Persona creation and application deals with creating personas based on data (i.e., data-driven personas) and then applying them in organizational use cases, e.g., marketing a business.
The process typically involves four main steps:
1. data collection — we collect the data about users or customers
2. persona creation — we created personas from this data
3. persona validation — we evaluate said personas and deem them of adequate quality for application
4. persona application — we apply the personas in real use cases
Gen AI cannot help much in data collection, at least directly. Data needs to be original and come from the users/customers.
Gen AI can help in persona creation. Depending on the data, it can be fed into a Gen AI model in various ways as context. Then, with appropriate prompts, personas in desired formats come out.
Gen AI cannot help much in validation, apart from writing code that would help evaluate the statistical properties or validity of the personas. In many cases, feedback from domain experts is needed to validate the personas.
Gen AI can help in application, depending on the use case. For example, “here is information about the target persona: [persona description]. Write an ad that would interest this persona.”
So, the biggest contribution of Gen AI in personas, thus far, seems to be the creation step. In addition, creative ways can be devised to enhance persona application using Gen AI. Finally, Gen AI could support data collection and persona validation indirectly by giving advice or in some other capacity, but it cannot replace the necessary human component in either of these activities.