Personalization Pyramid: Using Generative AI in Marketing Personalization

Introduction: The Intersection of Generative AI and Personalization

As marketers, we all know personalizing messages increases conversion rates. 

Yet, B2B personalization is woefully behind what we see in B2C. In my mind, there are 5 levels of personalization. To get to the top you need to make full use of generative AI for marketing personalization. 

Level 1: Location-Aware Personalization

Let’s start at the bottom. At the base level is location aware. You know a user is in a foreign country. So you localize content to their geography. Or you know a user is in a particular region or country covered by a specific AE. So you send messages from that AE. This type of personalization is table stakes and basic.

Level 2: UI-based Personalization

Up one level is UI-based. As an example, you could adjust the formatting of the content based on the user’s device. So content viewed on a mobile device looks different from that viewed on a desktop. Again, pretty basic. 

Level 3: Identity-driven Personalization

The next level is identity-driven. This is where you greet the lead by their name, you reference their title &/ company. Sadly, this is where most B2B companies are in their personalization journey. 

Level 4: Interest-based AI Personalization

The advent of AI makes the next level of personalization more interesting. It’s what I call interest-based personalization. Here you use AI to scan an individual's social media content to understand their personal likes and dislikes. You do the same with the news about their company to reference key corporate priorities. And then you combine the two to create what feels like a personalized email. Highly effective. I’m seeing a new crop of AI companies today creating products to do this for SDRs. The problem is that these emails while personalized are not personal. See my previous post on the AI B2B Marketing personalization myth. 

Level 5: Generative AI Predictive Personalization

The last level is predictive personalization. This is the future. Just because I like tennis and my company is hiring doesn’t mean (interest-based personalization) that I want your solution. You need to better understand my personal motivations. That’s where the intersection of generative AI and predictive personalization comes into play.

To do this, you can look at my digital behavior. What pages have I viewed on your website? What whitepapers or webinars have I consumed? What actions have I taken in your product? You can compare these actions with the customer journeys of others in a similar situation. What did these customers do next? 

You can then use generative AI to send messages to prospects that are helpful to their buyer journey. It’s the equivalent of ‘because you looked at this, we thought you’d be interested in these pieces of content.’ Netflix and Amazon already do this. Yet B2B companies don’t do this.

Conclusion: Maximizing Impact in B2B Marketing

Improved personalization means better conversions. Improved conversions means more pipeline. And a more (quality) pipeline should translate to more revenue. 

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