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 […]
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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. This is best paraphrased as “personas
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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
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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
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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
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In this perspective manuscript, my co-authors and I propose an approach of employing personas as an alternative form of making large volumes of online user analytics information useful to end users of the user and customer analytics, with results applicable in software development, business sectors, communication industry, and other domains where understanding online user behavior
In this research, we propose a novel approach for isolating customer segments using online customer data for products that are distributed via online social media platforms. We use non-negative matrix factorization to first identify behavioral customer segments and then to identify demographic customer segments. We employ a methodology for linking the two segments to present
