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Why create personas without data?

By on Aug 15, 2017

The first rule of persona creation is “use real data.”

Who could disagree with this first rule of persona creation?  We certainly don’t.  We know that personas are archetypes of a user subgroup and that they need to be based on real data so that they represent the needs, desires, and wants of the subgroup of your user population they are meant to represent.

So, why would we suggest creating personas without data?

How could you find yourself in a situation where this is true: You want to conduct research but you don’t know who to recruit for UX research studies.

You have no information on users because you are developing a product that is not only new for the company but also new to the market.

There is no competition so there are no users of similar products from whom to glean information in interviews or site visits for your personas.

We found ourselves in just this situation with a project in which we were going to recruit participants for formative usability studies to inform product design but we had no way to know who the target users would be.

Creating fake personas was the answer

To begin, we took opinions from everyone on the project about who they thought the users would be and we then used these opinions to create fake personas.

Like data driven personas, we gave our personas a name, an age, a job title, a photograph, and a key quote that reflected their lifestyle or aspirations.  We described their pain points and goals, all faked, BUT all with an eye toward thinking how each persona would want to use the product.

With the characteristics of these fake personas at hand, we then created a detailed screener to find participants for our studies.  Our first round of research entailed recruiting four participants from each of eight personas to engage with prototypes of the product in focus groups.

For the focus groups, we created workbooks in which the participants scored individual ratings to reflect

  • interest in the product
  • likelihood to purchase it
  • Identification of who (themselves or others) they thought were the target audience
  • Likelihood to recommend the product to others

In our analysis of the workbooks, we reviewed overall ratings and responses and categorized these by persona.

Source: Moneycrashers.com

Data told the real story of user interest

Based on our analysis of the focus group responses and discussion, it was easy to see who was “in” and who was “out.”  From our original 8 personas, we quickly narrowed the field to four subgroups of users who expressed interest in the product and were motivated to purchase it.

Now we could create 4 personas based on real data. These personas have become the basis for additional recruiting and research.

So, although we got to our personas from the unusual position of starting out with no data, we ended up with personas that we know well because we have learned how they are, as well as who they are not.

Mission accomplished.