So you have your research, now what?

Creating Actionable Personas

Christian 郑梵力 Ramsey
Business Anthropology

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So you have your research, now what? (A practical synthesis method)

Behavioural mapping + highlights

In my last post I started to highlight a synthesis method we use at ESP Collective ( helloesp.com ) but I started to digress though not temporarily, this is quite typical of me so this will be short and sweet.

Objective: Generate meaningful personas

So you’ve done your research, if you’re like us you used ethnography with a strict anthropological approach to get the most out of your data. SO what is next? How does one sort it?

The next step is taking that DATA and finding meaningful Information and then Knowledge to WISDOM, the DIKW framework allows us to see the innovation/product development process as a non-linear process to take DATA -> INFORMATION -> KNOWLEDGE -> to eventually WISDOM. I see this as going from psychopath to the empathetic mother Teresa. First you have no feelings for the people or often lacking knowledge of even who they are, just a forced business interest. This may seem like a stretch to start at psychopath but think about brands that you feel are calculative and cold, like McDonalds saying eat healthy.. It doesn’t feel authentic but rather… cold and calculating…. Back to the point, we will go from seeing data that may not look related or even have any meaning to you, to begin seeing it as thoughtfully as Mother Teresa. I will focus on those who have already done their first wave of research. [ Ethnographic Research? ]

With all that data and information you have we need to be able to model it so we can use it at an operating level. Personas are a great way to build this operating system.

  1. Comb through the data and pull out all of the behaviours. (Activities, Attitudes, Aptitudes, Motivations, Skills)

2. Map the behaviours mostly in scales on a visual

3. Take each interviewee and map them here (colour code them or tag them)

4. After they are all mapped you’ll want to look at the clusters

5. Create paths through each interview

6. Look at key paths where there are multiple supporting interviews.

(You can increase thickness and lower opacity to be better see the outcomes)

7. Take the key paths and generate personas from them.

Each behaviour on the common paths can be directly pulled out into a persona.

8. From there you can use these very powerful, research backed personas to make key decisions such as key paths through your in store experience, decide on major touch points and channels to invest in), or key interactions that you should design around.

Notes:

I will add a couple of follow articles for optimising this method and where to go from here

If you have anecdotal data from your interviews such as “customers usually use yelp to get here” what you can do is add another person to the map and make it semi-transparent to indicate that it was “said” and not observed, you can use this to look for asymmetries from what people say and do or how a group perceives another group incorrectly. This can also be used to account for an experts given insights that weren’t directly observed.

If you don’t have behaviours for every interview don’t just skip that variable when you create the path. Cut off the path there and start again at the next available variable. Comment here if you can’t understand what this means.

You can also use these gaps to do your second round of research to see the areas you may have missed.

Since you pulled all the behaviours you can also use the list of them to create a mental model and journey map if you have the time. Especially if you are designing a service.

Personas are often used incorrectly as just another way to abstract away from the nuance but you need to embrace the strong diversity and build into it.

This method takes from Alan Cooper’s behavioural mapping in Face 3 with a twist to better find trends.

Christian Ramsey — Business Anthropology @ ESP Collective

www.helloesp.com

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Christian 郑梵力 Ramsey
Business Anthropology

Human-Centred Machine Learning @IDEO, co-author of Applied Deep Learning. Contemplative at San Francisco Zen Center. www.linkedin.com/in/christianramsey