Persona Detection/Segmentation

What Is Persona Detection/Segmentation?

As opposed to customer segmentation which divides the market into groups based on demographics and purchase history, persona detection and segmentation creates more personal profiles in order to better understand potential customers using information about behavior, attitude and personal journeys.

Why Is It Important to Have a Good Persona Detection/Segmentation Model?

Personas are difficult to create as they are based on a lot of information that is not necessarily divulged in interactions with customers or prospects. However, they can prove very important because in many cases, they help to identify which products or services are most likely to interest a potential customer using information like life stage, special interests, and more. The difficulty of creating accurate personas and the potential that they hold make it very important to create a good and dynamic model.

What Internal Data Should I Have for a Good Persona Detection/Segmentation Model?

Using internal data to create user personas and to segment your customers accordingly can be challenging, since your past interactions, sales history, and demographic information will not necessarily accurately reflect your users’ personalities, goals, attitudes, etc. External data will be crucial for a good persona segmentation model but personal information gathered by registration forms and CRM databases can prove useful.

What External Data is Essential for a Good Persona Detection/Segmentation Model?

The best way to analyze people and create personas is to observe their daily behavior, thoughts, and actions. Therefore, social media information is crucial for persona building and segmentation. There is also widely-available software that analyzes and assesses personalities using these social media accounts, such as Watson Personality Insights, MR Simmons Brand Catalyst, and more.

What External Data May Prove Useful for a Good Persona Detection/Segmentation Model?

Surveys and questionnaires could be distributed in order to help create personas and identify concentrations of certain personas within your set of customers and prospects.

What Are the Main Challenges of the Persona Detection/Segmentation Use Case?

A significant challenge for persona segmentation is a lack of data, leading to reliance on stereotypes that can lead to incorrect assumptions about your customers and prospects, even alienating them at times. It is also challenging to correctly segment the personas and fit your marketing strategy and advertising to each persona.

Interesting Case Studies and Blogs to Look Into

Resulticks: Using Machine Learning to Create Persona Segments
Dynamic Yield: Turning Personas into Data-Driven Profiles for Segmentation

Tangible Examples of Impact

Persona Detection shows promise for the fraud detection field, as well.

“Artificial intelligence helps develop different personas based on behavior patterns. The algorithm already knows which persona the user will exhibit, so even if the correct password was typed on the associated device, the system knows when bad actors are featuring a persona that does not belong to the actual user.”

Biometric Update: Behavioral biometrics and persona-based security intelligence as a key fraud prevention layer