Tuesday, August 6, 2013

Design Thinking: Observing Extreme Users 2

Continuing the learnings from the Design Thinking training, figuring out who will be the extreme users of Bimotics is similar to the hypothesis of our early adopter customers. It is not a stretch to assume that those that are currently measuring and analyzing business would be the the most likely early adopter and positive extreme user.  On the other side of the spectrum, the extreme users that are least likely to use our products are those with either low data quality as poor quality adversely impacts the effectiveness of analytics or hidden agendas that is not supported by the data.

The things I would like to observe from our extreme users that love our product and find value in our features include the categories of analytics that mean most to them.  Are they leveraging topics related to sales and marketing over supply chain and finance?  How are they using the customer flows we designed? To navigate to and from analytics and dashboards, are they taking necessary steps to get around? I have learned from other software entrepreneurs that small business “use copy” and paste more often than using “new” in order to avoid typing in the same information over and over. Finally, I would like to know on what devices they access our application. Our product is mobile enabled; and we have taken care to so that our infrastructure supports mobile.  I would like to know if it was worth it.

Something to observe related to the extreme users who don’t use or even dislike our product, it whether or not they go to their teams and applications and work to improve data quality.  Are there initiatives or trainings that makes their resources input better information?  For those whose agendas don’t have data to support their decisions, I would be very interested in seeing and understanding how communication is done to other team members and whether they get push back from the others with access to the same analytics.  

I’m sure there are other groups of extreme users.  And the identification of extreme users can extend past product users.  For example, those that read this blog would be not segmented by product customer buy rather by prospect or investor.

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