It is never enough for a tech innovator to have a good idea. Innovations must go through the test of market research to ensure that they are well-received by target users. However, there is a pressing need for research to probe intersectional factors, so that resulting tech innovations can solve problems for a wide range of users.

Probing the market

Innovation research involves probing to understanding the problem space, needs and opportunities before one can come up with solutions. Research allows innovators to probe the market to determine whether or not an innovation is worth deploying on a larger scale:

  • Does the proposed product/solution already exist? Did it succeed or not, and if it didn’t, what lessons can you learn from that failure?
  • Does the product/solution solve a real problem for a large enough market?
  • What is the perceived market and how large is it?
  • Do potential customers understand the innovation and do they value it?
  • How much are they willing to pay for it? Is there a real revenue opportunity?

 and  offer more examples of questions that can guide market research around an innovation. The answers to these questions allow tech innovators to set clear research goals, identify gaps in the market and create bespoke, proprietary products or solutions. The answers to these questions might also highlight opportunities for collaborations.

Intersectional analysis

These questions, though valid, assume a certain homogeneity in target customer groups. To be considered complete, research must integrate sex, gender, race, culture geography, quality or even availability of internet, language etc and  at every stage. The failure to probe the market at this level can result in, for example, digital maternal health technologies and programmes in Sub-Saharan Africa that exclude the very women who need them. ()

Ongoing research by Qhala reveals that many digital platforms that provide opportunities for gig work are seldom created to meet the unique needs of women, who tend to be disproportionately affected by security risks inherent in some platform work, such as delivery work, and who can find themselves being paid less than men. Digital platforms may also not be designed to meet the needs of physically impaired users, who have to depend on friends and family to effectively use the platforms.

Computer facial recognition features trained on biased datasets may not recognise women, darker skinned persons and non-conforming people as well as they might white male faces. ()

Research is key to creating innovations that respond to real needs. However, that research must ask the right questions. The lack of research that takes into consideration intersectional factors remains largely unexamined and uninterrogated by tech innovators. As a consequence, the inequalities that exist in the non-digital world are simply replicated, even amplified, in digital innovation. This is to the detriment of tech users, who are supposedly, the focus of tech innovation. However, complete research, that includes intersectional analysis at every stage, can result in innovations that are inclusive and that stand a better chance of being commercially successful.