Great products come from a deep understanding of customers’ needs and wants. Such understanding is best formed by observation of customers using a product. Hence, the proverbial chicken/egg situation – a product that has not yet been developed cannot be observed.
One way to deal with this challenge is to start by identifying a “job” the customers of your future product needs to do. As Theodore Levitt observed,
“People don’t want to buy a quarter-inch drill; they want a quarter-inch hole.”
Therefore, a savvy product marketing professional can observe people doing the job with whatever tools (i.e. products) are available to them currently. A keen observation will likely reveal an opportunity for improving the customer’s job, i.e. simplifying the customer’s experience of obtaining the desired outcome. This approach is championed by Clayton Christensen in his book The innovator’s solution: creating and sustaining successful growth.
Observing customers in the process of using products is not a new concept, and it is known as ethnographic research. However, it is primarily used for learning how to enhance existing products, not to improve customer job experience. The cost of ethnographic research is very high and that forces very limited scope and data samples which would be unlikely to help discover a market segment deficiency of unmet customer needs. That ocean is too big to boil by means of ethnographic research.
The latest developments in big data and opinion mining technologies, combined with growing availability of customer experience testaments available online, offer new opportunities for uncovering unmet customer needs on a market scale. However, there are no widely accepted methodologies available to take advantage of these developments just yet.
The remaining challenges involve:
- A market segmentation approach that identifies a job by expanding the view of competition from the products on the same shelf to any product or service that customers could deploy to get this job done. Traditional segmentation methods are based on the assumption that your customers are defined by the demographic group they belong to. Some use a secondary qualifier of buyer persona to refine the target segments. These methods worked reasonably well in the age of mass markets and clever advertising campaigns, before the rise of the social customer. Today we do have the data and tools enabling us to learn who are the customers that purchased products like this and how they experienced them. We can even map them back to the demographics and persona profiles which can provide much better understanding of their real needs.
- Rigorous data governance methodology is focused on real customers and real communications. Higher volume and velocity of data does not translate directly into market intelligence that is capable of driving business decisions. It often creates even more noise at greater expense and results that are not relevant to business reality. We have to discriminate between endless repetition of mindless remarks by ambiguous digital entities and unique descriptions of real customers’ experiences with specific products or services. We should re-focus from inclusivity of content data sources to exclusivity of authentic content.