Einstein Messaging Insights

What it does: Uses AI to act as an early warning system that continuously monitors campaign performance metrics and automatically alerts marketing teams when anomalies occur, such as sudden drops in open rates, click-through rates, or unusual delivery patterns.

	Before 2025	What’s New in 2025
Detection	Detected anomalies in email metrics, but often with delays or limited context.	Real-time, AI-powered anomaly detection across opens, clicks, and unsubscribes.
Scope	Focused on individual email sends.	Analyzes both individual emails and entire journeys for holistic insights.
Alerts	Alerts were less centralized and sometimes overlooked.	Centralized, in-app notification system for instant, actionable alerts.
Analysis	Limited drill-down and impact assessment.	Visual “influence” scoring shows anomaly impact; detailed dashboards for analysis.
Tracking	Mostly tracked engagement at send time.	Tracks engagement for several days post-send, capturing late opens/clicks.

Einstein Engagement Frequency

What It Does: Utilizes predictive algorithms to determine the optimal email frequency for each subscriber, preventing email fatigue while maximizing engagement opportunities. The system considers individual engagement patterns and tolerance levels.

Category	Before 2025	What’s New in 2025
Reporting	Basic frequency recommendations; limited reporting options.	Real-time, customizable reporting in Data Cloud, with side-by-side scoring analysis.
Automation	Manual adjustments to send frequency; no journey automation. Earlier versions required marketers to adjust frequency settings manually.	Use EEF scores as triggers in Journey Builder and Flow for automated frequency control.
Integration	Not integrated into campaign planning tools. Legacy Einstein features were mainly standalone (Salesforce Help: Model Card).	Built into Campaign Designer, ensuring optimal frequency from the start.
Platform	Standalone feature, not fully unified with other Einstein tools.	Fully integrated with the Einstein 1 Platform and other AI-driven features.

Einstein Engagement Scoring

What It Does: This predictive AI feature analyzes subscriber behavior patterns to forecast engagement likelihood across opens, clicks, conversions, and retention. The system automatically segments your audience into four distinct personas: Loyalists (highly engaged), Window Shoppers (moderate engagement), Selective Subscribers (selective engagement), and Winback/Dormant (low engagement).

Category	Before 2025	What’s New in 2025
Privacy Adaptation in Scoring Model	Used machine learning to predict likelihood of opens, clicks, and unsubscribes primarily based on historical engagement data.	Continues to use advanced ML, but now incorporates more nuanced metrics (like engagement and unsubscribe rates) due to privacy changes affecting open tracking.
Persona Segmentation	Provided four engagement personas (Loyalist, Window Shopper, Selective Subscriber, Dormant/Winback) for segmentation and targeting.	Enhanced persona-based segmentation including dynamic update of segment membership, and prediction of future behaviours.
Integration	Used in Journey Builder for persona splits and basic pathing; required manual setup for audience targeting.	Now fully integrated with Data Cloud and Flow. Marketers can automate journey paths and campaign flows using Einstein Decision elements based on real-time scores.
Reporting & Insights	Provided dashboards for engagement predictions, but reporting was siloed and often required manual exports for deeper analysis.	New Data Cloud objects allow direct, customizable reporting on Engagement Scoring, enabling side-by-side analysis with other Einstein metrics.
Actionability	Marketers could segment and target based on scores, but automation was limited.	Marketers can now automate campaigns, flows, and journey splits based on real-time engagement scores, optimizing targeting and resource allocation.

Einstein Send Time Optimization (STO)

What It Does: Einstein Send Time Optimization now features enhanced customization capabilities through updates to the underlying data model. After disabling and re-enabling STO, marketers can build custom data graphs to personalize send time predictions based on unique business data.Absolutely! Here is your table with inline hyperlinks embedded within the most relevant words or phrases, referencing official Salesforce documentation and trusted community resources:

Category	Before 2025	What’s New in 2025
Algorithm	Used historical open/click data to predict the best send time for each contact.	Enhanced with real-time behavioral data, cross-channel signals, and adaptive AI models for greater accuracy.
Data Sources	Relied mainly on email engagement history within Marketing Cloud.	Now leverages Salesforce Data Cloud, incorporating web, mobile, and CRM activity for holistic timing.
Granularity	Provided optimal send time at the individual contact level, but updated infrequently (often weekly).	Updates predictions dynamically—sometimes daily—based on the latest engagement signals.
Channels Supported	Primarily supported email campaigns.	Expanded to support email, SMS, push notifications, and multi-channel journeys.
Integration	Required manual selection of STO in Journey Builder or Email Studio.	Can be set as a default for campaigns and journeys, and is available as a decision element in Flow.
Reporting	Offered basic reports on STO performance (e.g., open rates by send time).	Advanced analytics in Data Cloud, with real-time dashboards and A/B test support for STO impact.
Actionability	Marketers had to manually adjust or reconfigure sends to benefit from STO insights.	STO can now automatically adjust send schedules and journey paths, reducing manual intervention.
Privacy/Compliance	Depended on open/click tracking, which became less reliable with privacy changes.	Incorporates a broader set of engagement metrics, making predictions more robust to privacy restrictions.

Einstein Copy Insights

What It Does: Analyzes email subject lines, preheader text, and body copy using natural language processing to predict engagement impact and provide optimization recommendations.

Category	Before 2025	What’s New in 2025
AI Analysis	Basic NLP for subject lines; limited actionable recommendations.	Advanced NLP and generative AI for subject lines and body copy, with real-time suggestions.
Content Creation	Manual drafting and testing of copy.	Instantly generate, test, and refine copy with AI inside Marketing Cloud.
Reporting	Limited tracking of language impact.	Enhanced reporting on how language changes affect engagement and conversions.
Access	Sometimes required add-ons or extra licensing.	Available to all users in a business unit for unified messaging optimization.

Einstein Content Selection

What It Does: Automatically selects and delivers the most relevant content for each subscriber using AI-powered content matching based on past interactions, preferences, and behavioral patterns.

Category	Before 2025	What’s New in 2025
Personalization	Content selection happened at send time, not open time.	Open-time personalization: content is chosen when the email is opened.
Asset Management	Basic asset selection, limited metadata use.	Asset classes, rich metadata, and profile attribute mapping for granular targeting.
Rules	Simple rules, often just frequency caps.	Advanced business rules: exclusions, fatigue, and variety controls.
Analytics	Limited reporting on asset performance.	Real-time analytics dashboard and downloadable reports for creative optimization.
Setup	Required some technical setup.	Fully no-code, self-service setup and management.

Einstein Email & Web Recommendations

What It Does: Provides intelligent product and content recommendations within emails and on websites based on individual behavior patterns, purchase history, and engagement preferences.

Category	Before 2025	What’s New in 2025
Channels	Email and web recommendations managed separately; limited cross-channel sync. See Email Recommendations and Web Recommendations.	Unified, AI-driven recommendations across email, web, and mobile.
Timing	Recommendations set at send time, static for each send.	Open-time recommendations: content updates at the moment of engagement.
Setup	Required developer or IT support for scenario configuration.	No-code scenario setup and management for marketers.
Reporting	Siloed analytics, hard to compare with other metrics.	Integrated with Data Cloud for unified, deep analytics and reporting.
Automation	Manual campaign adjustments based on recommendations. See Campaign Management.	Automated journey and flow adjustments based on real-time engagement.

Customer Journey Mapping with Einstein

What It Does: Maps comprehensive customer journeys, identifies critical touchpoints and conversion paths, enabling targeted campaign development based on journey stage and behavioral triggers.

Category	Before 2025	What’s New in 2025
Journey Design	Manual, drag-and-drop builder; limited AI recommendations.	AI-driven orchestration with predictive analytics and generative AI (Copilot).
Data Integration	Journeys updated on scheduled intervals; limited real-time reaction.	Real-time data integration: journeys adapt instantly to new customer actions.
Predictive Modeling	Basic segmentation and triggers.	Automated journey branches based on predictive models (churn, engagement, etc.).
Visualization	Basic journey maps.	Rich, customizable visualizations and workflow customization.
Cross-Cloud	Limited integration with other Salesforce clouds.	Unified journey management across Sales, Service, and Marketing Clouds.

Churn Prediction with Einstein

What it does: Identifies customers at risk of disengagement or churn using predictive modeling that analyzes engagement patterns, interaction frequency, and behavioral indicators.

Category	Before 2025	What’s New in 2025
Model Building	Required data science expertise or external tools.	No-code, point-and-click model building for custom churn predictions.
Scoring	Periodic, batch churn risk updates.	Real-time, continuous scoring as new data arrives.
Transparency	Limited insight into model drivers.	Clear explanations of which features most influence churn predictions.
Integration	Manual export/import for retention workflows.	Direct integration with Salesforce workflows and automated retention actions.
Alerts & Insights	Basic reporting, no proactive alerts.	Visual dashboards and proactive alerts for high-risk customers.
Model Maintenance	Manual retraining required.	Automatic, continuous model evaluation and retraining.