Improve Performance with Einstein for Marketing Cloud

Learning Objectives

After completing this unit, you’ll be able to:

  • List the Einstein features that help marketers improve their performance.
  • Understand how to include Einstein in your marketing campaigns.

Previously, we discussed how marketers face challenges understanding who their customers are as they engage across a multitude of channels and devices. And these interactions also produce enormous amounts of data, making it increasingly difficult for marketers to understand how customers are engaging, what’s working (or what’s not), and what to do next. 

These challenges with the volume and velocity of data are well-suited for AI to solve, so let’s take a look at some of the Einstein features available today that can help marketers optimize marketing performance and work more productively.

Einstein Social Insights

Social Studio in Marketing Cloud lets marketers publish promotional content to their social accounts, engage in 1-to-1 conversations, and analyze social data. It’s a natural fit for Einstein. Some examples of these AI-powered capabilities inside Social Studio include:

  • Spam detection models: automatically identify and remove known spam sites and posts on social channels.
  • Influencer score: considers a social user’s reach and frequency of engagement on social channels to determine their relative influence in the social sphere.
  • Sentiment analysis: recognizes the tone and sentiment of conversations, empowering marketers to understand the voice of their customer and prioritize responses. For example, in this image, we can see a marketer tuning the sentiment model in Social Studio to better characterize the language used in conversations about the brand as positive or negative.

The Admin console of Social Studio in Marketing Cloud, showing the configurable Sentiment Model along with positively and negatively rated posts.

Savvy marketers can use these advanced features to advance their social strategy and build brand loyalists. For instance:

  1. Run an Influencer Marketing Campaign. Use both the influencer score with social listening around keywords or topics to identify people with high social credibility. Then launch a campaign to recruit them as brand advocates.
  2. Deliver Social Customer Care. Use Social Studio’s sentiment analysis to identify posts with negative brand sentiment. Then create a queue of conversations to triage. When used with the influencer score, marketers can prioritize and route cases to their service counterparts for resolution.

Einstein Vision for Social

Over 3 billion images are uploaded to social channels daily. If marketers can’t parse these images, they’re missing an opportunity to learn about their fans, followers, and customers’ interests.

Einstein Vision for Social unlocks insight and context in images. You can train Social Studio to classify images that relate and represent your brand through deep learning. Einstein Vision for Social can recognize when visual content contains certain:

  • Products/objects
  • Logos
  • Scenes (such as a beach or mountain range)
  • Food

Marketers can combine this new data with other social data to deepen their understanding of brand followers, engage, and measure their marketing efforts.

Einstein Vision for Social, showing a horizontal bar chart of all identified logos across social platforms and a feed with a specific image and brand logo identified.

In this image, Einstein Vision for Social has identified and tracked WOW Air’s logo across social posts to quantify the brand’s social reach.

Einstein CDIM

Since a complete view of the customer is the end goal, solving for customer identity is a top priority. But, with the average customer using 10 channels to communicate with companies, this is harder than ever. 

Einstein Cross-Device Identity Management goes beyond matching on personally identifiable attributes, such as an email address or a phone number. Instead, it uses an algorithm to identify the same person across devices and platforms, considering characteristics such as their IP address, location over time, and purchasing habits. 

Einstein CDIM panel displayed within Audience Studio, showing a comparison between the number of identified people/users based on both deterministic matching and probabilistic matching.

By identifying more people this way, you:

  • Improve the reach and relevance of your marketing ads.
  • Optimize your ad inventory spend.
  • Avoid serving the same person multiple offers across different devices.
  • Sequence ads, at optimal frequency, for consistent messaging and experience across channels.
  • Deliver accurate analytics for segment profiles and campaign conversions.


Lookalike modeling models common traits or behaviors among current customers, then seeks consumers who share those same characteristics. It’s one of the more recognizable implementations of AI. And though it’s not new, it remains a key tool to extend messaging and acquire new customers.

With Einstein lookalikes, marketers can use their first-, second-, and third-party data in Audience Studio to create rich audiences and segments for modeling purposes. It allows marketers to grow their audience based on similarities of the new audience compared to the original audience.

A Lookalikes modeling pop-up within Audience Studio showing an interactive graph where the x-axis equals segment reach and the y-axis equals segment similarity.

Einstein Journey Insights

Consumers control their journey with brands more than ever before. This means marketers understand what those journeys look like in order to meet them along the way.

Einstein Journey Insights starts by tracking all of the interactions customers have across touchpoints such as web or mobile browsing, email, support requests, and so on. Then Einstein applies advanced attribution modeling to improve engagements and event sequences leading to specific goals, such as purchasing or leaving a product review. Plus, interactive reports and visualizations show marketers how their planned journeys performed compared to the organic journeys consumers took themselves.

For instance, if the goal was to get a survey response post-purchase, Journey Insights would identify the optimal number of steps taken to get that response, what type of interactions should be included (i.e., email, direct call from support agent, etc.) and the right order to achieve higher response rates.

The Einstein Journey Insights report, showing the sequences and activities that consumers followed towards completing a sales purchase goal.

Einstein Content Tagging

If you’re out to build engaging and personalized messages for your customers (which we hope you are), then you’ll need a rich library of content from which to build them. The challenge is that keeping those assets accurately tagged and organized is a seemingly never ending task, often resulting in reusing the same content or spending valuable time searching for that perfect image.

With Einstein Content Tagging and image recognition technology, marketers no longer have to manually tag image assets. Instead, Einstein will add and update content tags and metadata automatically, every 24 hours, in addition to any tags you’ve added yourself.

Filtered view of results in Content Builder that include mountains by checking the Einstein generated content tag called “mountain” in filters.This adds more detail about each image asset than can be done by hand and makes finding the right asset infinitely easier so you can get back to creating that perfect message. 

Datorama Einstein Marketing Insights

As marketing budgets grow, so does the pressure to drive ROI, growth, and better customer experiences. Datorama Einstein Marketing Insights provides a pipeline of AI-generated insights using automated regression modelling and statistical analysis methods across your data.

With Einstein Marketing Insights, reveal insights and optimization paths to capitalize on what’s working and adjust  what’s not. Do this at the pace of marketing for improvements to keep your KPIs performing on track.

Einstein Marketing Insights reveals the optimization paths to improve your KPIs and identify high and low performers across channels, campaigns, audiences, regions, and more.

For instance, in this image, Einstein Marketing Insights combs through the data to find high and low performers— identifying attributes such as audiences, creative concepts, and underperforming channels. In this example, Einstein Marketing Insights identified that the combination of the creative concept "Family Video" and audience "24-35," which represents a 17M impressions investment, is performing 60% below norm. The marketer knows now to adjust the campaign with either a new creative or a different audience. Einstein Marketing Insights completes the picture so marketers can make smarter decisions faster. 

Now that you’ve learned about Einstein features that help you understand your data to improve your campaign performance, in the final unit, you’ll look at several Einstein features in Marketing Cloud that create a personalized experience for both individuals and target audiences.


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