Survey results have just become even more meaningful, as Pollfish is using advanced data science and algorithms to give your even more insights about your survey data and the users who responded with the Personas section.

We are building one of the most advanced machine learning models on the planet - using behavioral data and active survey responses to determine and validate user profiles. The data derives from a process of machine learning, using anonymous metadata from the mobile, like device type, installed app categories, GPS etc. 

The personas are of 6 types:

1. The bookworm: A user that is regularly using their mobile phone to read books, news or magazines.
2. The Traveler: A user that is regularly using their mobile phone to explore places or organize trips.
3. The music fan: A user that is regularly using their mobile phone to listen to music.
4. The socialite: A user that is regularly using their mobile phone to socialize or communicate with other people.
5. The sports fan: A user that is regularly using their mobile phone to do sports or stay fit.
6. The Productivity Booster: A user that is regularly using their mobile phone to boost daily productivity.

The chart we provide represents the alignment of the survey respondents in your survey results to the personas. As you select/deselect age, gender, location criteria, you will see changes in the alignment of those personas - in real time!
A person can easily fit multiple profiles if they are exhibiting characteristics of those categories (e.g. a Music fan can also be a Bookworm).

This data will provide you more insights on the behavior and preferences of the users in your survey, which will help you make better decisions by providing even deeper insights - and this in only available on the Pollfish platform. You can see an example with sample results here: https://www.pollfish.com/dashboard/results/10578/1557829979

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