How many data-driven personas do companies need?

The profile of the buyer persona is made up of demographic features, character traits, interests and needs - and is representative of an entire customer group. In practice: Each customer group needs its own persona. Basically: All target groups for which you create a data-driven persona should offer the company added value - whether in the form of high turnover, recommendations or loyalty. In short: focus on customer types that contribute to the company's success. The Pareto principle helps to determine how many personas make sense: On average, these should cover around 80 % of your desired customers. The criteria you use to segment customers and assign them to a persona vary depending on the company and its goals. In general, personas can be defined according to the following aspects:

Turnover

If there is a certain customer group that is responsible for a large share of the turnover, it can make sense to segment target groups according to generated turnover: Into A, B and C customers. While A customers of an online shop order regularly for higher sums, C customers buy only rarely and generate a smaller share of the annual turnover. The advantage of this method: Good data-driven personas has an immediate effect on the turnover of your company. The disadvantage: the persona is literally number-based and remains abstract, since, for example, reason for purchase, pain points and motivations take a back seat to sales. Accordingly, it is comparably difficult to develop a "living" persona with this type of segmentation.

Loyalty

Loyal customers - those who regularly buy from you and recommend products and services to others - are the main contributors to a company's success. One or more personas then help to make statements about whether and how your target group changes over time. It also reveals what you can do better in the future - so that more buyers become regular customers. Important: If you create data-driven personas for a loyal customer group, turnover does not necessarily play a role - what is important is that this target group regularly interacts with the company.

Reasons for purchase

One of the most common criteria to segment customers are reasons and pain points that make people buy. Why does the customer choose product X? And how does it help solve problems? Is price, quality or brand image more important to the customer? Questions like these help to orient content and communication even more strongly to the needs of the target group. If the latter differ significantly, it can make sense to re-segment customers and develop several data-driven personas for different buying motives.

Business objectives (B2B)

In the B2B sector in particular, it is important to consider the persona as part of a company. Thus, when developing a B2B buyer person a, the company's goals play a central role when it comes to the buying decision. In practice: Depending on how many B2B customers you work with, a different persona is needed for each company and its vision - unless some companies can be grouped into clusters because, for example, they have the same structures, workflows, product ranges, turnover or employee size or are located in the same industry.

Demography

In terms of demographics, age differences between customers play a role. If target groups belong to different generations, data-driven personas represents the values and needs of this customer group. In addition to age, it is also important to consider the culture of customer groups. If customers of the same generation grew up in different cultures, this has an influence on how they perceive design and advertising, for example. Image motifs and the tonality of texts should also harmonise with the cultural experiences of your customers.