Explore Marketing Use Cases for Artificial Intelligence

Learning Objectives

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

• Identify common use cases for AI.
• Explain how Salesforce Einstein helps business users.
• List the areas where Einstein can assist marketers.

Every brand and marketer will define their marketing use cases and challenges slightly differently based on their industry, whether they are B2C or B2B, the relative size of their organization, and so on. At the end of the day, though, most of these could be summarized in four core pillars that all marketers must strive to achieve in order to meet their customers’ expectations. They must:

• Know everything possible about their customers.
• Personalize every interaction with intelligence.
• Engage across the entire customer journey.
• Analyze results at speed and scale.

Now, keeping this in mind, let’s see how marketers apply artificial intelligence to each of these focus areas. For each, we’ll explore some of the common use cases and the possible AI solutions that can help address them. 

Know Your Customers Better

Use Case	Challenge(s)	How AI Can Help
Create a unified view of each customer across marketing touchpoints.	Resolve identity across multiple devices and disparate channels	Match someone’s actions to their identity based on probability models
Discover previously unknown audience insights and segments.	Audience data sets are too large for normal business intelligence tools	Group data into clusters for analysis and to understand audience or segment overlaps
Collect new data points from customer interactions, content, and conversations.	The volume and velocity of data creates overtaxes typical analysis methods Resources and cost restraints limit more sophisticated analysis	Augment data and attributes through natural language processing and image recognition
Identify where customers are in their journey.	Traditional lead scoring is manual and rules based Assumptions and biases can skew results	Predictive lead scoring

Personalize Every Interaction

Use Case	Challenge(s)	How AI Can Help
Increase engagement across channels with personalized content and offers for each known subscriber.	Create a persistent preference profile across online and offline interactions Content permutations exceed a manual approach	Recommendation engines for content and product offers
Increase online conversion by personalizing content and offers across the open web.	Little data available on anonymous visitors for personalization Create a persistent preference profile across online and offline interactions Provide enough value to win a visitor’s digital hand-raise (e.g., email signup or login)	Group data into clusters for analysis and to understand audience/segment overlaps Recommendation engines for content and product offers
Build customer loyalty with connections to experts, affinity groups, etc.	High volume of inbound questions and requests Staffing costs are too high to meet scale needs Customers expect immediate responses or self-service	Recommendation engines for community knowledge articles, related topics, experts, etc.
Encourage new product discovery for upselling and cross-selling opportunities	Customers don’t know what they don’t know Content and product catalogs contain too many items for customers to sort through manually	Recommendation engines for content and product offers Predictive catalog sorting

Engage More Intelligently

Use Case	Challenge(s)	How AI Can Help
Maximize engagement by optimizing the marketing mix.	Customer channel preference missing or outdated Customers engage across many channels throughout a journey	Predictive scoring and segmentation Predictive attribution and sequencing
Capture customer attention over competitors.	Customers are flooded with communications Time and attention spans are shrinking	Send-time optimization
Improve inquiry and support response.	High volume of inbound questions and requests Staffing costs are too high to meet scale needs Customers expect immediate responses or self-service	Smart bots Automated team routing and prioritization through natural language processing (NLP) and sentiment analysis

Analyze More Effectively

Use Case	Challenge(s)	How AI Can Help
Create a unified view of marketing campaign spend and performance.	Marketing data sets are complex and disjointed Data sources have differing taxonomies or schemas	Probabilistic attribute/field matching Data normalization & harmonization
Measure and optimize marketing campaign spend.	Inconsistencies within data sets Multiple data sources—difficult to surface insights according to optimal combinations of channels Need real-time data and insights	Predictive campaign insights and recommendations
Optimize channel and journey engagement against business goals.	Consumers deviate from marketers’ planned journeys Gaps in cross-channel measurement and attribution	Predictive attribution and sequencing
Identify critical areas for improvement in campaign performance and spend.	Data sets are too large for typical analysis methods Resource and cost restraints limit more sophisticated analysis and insight Analysis needs to be done in real-time	Anomaly Detection Predictive campaign analytics

Meet Salesforce Einstein

Now that you have a sense for the types of use cases that artificial intelligence can help marketers address, it’s time to understand how Salesforce brings that to bear. So let’s meet Einstein.

You may have encountered Salesforce Einstein before. In fact, if you’ve taken the Salesforce Einstein Basics Module, you know all about it. But in case you haven’t, here’s a quick summary:

Salesforce Einstein is Salesforce’s AI brand, and includes all of the intelligent products or services accessible by enterprises and business users. It’s embedded into all Salesforce apps, so every business user can benefit from AI as they work. 

How can Einsten help? Salesforce Einstein: 

• Discovers insights that bring new clarity about your customers.
• Predicts outcomes to make decisions with confidence.
• Recommends the best actions to make the most out of every engagement.
• Automates routine tasks so you can focus on customer success.

Putting it in Context for Marketers

Now that you’re refreshed on Einstein, let’s look at it through the lens of what marketers are trying to achieve and how marketing technology can help.

First, in Unit 3, we explore how Einstein can help marketers be more productive and improve the performance of their marketing programs by providing a better understanding of their customers and surfacing key insights. Then, in the final unit, you learn about the Einstein features that help marketers deliver the personalized interactions that customers expect through improved segmentation and content delivery.

Resources

• Module: Salesforce Einstein Basics
• Module: Marketing Cloud Basics