There’s a nuance, I’ve discovered, in the application of user centered design methods for entering the frontier and emerging markets of the developing world where a significant proportion of economic activity is confusingly labeled “informal”, rather than unformal as the case tends to be.
In more advanced consumer market contexts, where there are umpteen data flows, and decades of consumer research and insights to draw upon, the unquestioned assumption is that user research tends to level the playing field among contenders.
However, this doesn’t hold true, in my experience, in the emerging and frontier markets, such as those in East Africa. Simply basing one’s product development and market entry strategy on even the most rigorously designed user research program does not suffice. At the frontier, competitive advantage boils down to how well you interpret your data so gathered using design ethnography methods and quantitative surveys.
The biggest and best data collection in the world cannot help you if it’s not answering the right questions, nor the insights drive design if there are underlying biases filtering the inputs.
The key, as any trained anthropologist will inform you, is in being able to shift one’s perspective sideways, enough so as to perceive the landscape and the context from the viewpoint of the users being researched. And, perhaps, that is why increasing the diversity of experiences and perspectives of your team can make or break your new product introduction and/or your competitive strategy.
An amusing example of this kind of problem is one I discovered yesterday when poking around my twitter profile after the sudden change in UI that took place without warning. It seems that because I hadn’t input my real gender in the system, Twitter’s data analytics designated me “male” based on my tweeting behaviour.
Their age range is vast enough that they cannot go wrong, and besides, a lady never shares her real age. In the grand scheme of things it doesn’t matter if I’m considered male or female in the system. What is of concern is the underlying assumptions that the designers of the system have made when assigning behavioural choices to one or the other gender.
Now, if we were to extrapolate this relationship between initial design settings in the system, and the inaccurate output – as clear a case of their assumptions being rooted in stereotypes as any that I’ve seen – imagine for a moment what would be the case if the same sort of unthinking, unquestioned stereotypes were applied to the interpretation of user research data collected from a geography or context vastly different from one’s own?
What if this same approach was used for the system of designating assumed behaviours and user needs meant to guide the design of solutions for the rural African market woman?
If the most modern and global social media messaging systems of Twitter are unable to distinguish something as basic as gender – they state based on your profile and activity – they’d do better by stating they are unable to distinguish gender based on these factors than to make gross assumptions on “What do women tweet?” in 20 foot pink letters.
I’d have more respect for them tbh instead of feeling I’ve been put in some fluffy fuschia box, as a woman, just because the stuff I do (my profile is professional) and the stuff I tweet about (business, trade, economics, and design strategy) flags me as a male?
Extrapolating this challenge further, in the context of frontier and emerging markets, where the markets are not crowded with competitors at this early stage, nor is your brand recognized, is this the first impression that you can risk making?
I’ve often said that these are some of the most challenging markets, and affordable connectivity is only making it harder – word of mouth now flies at the speed of silicon, and a new entrant must stand up to social media scrutiny.
Frankly, in my own discipline and field of focus, it only makes me more confident of my team’s ability to offer a distinct competitive advantage.