Why genAI?

Ad targeting starts with finding the right people. AI has helped marketers do this for years with sophisticated clustering algorithms. These algorithms create segments of people based on certain similarities that indicate their likelihood to respond to an ad. GenAI can make it easier to build these segments on the fly.

How will it create impact?

GenAI can work in tandem with clustering algorithms and predictive AI to let marketers ask for granular segments using a natural language interface. This automates a lot of the statistical analysis required to tease out relevant variables to build new segments or find look-alike audiences. In practice, a marketer without a statistical background can ask for an audience that would be likely to buy a specific product. For instance, they could ask for outdoor enthusiasts to launch new trail running shoes.

GenAI can also help define richer and more numerous personas to help with targeting strategy. With more details on each cluster, advertisers can build messages that will resonate with the clusters and identify channels to reach them.

How easy is it to implement?

Since clustering algorithms have long been a staple for creating segments, it’s a well-developed field with numerous providers that have the statistical chops to adapt to genAI:

• Salesforce’s Customer 360 Truth Profile took 15 billion records and condensed them into 550 segments across 165 activations. Its Einstein AI has added a way for marketers to use natural language to quickly make segments and evaluate segment performance.
• Creative agency Monks used Google Gemini to work with sleep wellness company Hatch to identify three personas for their devices and ways to target them.
• Zeta has added a genAI natural interface to its Marketing Platform that allows it to create dynamic segmentation more easily, something Nationwide has used.

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