Personas are humanlike descriptions of customer segments. Just like customer segments, you can use the persona technique to divide your overall market into smaller subset that you can then examine individually.
In practice, the best way of using personas for customer segmentation is to apply a technique of data-driven persona creation, such as automatic persona generation. Using this approach, you can create an arbitrary number of personas from your source data; e.g., 5, 10, 50, or 100 personas.
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Personas and market segments are higly similar in the sense that they both are based on real data about the customers. However, the main difference is that personas individualize that data in a representation that has a name, face, and human attributes. In conclusion:
Personas = humanlike representations of customer groups
Market segments = nameless, faceless descriptions of customer groups
Advertising is often considered to have four main functions: (a) targeting, i.e., selecting whom the marketing messages are sent to, (b) message creation, i.e., copywriting, which referes to creating ads and other marketing communications that are customized for the selected target group(s), (c) channel selection, i.e., deciding which mediums to use in order to reach the target group(s), and (d) reporting, i.e., analyzing the results of an advertising campaign.
When it comes to advertising, personas can help in all of the above advertising functions. For example, you can use personas in targeting, to select the customers who receive your company’s marketing messages. Moreover, personas can also be used for message creation – ideally, personas result in more personal ad copy texts that are resonating well with the target audience that the persona represents. Similarly, by knowing in which channels the persona most spends his or her time, you can choose the appropriate channels for advertising strategy. Finally, you can report the results by persona, e.g., “Mary was the most recipient to our new campaign on Dinner in the Dark products, while David most enjoyed the Flight experience campaign”.
Personas provide alternative to numbers. Therefore, you can use personas to present your online analytics data as people instead of nameless, faceless target groups. This can help decision makers to “get into the shoes” of customers, offering a more immersive understanding of the customers than the “cold”, raw numbers.
When it comes to using personas for marketing, personas are most often used in targeting, i.e., selecting people who are to receive the company’s marketing messages. However, personas can also be used for copywriting – ideally, personas result in more personal ad copy texts that are better resonating with the target audience that the persona represents. Finally, personas can be used for market research, so that you segment the overall market (or customer base) not as nameless, faceless target groups but as personas with names and individualized attributes. This can improve the customer-centric decision making of your company.
Using personas for UX design means considering the needs of the users that the persona represents to design products (e.g., websites) such that their user experience for those users is optimized. For example, a persona can be someone who is technically sophisticated, elderly or has disabilities, which means that the design needs to consider accessibility from the persona’s point of view.
Personas and Scenarios as a Methodology for Information Sciences is an interesting research article that describes the use of personas, along with scenarios, as a methodology common in many domains. The article than makes the case for the use of personas in information science research, which is interesting.
The article presents a quick review of the strengths and weaknesses of personas and also presents a case study of the approach.
I found the article interesting in that data-driven personas, like those developed via APG, can be great research foundations.
Full article: Singh, Vandana. Personas and Scenarios as a Methodology for Information Sciences. Qualitative and Quantitative Methods in Libraries, 7(1), 123-134. Available at: .