Building User Persona’s from Multiple Data Sources

By now, your business should be collecting data from multiple sources about your customers – web, social media, POS system, etc. The problem is going to be that combining these sources together to create users personas about your customers isn’t always simple. Not to mention the fact that you might not have the resources or personnel to do so. With that in mind, building user personas is quite simple, and when done so correctly, the output will easily translate into the rest of your business.

What is a user persona? It’s data about a group of users that share similar traits based on particular metrics. Let’s break that down a little more to say that a user persona can be created for every data point that you gather for your business. You can develop individual personas for social media users versus website users, or customers that bought Product A versus those that bought Product B. It’s really up to you, but it starts by asking questions and then deploying the right applications to collect data.

Website data and social media data are two really easy sets to combine. You can take the analytics provided through social media (Facebook, Twitter) and use that as a base to match up your website data. Facebook, for example, provides gender and age information. That is a good start for a user persona, and that is also data that can be pulled out of Google Analytics. By validating the two against one another, you can start to categorize users by those two metrics alone.

Let’s say we have a high number of females that like us on Facebook. The two top age ranges are 18 – 24 and 25 – 34. I can look at my posts on Facebook and just analyze that audience to see which ones that they interacted with the most. I can then create a segment in Google Analytics that only looks at those two age groups that are female and then analyze all the pages they interact with. I would look at the Time on Page metric to determine what pages were most relevant, validating it by the highest time. If I wanted to take it a step further, and I have a conversion in place, let’s say a Newsletter signup, I can see how many converted and from what pages or let’s say I wanted to see how many from this segment actually bought a product I can this here as well.

My user persona looks something like this:

Female Audience #1

  • Age 18 – 34
  • Location: Upstate New York
  • Income: $35,000 – $60,000 (pulled from market analysis in most cases)
  • Device type: mobile phone, Apple iPhone
  • Facebook content – posts about using Product A, images of Product A, testimonies by females
  • Website content – Product A page, Product A blog on how-to, Product A ingredient statement
  • Converts 30% of the time to newsletter
  • Referral sources include Facebook and “Product A use” search term on Google
  • Higher conversion with coupon code

*NOTE: Most businesses actually give user personas names and personality traits. You can create your personas however you want to!

If I wanted to run a program that increased Newsletter signups by females in that age range, I can use the data I already have collected to write new content pieces that I publish to Facebook and lead into my website. Although this is a more manual process, by doing it this way I start to lean more about my audience, and if I am the person putting the advertising program together, it really benefits me to be looking at everything.

The first question that you should ask about your data is what am I looking to improve by collecting this data? From there, you can start to ask additional questions that break down into persona data.