Steve will review how AI is impacting on consumer insight now and what the key changes will be over the next few years. He will then talk through some ideas of how that will leave the world of both agencies and clients.

Is AI making us lazy, or can it make us more creative, strengthen our critical thinking skills and also create research experiences that are more real and valid, and save time and money in testing ideas?  I’ll discuss real world tangible applications with examples from real client work including:

Visual storytelling, where I will show how AI turns TikTok/Verbatim/Conversational AI survey data into engaging visual narratives at scale.

Using AI to design a Metaverse research environment. AI enabled more efficient communication and a better end result with a 3D designer.

AI co-creation where we use AI to visualize respondents’ ideas in real time – to enable respondents to build on an idea, with relevant visual prompts.

Rapid prototyping with AI allows for swift creation of realistic models and tools, to test for example  AI-generated virtual shopping assistants or AI based product selectors. This facilitates faster feedback and iterative design and a much more cost effective way to optimise and refine digital designs.

The paper presents data from using Large Language Models (LLM) generated population segment information to generate personas which are then in turn used to generate responses to survey questions. We are able to compare the real world outcomes of tests of numerous products/concepts with those generated by LLM’s such as OpenAi’s GPT and Anthropic’s Claude 2. We found that there was a surprisingly high correlation between the LLM generated answers and the real world data. The paper will discuss these results and other experiments currently in progress. It will also discuss the general concept of persona lead LLM response modelling and its implications for market research.

During the presentation we’ll review techniques in Generative AI and LLMs, and then delve deeper into how these techniques could be applied to understand our real-world complex scenes. The talk will also demonstrate the capabilities of the current systems and the challenges we must still tackle.

Explore the transformative power of AI (machine learning and NLP) in analysing open-ended survey questions in the context of market research. This session will guide you through advanced techniques including Topic Modelling and LLMs, applied to large, multilingual datasets at BBC. Gain practical insights into useful tools like Top2Vec, and understand their strengths and limitations in real-world applications. The talk aims to provide you with actionable knowledge from the trenches to elevate your survey analysis methods.

This pro-bono research project for a US education start-up exemplifies the potential benefits of using an end-to-end AI-assisted hybrid research approach. Join 2CV to hear how AI was used across the whole research process – creating a chatbot survey with conversational AI, using GPT assess the quality of open-ended responses, AI for data capture & thematic analysis, DALL.E2 to generate imagery based on participant verbatim and AI ‘Smart Probing’ which transformed open-ended responses into emotional moments delivering deeper insights than traditional surveys.

MMR is on a mission to uncover emerging technology that can boost consumer engagement and yield improved insights. Presentation reveals results from experiments with effectively integrating AI video avatars into consumer quant research in Europe and Asia.

In today’s rapidly advancing digital landscape, the introduction of innovative Artificial Intelligence (AI) tools holds the promise of unlocking unprecedented insights from quantitative survey data. Yet, the current state of this data may be inadvertently placing the industry at a disadvantage.

At the heart of the challenge lies the format and depth of the exported survey data. Traditional methods, such as CSV or SPSS file exports, capture a snapshot of the responses but often omit crucial contextual information. This context, which includes the order in which questions were asked, the phrasing of the questions, and the overarching theme of the survey, plays a vital role in understanding the nuances behind each response. Without it, we risk a superficial analysis that doesn’t do justice to the respondent’s intent or the survey’s purpose.

AI tools, with their capacity to analyze vast datasets and detect subtle patterns, could revolutionize the way we interpret survey responses. However, their potential remains untapped if they’re fed data stripped of its essential context. An AI can’t intuit the difference between two identically worded questions placed in different sections of a survey or understand the implications of a change in question order. It operates on the data it receives, and if that data lacks depth, the insights generated will be correspondingly shallow.

The industry stands on the cusp of a transformative era where AI could elevate the value derived from surveys. To harness this potential, there’s an urgent need to reevaluate and enhance the way we store and export survey data. By ensuring that data retains its rich context, we position ourselves to glean deeper, more accurate insights, driving informed decision-making in an AIdriven future.

Carl Sagan once noted that in evolution “extinction is the rule, survival is the exception”. Whilst the ‘Terminator’ scenario will remain the stuff of science fiction … AI may well deliver an existential ‘career crisis’. Your job will be lost to someone who knows how to use AI, before it is lost to AI” (Diane Yoon, OpenAI).

AI is going to profoundly change our world and insight professionals following the ‘business as usual’ model need to pivot quickly or be doomed to failure. We need to look beyond our current horizon as the biggest and brightest future will be for those insight professionals who can operate as ‘polymaths’ … able to see the big business picture and join up all the dots.

A number of years ago, we wrote an article entitled ‘If I hear the word paradigm again, I will shoot myself!’, which was expressing frustration about every twist and turn in the development of market research being announced as a new paradigm. But now it really is time to dust down the paradigm word and accept that we are facing a massively disruptive event that has us scrambling to understand its ramifications and over which we may have little control. At this time the end point is difficult to foresee, but the role or even the very existence of the ‘knowledge worker’ is under threat.

As an element of a fourth industrial revolution, the dawning of the age of transformative AI has got an extra kick to it. The previous revolutionary inflection points were essentially about enabling human endeavour. But with transformative AI, we now have a technology that is moving from playing an enabler role to being a substitute for human endeavour. At the moment we are very focused on how to use the new technology to deliver our own work better, faster, cheaper … but this is still looking at AI through an ‘enabler’ lens. We must pinpoint where AI is now likely to be doing most of the heavy lifting and where it will be tricky for it to serve as a substitute for us humans. While there are increasingly those areas where AI will do most of the work, substituting human capability, we also need to identify and develop those areas where only human creativity will suffice. We are focused on how to use AI … rather than how to professionally survive AI.

We must ask ourselves ‘what is our new point of differentiation?’ because yesterday’s skills will now come for free. Our human ‘super-power’ is the ability to comprehend – and importantly, empathise with – the complexity of the human condition and experience, conveying it in a way that businesses can understand and action. In turn, this ‘super-power’ will draw upon 7 ‘Power Skills’ … these are the skills that will differentiate us from what AI can offer, that are most important to dial up because they are.

Debrah Harding, MRS
Lexy Kassan, Databricks
Phil Sutcliffe, Nexxt Intelligence

Chaired by AJ Johnson, COO, Mediaprobe and ASC Board Member

As the conversation grows around how game changing generative AI will be for the world, including the research industry, what do we need to consider in terms of ethics?

Our panelists will offer their expert individual perspectives on AI ethics as an industry regulator, data specialist and commercial research technology provider.

The panel will explore and discuss current hot topics and concerns around AI ethics offering words of caution and giving advice on how our industry can embrace AI whilst retaining good practices.