How much should we be looking behind us to plan ahead?

We have been doing all kinds of cool (and admittedly fun) analysis using AI and have been testing out and using new ways to apply this amazing technology. It’s been great reading, hearing and talking about how AI is empowering us to uncover new and more profound insights into the behaviours and opinions of people and businesses from our research. We’ve recently seen some exciting examples of AI being used in areas such as automated coding and analysis of qualitative and quantitative research outputs and integrating and analysing multiple data streams to generate insights. It’s got us thinking though – while the idea of getting more from what you already have (and getting it faster) is highly appealing, do we risk losing focus on the here and now, and indeed, the future? 

Recent Innovations in AI

Firstly, some more on the recent innovation we’ve seen… Like many agencies, we sit on vast amounts of text, data and content gathered from the numerous studies we’ve run over the years. These could be from one-off or tracking studies; from closed or open-ended responses; and from charts, text, images or videos. We sit on a treasure trove of information which previously we would occasionally dip into in response to a client request (or for our own curiosity), to see if we could unearth a previously hidden insight or learning that could be relevant to the need at hand.

In the recent MRS webinar “AI: Powering Up Consumer Insights”, we learnt how Kokoro have been using AI to codify, tag and analyse a massive tranche of historic data, text and video from an ongoing tracking study. We also learnt how Cambridge Design Partnership is using AI to analyse the massive amounts of usage data generated by sensors embedded in products they are testing, which in turn can be looked at alongside self-reported information from users of those products (e.g. how they felt about their experience of using the product) with the findings developed into personas which can predict how people could behave in the future.

The Limitations of Historical Data

These are great examples of using the power of AI to enhance our understanding of what we already have, and (potentially) using it to predict what could happen in the future. It does pose the question though about how much we can rely on knowing what’s happened in the past to predict what’s going to happen in the future, or to paraphrase the age-old disclaimer seen alongside any financial investment information, is past performance indicative of future results?

The insights industry is very good at testing and validating hypotheses on behalf of its clients through primary research. But elsewhere, we expect to see AI-based tools trained on historic data, being used to provide answers to these hypotheses without consideration of current and future contexts. The great risk here is missing out on the critical factors below which affect how people think and behave, and which highlights how we need to account for different scenarios in our thinking and planning.      

• Category evolution: How has the category or range of categories changed? Tastes change as categories emerge, mature and die, think 3D TVs, digital music downloading or fake meat.     
• Competition, Mergers and Acquisitions: Have new brands entered the market? Are there brands which no longer exist, or which have been acquired by a competitor?
• Regulatory changes: Has the category or vertical been impacted by new regulation, e.g., government enforced changes to wholesale pricing which affect retail pricing, or the way product information has to be shown on packaging or in advertising?
• Reputational changes: Have any brands or prominent individuals suffered reputational damage as a result of an incident, e.g. an oil spill or financial misconduct?  
• National/ International events: Has there been a national or international event which could affect people’s or businesses’ opinions and behaviour more broadly, e.g. military conflict or pandemic?
• Disruptive industries and products: Are there new-to-the-world technologies that are shifting/will shift existing markets substantially and in what timeframe?

The Importance of Fresh Perspectives

We should stress there is great benefit to be had from digging deeper into what we already have; it helps us understand people and businesses better and informs our ideas and hypotheses about what will happen next.  We also have the added benefit of being able to do this faster and more accurately than ever before via the transformational technology that is AI. 

However, we should never forget that people, businesses, categories and markets constantly evolve and it’s our role as researchers to remain curious, be agile and consistently seek the most contemporary and representative view of our buyers, users and audiences that only fresh research can bring.