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What Are the Top Use Cases for AI in Marketing?
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By: Paul Roetzer

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May 1st, 2019

What Are the Top Use Cases for AI in Marketing?

Editor’s Note: This post originally appeared in the Answering AI editorial section of our newsletter. Subscribe to the newsletter to get exclusive insights and resources twice weekly (usually Tuesday/Thursday), as well as select promotions.

Today’s Question: What are the top use cases for AI in marketing?

Using our AI Score for Marketers assessment tool, we’ve asked hundreds of professionals to rate the value of intelligently automating more than 60 common AI use cases.

All use cases are scored on a 1 - 5 scale (1 = no value; 5 = transformative) based on the same question: “Assuming AI technology could be applied, how valuable would it be for your team to intelligently automate each use case?”

Respondents are guided to consider the potential time and money saved, and the increased probability of achieving business goals.

Here are the top 15 marketing AI use cases, with average rating, according to our analysis of 210 respondents. As you can see, the highest rated use cases were scored between 3 and 4, indicating they are of moderate-to-high value for marketers.

  1. Analyze existing online content for gaps and opportunities. (3.88)
  2. Choose keywords and topic clusters for content optimization. (3.72)
  3. Construct buyer personas based on needs, goals, intent, and behavior. (3.71)
  4. Create data-driven content. (3.70)
  5. Discover insights into top-performing content and campaigns. (3.64)
  6. Measure return on investment (ROI) by channel, campaign, and overall. (3.64)
  7. Adapt audience targeting based on behavior and lookalike analysis. (3.64)
  8. Optimize website content for search engines. (3.55)
  9. Recommend highly targeted content to users in real-time. (3.52)
  10. Assess and evolve creative (e.g. landing pages, email, CTAs) with A/B testing. (3.47)
  11. Deliver individualized content experiences across channels. (3.44)
  12. Define topics and titles for content marketing editorial calendars. (3.43)
  13. Predict content performance before deployment. (3.41)
  14. Forecast campaign results based on predictive analysis. (3.40)
  15. Build media and influencer databases based on interests, audiences and intent. (3.37)

As discussed in a previous Answering AI editorial, quick-win pilot projects with narrowly defined use cases are the best way to get started with AI. Consider if any of these use cases are a priority for your company, and then go find smarter solutions to drive costs down and revenue up.

Have an AI question you want answered in an upcoming newsletter editorial? Submit your questions and feedback to marketing.ai@pr2020.com.

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About Paul Roetzer

Paul Roetzer (@paulroetzer) is founder of PR 20/20, author of The Marketing Performance Blueprint and The Marketing Agency Blueprint, and creator of The Marketing Artificial Intelligence Institute and Marketing Score. Full bio.

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