Testing innovation ideas - don't always believe what you're told

Qualitative market research is valuable in the early stages of new product development and concept testing, but it can bring with it challenges that requires the skill of researcher in both the fieldwork and analysis phases to navigate what has been said, and how to turn this into recommendations for the client

In this article Bryter's UK MD Seb Martin looks at the challenge of testing new technologies that offer only marginal improvements over existing solutions, and why the researcher should not always believe everything the respondents tell them.

Testing new ideas can be hard. Consumers’ frames of reference are firmly rooted in the here and now, and any innovation put before them is compared against the established status quo. This is also why you typically don’t ask your customers what you should do next when it comes to innovation. You will typically get back an iterated version on what already exists. The classic ‘faster horse’ problem.

However, if you show them something genuinely innovative, there is a risk they can get overly excited and give the researcher a false impression of the potential for a new product. Curved TV is a good example of this. In testing consumers were blown away by the fact a manufacturer had managed to bend a TV screen. The reality of owning a curved TV turned out to be quite different though. A novelty item that didn’t deliver any real benefits to the viewer, and looked weird when mounted on the wall. The learning here is to identify the genuine need (or lack thereof) being served by the technology. Is there something tangible here, or are consumers just being wowed by a cheap magic trick.

But what about when you are testing an innovation that is an incremental improvement on what already exists. This too raises challenges. In cases where the proposition offers a slightly enhanced experience or only addresses only a minor pain point, you can run into the problem of risk vs reward, and consumers can reject something that has genuine utility and longevity.

A good example of this reaction can be found in innovations in banking technology. Over the years over researching innovations in banking and payment system technology, feedback from respondents in qualitative research has followed a similar pattern. They typically reject new ideas that offer only marginal gains but also present a new level of uncertainty in terms of the security of their money. Chip and PIN, contactless payments, mobile wallet. All of them received the same negative feedback in testing. The issue here is that consumers have an established way of doing things that they don’t consider to be problematic, or a pain point that needs solving. So, when they are presented with a solution that offers them a slightly more convenient way of doing the same thing e.g. tap your card rather than insert it and enter your four digit PIN, they don’t think the risk is worth the reward.

Loss aversion is the big bias at play here. Behavioral economics describes how people tend to prefer avoiding losses over acquiring equivalent gains. Essentially, the pain of losing something is often felt more intensely than the pleasure of gaining something of the same value. The same logic applies to an innovation that is felt to offer only a marginal improvement over the status quo, but brings with it a sense of heightened risk, particularly to that most important of things, our money!

The reality is that these technologies come to market, and quickly become adopted by large swathes of the population due to the additional level of convenience they offer, and the realisation that they are not having their money stolen on a routine basis. So how do you factor this into your research and analysis when testing these kinds of innovations? How much of what the respondents say should you take at face value; when they tell you they’d never use such a system because of security fears, should you believe them?

Well, there isn’t an easy answer to this, but this is where a study of the category and a good understanding of human behaviour are both important. Do this in three ways:

1. Look at previous innovations in the category (and elsewhere), and historical patterns of adoption. Have we seen similar incremental innovation in the past, and what was the pattern of adoption. Did consumers adopt and use straight away, was there a delay, did certain consumers adopt quicker than others? In the case of banking and payment technology there is a long history of incremental change to how we make payments, with marginal gains in terms of the efficiency of doing so. This shows that consumers will adopt these solutions over time
2. Understand the audience you are speaking to and their history of adoption and usage of new innovations. Are they early adopters, laggards, or just part of the early/late majority that like to see new solutions bedded in and adopted by others before they jump on board. Make sure that you include a spread of different respondent types in your study to understand what is driving the early adopters but holding back the laggards
3. Have a good working knowledge of some of the most prevalent biases such as loss aversion that could be affecting your results. Use these in your analysis to navigate what is being said, and translate it into what the consumer might actually do and when. Based on this the researcher can make more balanced and contextual recommendations, not just report back what the respondents said in the research.

So, what were the recommendations in relation to banking and payment tech innovations?

• Expect fast adoption by certain groups, some resistance from others at first followed by wider scale adoption as consumers realise their security fears are unfounded.
• Provide reassurance upfront about the security of new systems to help consumers along the path and accelerate adoption.
• Show the use cases and benefits to bring the technology to life and highlight where marginal gains can make an impact in everyday scenarios

Get in touch to find out more about how research and insights can be utilised to test new technology products and services.

Read more about applications of market research and the different qualitative and quantitative techniques available to researchers