wooden figures representing personas

The growing possibilities of data analytics create new possibilities for customer insights based on data. Is this the end of the classic buyer persona?

What is a data-driven persona?

While buyer personas are usually created in a interdisciplinary workshop of marketing, sales and other customer-related departments with reference to real customer quotes and interviews, data-driven personas – as the name suggests – are created on the basis of customer data. This is not about individual data, but rather data sets that can make statements about specific customer groups and their behavior.

By using artificial intelligence, it is possible to identify commonalities within the mass of existing customer data, for example, those related to customers of certain products or services.

Example:

A chocolate supplier uses data analysis and finds out that young customers buy white chocolate more often than older customers. Further analysis shows that young customers tend to buy smaller quantities more impulsively. Based on this information, a data-driven persona can be created for specific campaigns to sell and recommend white chocolate.

Do data-driven personas replace buyer personas?

What the data-driven persona lacks, of course, are the personal and emotional components that are usually gained through interviews. Data analysis alone can’t determine what motivates the young chocolate fan, what keeps them from buying or what concerns or needs they have throughout their journey.

Although social media profiles can potentially be analyzed (monitoring) to find out more personal details, real customer understanding is usually achieved through direct questioning or exchange with customers and not just their data.

Therefore, a persona created by data analysis can be treated as a helpful supplement or basis for a comprehensive persona.

The advantages of a data-based persona

The data basis provides marketing and sales with a helpful argumentation template for creating personas and working with them. Often, personas are not taken seriously within the company, because they „feel“ too subjective and are not based on „facts“.

Meanwhile, a data-based persona template can be used to develop a customer type that is documented by data. It then can be extended by further persona methods. Marketing and service can use personas strengthened by numbers. They have the additional advantage that they can also carry out turnover-based prioritization. They can for example evaluate, which customer types make more turnover, whether there are seasonal characteristics (e.g. more chocolate sales in Winter), etc. This allows persona campaigns to be much more targeted, sales can be increased and customer groups can be expanded.


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