The Intelligence Layer: Einstein Discovery, Stories & Models
The Intelligence Layer: Einstein Discovery, Stories & Models
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 intelligent: the intelligence layer, powered by Einstein Discovery. This is where the platform stops merely describing the past and starts predicting the future — and, importantly, explaining itself along the way.
Stories: insights on autopilot
Point Einstein Discovery at a dataset and it produces a 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.
A story typically surfaces:
- Top predictors — the factors most strongly associated with the outcome.
- Top influencers — how specific field values push the result up or down.
- Explanations — human-readable reasons you can trust and share.
The model behind the story
Every story is backed by a 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.
Deploying predictions to score records
A model is only valuable when it touches real work. Deploying a model pushes its predictions onto live records, so that when a user opens an opportunity, case, or account, they see:
- A score — the prediction (a probability, a likely value).
- An explanation — why the score is what it is.
- An action — a recommended next step to improve the outcome.
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.
Monitoring models
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 monitor your models:
- Volume — how many predictions are being made.
- Alerts — flags when something looks off.
- Accuracy over time — is the model still performing, or does it need retraining?
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.
Einstein Discovery for Reports (EDI insights)
Not every insight needs a full CRM Analytics dashboard. Einstein Discovery for Reports — sometimes referred to as EDI insights — brings Einstein's analysis directly onto standard, operational Salesforce reports. You get predictive and descriptive insight layered right onto the reports your team already uses.
The best part: it is 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.
Bringing it together
The intelligence layer completes the platform picture — Einstein Discovery moves through four stages:
- 1
Story
Einstein Discovery auto-generates insights — top predictors, influencers, and explanations — on a dataset.
- 2
Model
The predictive engine behind each story, learned from the patterns in your data.
- 3
Deploy
Push scores, explanations, and recommended actions onto live records, masking the underlying complexity.
- 4
Monitor
Track volume, alerts, and accuracy over time so predictions stay reliable, and retrain when accuracy slips.
Alongside it all, Einstein Discovery for Reports delivers the same intelligence — free with the license — on standard operational Salesforce reports.
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.
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