How to Build Profitable Products that users like to Use 

By Suraj Venkat

User researchers are often concerned with expertise, why are some users expert users of a product while others are intermediate or beginners, even after similar temporal usage patterns? 

To drive adoption of a product we need to factor in the expertise of the target user group and design the product such that it matches the target user group's expertise level as well as expected use cases. For instance it makes no sense to build drag and drop developer tools for advanced software engineers wanting to build complex software. While such a tool may be enjoyed by them for simple tasks, it would cost a lot of development time for the builders of the tool to provide sufficient functionality to the users and even then may not provide the users the level of customization and control that they desire from a developer tool. Any novel interactions may be appreciated by the users if the user draws some benefits from learning the interaction such as saving time in performing a particular task. This user group being in the advanced portion of the users' universe may be open to adopting newer interactions.

Whereas for instance building consumer apps for older people in the age group of 50+ has to factor in how many years of experience with technology this target group possesses. This particular user group needs apps that are intuitive and very similar to apps that they are habituated to. Introducing novel or complex UX interactions may not be a smart manoeuvre here as their expertise is closer to novice, in general.

Scientific Considerations

The brain is responsible for human behavior but it is also shaped and modified by the behaviors it produces.

The study – Robert J Zatorre, R Douglas Fields & Heidi Johansen- Berg(2012),”Plasticity in gray and white: neuroimaging changes in brain structure during learning”. In Nat. Neurosci., 15 (2012), pp. 528–536 reviews human neuroimaging findings of structural plasticity and then discusses cellular and molecular level changes that could underlie observed imaging effects.

An early longitudinal MRI used voxel based morphometry to demonstrate that gray matter density in the visual motion area undergoes changes in as little as 7 days and white matter changes through fractional anisotropy, for people learning to juggle.

Hence, understanding a user persona's previous experiences or the kinds of products that they already use can be a great starting point in building effective products that get adopted by these users thus leading to profitability.