092 - How to measure data product value from a UX and business lens (and how not to do it)

Today I’m talking about how to measure data product value from a user experience and business lens, and where leaders sometimes get it wrong. Today’s first question was asked at my recent talk at the Data Summit conference where an attendee asked how UX design fits into agile data product development. Additionally, I recently had a subscriber to my Insights mailing list ask about how to measure adoption, utilization, and satisfaction of data products. So, we’ll jump into that juicy topic as well.

Answering these inquiries also got me on a related tangent about the UX challenges associated with abstracting your platform to support multiple, but often theoretical, user needs—and the importance of collaboration to ensure your whole team is operating from the same set of assumptions or definitions about success. I conclude the episode with the concept of “game framing” as a way to conceptualize these ideas at a high level. 

 

Key topics and cues in this episode include: 

• An overview of the questions I received (:45)
• Measuring change once you’ve established a benchmark (7:45) 
• The challenges of working in abstractions (abstracting your platform to facilitate theoretical future user needs) (10:48)
• The value of having shared definitions and understanding the needs of different stakeholders/users/customers (14:36)
• The importance of starting from the “last mile” (19:59)
• The difference between success metrics and progress metrics (24:31)
• How measuring feelings can be critical to measuring success (29:27)
• “Game framing” as a way to understand tracking progress and success (31:22)

Quotes from Today’s Episode

• “Once you’ve got your benchmark in place for a data product, it’s going to be much easier to measure what the change is because you’ll know where you’re starting from.” - Brian (7:45)
  
  
• “When you’re deploying technology that’s supposed to improve people’s lives so that you can get some promise of business value downstream, this is not a generic exercise. You have to go out and do the work to understand the status quo and what the pain is right now from the user's perspective.” - Brian (8:46)
  
  
• “That user perspective—perception even—is all that matters if you want to get to business value. The user experience is the perceived quality, usability, and utility of the data product.” - Brian (13:07)
  
  
• “A data product leader’s job should be to own the problem and not just the delivery of data product features, applications or technology outputs. ” - Brian (26:13)
  
  
• “What are we keeping score of? Different stakeholders are playing different games so it’s really important for the data product team not to impose their scoring system (definition of success) onto the customers, or the users, or the stakeholders.” - Brian (32:05)
  
  
• “We always want to abstract once we have a really good understanding of what people do, as it’s easier to create more user-centered abstractions that will actually answer real data questions later on. ” - Brian (33:34)

Links

• https://designingforanalytics.com/community