Concept testing is common practice across the market research world and has been around for several decades. In recent years, there’s been a surge in innovation in this area, and those innovations have focussed predominantly on two elements:
Measures like Purchase Intent (PI), Net Promoter Score (NPS) and top-two-box attribute scores have historically been used to predict the potential success of a product in the market to such an extent that they have been institutionalized into norms and benchmarking. Innovation in this area was necessary as it has been proven that these measures alone have limited predictability of actual market success, where 8 of 10 products fail within 2 years. Newer measures and techniques like willingness to pay, wisdom of the crowd, latency testing and a host of other (partial) behavioral measures have proven to be able to make stronger predictions on future market success.
The second frontier has been centered around market research automation. A variety of market research technology platforms have arisen that automate many of the processes that previously were tedious and time consuming. This includes everything from fieldwork and analysis to even reporting. These advances have resulted in shorter delivery times and significant cost savings, but have fundamentally kept the same status quo Key Performance Indicators (KPIs) such as PI and NPS as key decision making measures.
Yet even with these advances the number of successfully launched products has not subsequently increased. If anything, it has gotten harder and harder to introduce and maintain a successful product these days. Why is that? Why in spite of advances in methods and automation have we not solved the inherent problems with traditional concept testing and made it better?
Need for innovation on process
The truth is that creating a new product is a long process. It starts with a consumer need or a technical breakthrough. It requires a deep understanding of needs, habits, landscape, time and many other factors. The validation, which is what the far majority of concept tests focus on, is the final part of this long innovation process. If the outcome of the concept test is merely a measure of strength (or worse; a “go” or “no go” check), the concept test then adds very little value. Even though it is predictable, affordable and fast.
What is needed is a concept test that does not merely focus on predicting market success, but a test that uncovers WHY the concept’s success was achieved: Why do consumers like the concept? What elements work? What elements can and must be improved?
Answering these questions during the innovation and development process will provide the actionable insights needed to make the concept stronger, hence adding direct value. Having the ability to test earlier in the process and to apply the learnings directly onto the concept builds an iterative improvement process and thereby elevates the final result.
If a concept test is able to answer these broader optimization types of questions, it has the potential to directly contribute to the innovation success of a company and subsequently streamline their innovation process.
In this presentation, we cover how some of the new technologies can be used to develop insights for innovation and brand building.