Customers want faster, smoother, more personalized experiences — so much so that 52% of customers walk away from brands that send messages they find irrelevant. Customers aren’t the only ones who crave better experiences either; marketers are in the mix because they know the importance of capturing their audience’s attention.

To that end, 57% of marketers say using artificial intelligence (AI) is essential for creating 1-to-1 marketing experiences; however, actually delivering these experiences is difficult. More often than not, AI is still seen as the domain of data scientists with extensive training. Without access to these data gurus, many marketers think they must rely on backward-looking analytics, often using manual (or somewhat manual) processes to do things like identifying target audiences or choosing the content and offers they send.

But AI isn’t just for data scientists anymore. By embedding it into the apps and workflows where power users spend their time, Salesforce Einstein is democratizing AI and putting it in the hands of marketers, making things like predicting consumer engagement and campaign planning easier.

Let’s see how one company uses Marketing Cloud Einstein to do just that.


FareCompare creates predictive 1-to-1 journeys with Einstein.


FareCompare provides its customers with the best airfare prices by analyzing historical travel data. However, communicating with travelers across the globe has always been a challenge. Even with personalized emails containing deals specific to subscribers’ locations, FareCompare started seeing higher unsubscribe rates, and the company struggled to engage subscribers with relevant content.

FareCompare executives dug into the data, trying to find patterns that would predict unsubscribes, but they couldn’t pinpoint a solution.

This is where Marketing Cloud Einstein came into the picture. The company discovered which subscribers were most likely to unsubscribe, and then used Einstein Engagement Scoring to suppress those individuals from general marketing campaigns. This enabled the company to do what many marketers have trouble doing: predict how audiences will engage a company, and how best to reach them.

By connecting Einstein Engagement Scoring with its email program to predictively segment its audiences and send personalized content to more receptive audiences, FareCompare saw amazing results, including:

  • 33% return on investment

  • 13% increase in revenue

  • 11% increase in click-through rate

  • 49% decrease in bounce rate

  • 66% decrease in unsubscribes


Introducing Einstein Engagement Scoring from Marketing Cloud.


Einstein Engagement Scoring is an AI-enabled feature that predicts your subscribers’ likelihood to engage with your content across email and web, which helps you remove a lot of the guesswork from audience targeting and content curation decisions.

Today, it answers four main questions for marketers: In the next 14 days, what is the likelihood that my subscribers will...

  1. Open an email?

  2. Click on email content?

  3. Convert on the web?

  4. Stay subscribed to my email list?

Marketers can also get a quick measure of audience health on these metrics by comparing them to industry averages, and by looking at a trend indicator that shows how activity predictions change on a week-to-week basis.

Knowing the likelihood of an audience engaging with certain content or in certain channels before hitting send on an email, mobile message, or ad provides for more streamlined processes and gives marketers a huge boost to refine their marketing strategies.

At a high level, marketers can:

  1. Define segments based on predicted engagement behavior

  2. Target those segments using Marketing Cloud tools and apps (by sending email campaigns, creating score-based decision splits in Journey Builder, using scores as dimensions in Audience Builder, and more)

  3. Determine subscriber list and audience health

To add more context, consider a marketer who’s challenged with engaging dormant — or even lost — customers. Using Einstein Engagement Scoring, this marketer would easily be able to define that key segment (win-back or dormant customers) and send them relevant content (perhaps a short satisfaction survey). The same is true for a marketer who uses Einstein Engagement Scoring to identify the best or most loyal customers, seed a lookalike audience, then extend the company’s reach across social and display advertising.

With more companies competing on customer experience than ever before — 68%, according to the Salesforce “State of Marketing” report — marketers continue to emphasize customer journeys. AI can enhance these journeys. Einstein Engagement Scoring, for example, can use an engagement score as a trigger event for starting a journey. This allows marketers to create more personalized campaigns for specific subscribers and test different messaging for them as well.

And the best part about all of this? It’s turnkey — no services (or data scientists) required. Ready to get started?

Watch our three-minute overview video to see Einstein Engagement Scoring in action, and get in touch today to learn how you can start gaining insight into your audiences with the power of AI.