Free eBook - how to build data experiences for end users

Deploying and Scaling Analytics That Get Adopted

Organizational data literacy is regularly addressed, but it’s uncommon for product managers to consider users’ data literacy levels when building products. Product managers need to research and recognize their end users' data literacy when building an application with analytic features. Otherwise, it can lead to a low adoption rate and a poor product experience. 

Are applications building for their audience? 
A recent study by Hanover Research surveyed 463 US-based professionals in upper management who work in a digital or analytics software organization. One of their objectives was to discover whether applications are supporting their end users' data literacy level. There was one strong conclusion: Application teams tend to vastly overestimate their end users' data literacy levels.

What role do analytic tools have in end-user data literacy?
Few companies specialize in data discovery or analytics, many product teams turn to analytics tools to fill the gap, and give their users the power of data-driven decision making.

How can Product Managers empower data adoption?
Product managers need to craft a personalized data experience that will provide end users with data literacy. One-size-fits-all dashboards may be an easy solution, but it may lack actionable insights for the end user. Self-service analytics can provide meaningful data for all data literacy levels.