,229,230,233],{},"A deployed model is a living thing, and data drifts over time. Customer behavior changes, markets shift, and a model that was accurate last year can quietly degrade. That is why CRM Analytics lets you ",[109,231,232],{},"monitor"," your models:",[133,235,236,242,248],{},[136,237,238,241],{},[109,239,240],{},"Volume"," — how many predictions are being made.",[136,243,244,247],{},[109,245,246],{},"Alerts"," — flags when something looks off.",[136,249,250,253],{},[109,251,252],{},"Accuracy over time"," — is the model still performing, or does it need retraining?",[100,255,256],{},"Good practice is to keep an eye on these metrics and refresh a model when accuracy slips, so the guidance your users rely on stays trustworthy.",[118,258,260],{"id":259},"einstein-discovery-for-reports-edi-insights","Einstein Discovery for Reports (EDI insights)",[100,262,263,264,267,268,271,272,275],{},"Not every insight needs a full CRM Analytics dashboard. ",[109,265,266],{},"Einstein Discovery for Reports"," — sometimes referred to as ",[109,269,270],{},"EDI insights"," — brings Einstein's analysis directly onto standard, operational ",[109,273,274],{},"Salesforce reports",". You get predictive and descriptive insight layered right onto the reports your team already uses.",[100,277,278,279,282],{},"The best part: it is ",[109,280,281],{},"included free with the CRM Analytics license",". That makes it a low-friction way to introduce augmented analytics to users who live in reports and are not yet ready to jump into a dedicated analytics app.",[118,284,286],{"id":285},"bringing-it-together","Bringing it together",[100,288,289],{},"The intelligence layer completes the platform picture — Einstein Discovery moves through four stages:",[291,292],"lesson-steps",{":items":293},"[{\"title\":\"Story\",\"description\":\"Einstein Discovery auto-generates insights — top predictors, influencers, and explanations — on a dataset.\"},{\"title\":\"Model\",\"description\":\"The predictive engine behind each story, learned from the patterns in your data.\"},{\"title\":\"Deploy\",\"description\":\"Push scores, explanations, and recommended actions onto live records, masking the underlying complexity.\"},{\"title\":\"Monitor\",\"description\":\"Track volume, alerts, and accuracy over time so predictions stay reliable, and retrain when accuracy slips.\"}]",[100,295,296,297,299],{},"Alongside it all, ",[109,298,266],{}," delivers the same intelligence — free with the license — on standard operational Salesforce reports.",[100,301,302],{},"With data, design, and intelligence all covered conceptually, it is time to see it in action. The next lesson is a hands-on tour of Analytics Studio, the Data Manager, and a real story.",{"title":304,"searchDepth":305,"depth":306,"links":307},"",1,2,[308,309,310,311,312,313],{"id":120,"depth":306,"text":121},{"id":167,"depth":306,"text":168},{"id":178,"depth":306,"text":179},{"id":225,"depth":306,"text":226},{"id":259,"depth":306,"text":260},{"id":285,"depth":306,"text":286},"How CRM Analytics adds AI: Einstein Discovery stories reveal top predictors, models score records with explanations and actions, and reports get insights too.","md",{},{"title":37},{"title":90,"description":314},{"id":320,"start":321,"end":322},"aPwndqsmaGk",864,989,"95ALKCHd9X8yae21ZzFCcxylbM-YWsNbuxOQ8kQ0m4M",[325,327],{"title":33,"path":34,"stem":35,"description":326,"children":-1},"The CRM Analytics design layer explained: lenses for quick exploration, dashboards for curated analytics, and apps that group assets and control sharing.",{"title":41,"path":42,"stem":43,"description":328,"children":-1},"A guided CRM Analytics walkthrough: navigate Analytics Studio, explore the Data Manager and jobs, open dashboards and lenses, and read an Einstein Discovery story.",[],1783454189965]