Most of us are aware that technologies such as AI, machine learning, facial recognition, and automated systems are changing our lives. But, when we look around us, we see very few signs of the actual technology. This is what happens when change is done correctly.
For example, speak to your phone and ask it the best route to some specific destination and you unleash a torrent of technologies that would have been science fiction until recently. Your phone interprets your spoken commands, it uses GPS to know where you are at the moment, it accesses stored maps and real-time traffic news, and with that data it iteratively finds an optimum solution for your journey. As you move along the journey, it tracks your position, updates the instructions, and speaks instructions to you. This everyday task is applying AI and machine learning, it is utilising multi-vendor systems, and updating the results in real-time – but it looks and seems very ordinary. This is true of any good use of technology, and it is very apparent in the way that cutting-edge technologies are being applied in the insights process.
The latest GRIT report had a section on the adoption of automation and this showed that agencies are much more aware of the use of cutting edge techniques than end-clients, which is as it should be. Let’s take AI and machine learning as an example, many of the panel companies are using AI and Machine Learning to improve the quality of the data they supply, they are using it to spot fraudulent and duplicate participants. This use of AI, automation and technology is invisible to the agency-based market researcher and is invisible to the end client. The only clue, that one suppler is using it and another isn’t, is in the quality of the data. Similarly, a growing number of companies are providing automatic transcriptions for recorded conversations – especially from video sessions. But, from a user’s point of view, they are not providing ‘automated transcripts’, they are providing ‘transcripts’. In most cases these transcripts are provided to the agency-based researcher, who is then able to better analyse the information (and may use automated text search and analysis tools) to find the story. The end-client, does not see the AI used in the transcription process, not the automated text analytics, they see a better report, produced quicker, and for a lower cost – which is as it should be.
In many ways the relationship between innovation and end clients, is like the relationship between the visible and submerged parts of an iceberg. The visible part is what we see – we may know that the underwater part is larger, but it is the visible part that draws our attention and focus.
Describe the benefits not the features
The message to tech companies selling advanced tech, and the message to agencies using advanced tech, is to focus on the visible part (not the submerged part). Show the client what the benefits are (e.g. better data to the agency, better stories to the end client) – which restates old advice, focus on the benefits, not the features. Rather than say “We have double-helix-optimised-inverted-analytics which works in the following way …:, say “We help you reduce churn and increase lifetime value (and we do it in a time and cost efficient way because of innovations that we are happy to explain to you if you want us to.)
If you are an end-client, don’t fixate on the need to use AI or biometrics, or the latest form of behavioural economics – focus on the problems you need to solve. When a supplier talks about their latest widget, ask them to spell out the benefits to you, and if they start talking just about the features, stop them. One of my preferred questions to suppliers of innovative tech is “What problem do you solve?”. You would be amazed at how many times they either a) do not have a clear idea of the problem their system solves, or b) they are unaware of that there are already solutions to the problem they mention.