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As AI and machine learning become entrenched in market research, delivering large scale insight that provides the ‘why’ as well as the ‘what’ is increasingly economical, speedy and desirable.

As AI and machine learning become entrenched in market research, delivering large scale insight that provides the ‘why’ as well as the ‘what’ is increasingly economical, speedy and desirable.

Hear how HSBC, Chivas Brothers, Colgate Palmolive, Diageo, Cambridge University Press and others are bridging the gap between qual and quant by commissioning Big Qual methodologies to gain rich, personalised insight at scale.

Book your ticket to:

  • Examine Big Qual methodologies that enable researchers to go large but stay personal
  • Gain new tools for your Big Qual toolkit
  • Glean qualitative insights from multiple sources of unstructured data
  • Examine the fusion of AI and ML with qual to extend the breadth of insight
  • Discuss the intersection of qual and quant methodologies and what this means for insight teams
No Biography Available

09.45 Welcome by the Chair
Caroline Hayter, Co-founder, Acacia Avenue

 09.55 Big and personal?
This session will debate the merits and pitfalls of big qual.  What is it, how can it be used, when big qual becomes quant and whether this really matters.
Chair: Caroline Hayter, Co-founder, Acacia Avenue
Andy Dexter, Managing Director, Signoi
Louise Horner, Research Director, Acacia Avenue
Gill Ereaut, Consultant, Linguistic Landscapes

10.35 Gathering insight from always-on conversations with customers
The Cambridge Panel is an exclusive online research community of those in international education. Thousands of opinions shared in forums, interviews, and discussions generate a vast amount of qualitative insight which informs future product development.
During the pandemic, the Panel became the go to place for many for peer-to-peer support and to a certain extent Cambridge University press’ Big Qual has become the community’s Big Qual too. Hear how to build, manage and cultivate a hotbed of qualitative insights.
Rob Hardy, Head Of Insight, Cambridge University Press

11.05 Morning comfort break

11.25 Building from the ground Up: How Colgate Palmolive used AI based ‘qual at scale’ to create a new foundation for the home care category
Colgate Palmolive wanted a more human-driven understanding of the world of home care & surface cleaning across markets in France, Italy, Germany & Poland. In response, delivered qual at quant scale, using its NeedDriver Mapping methodology to create segments rooted in natural conversations happening online, building from the ‘ground up’ using qualitative data. The team begun with 259k online quotes from over 500 consumer, brand and expert blogs/ websites/ forums to create 6 segments.
The project has received great traction within Colgate Palmolive and has influenced the rethinking of portfolio pillars. It is the foundation of the cleaners’ growth strategy and of the storytelling with commercial partners.
Foivos Dousos, Associate Director
Xavier Vaissière, Growth Insights Manager –  Personal Care, Home Care & Agile tools, Colgate Palmolive Europe


11.55 Message received! Can an award-winning WhatsApp approach help brands think bigger?
Jigsaw has integrated WhatsApp into its Whycatcher research platform, enabling qual at scale via the world’s most popular messaging service.
This session will draw upon recent case studies to offer some useful tips about using WhatsApp for big qual. Hear a roadmap to use WhatsApp to deliver qual at scale, including the first principles, key dos and don’ts and useful applications.
Alex Johnston, Director, Jigsaw
Matthew Bishop, Communities Manager, Jigsaw

12.25 Lunch

13.15 Following the #Covid conversation: building a toolkit to access, analyse, and visualise Big Qual databases 
There are few realms of unstructured data larger than Twitter’s database. How would anyone unpick such a vast database, and present meaningful insights?  Bayes Price & Red Centre Software have tracked the #Covid conversation since day 1 of the pandemic; gathering 200 tweets every 5 minutes via Twitter’s free API.  
In this session hear how any Big Qual researcher can maximise classic MR skills to; gather, convert and code Twitter data; use NRC Lexicon, Suyzhet and ML models to analyse text and emojis; add context, visualise and share insights via interactive Tableau and dynamic PPTX. 
Matt Gibbs, Managing Director, Bayes Price

13.45 Ethnography at scale: using visual user generated content to deliver qualitative insights
EVA is Kantar’s unique AI-powered social imaging tool, that can gather and cluster visual user generated content from platforms such as Instagram and Weibo, providing a rich understanding of what people are sharing about their lives, categories and brands - think of it as ethnography at scale.
In this session Chivas Regal and Kantar will share how they gained a deep, understanding of a new target tribe that was culturally connected but based across 8 different target markets. Using EVA they gathered and analysed 70k+ pieces of visual user generated content enabling the Chivas team to think about partnerships, activations, comms, products and packaging in each of their markets.
Ella Majava, Associate Director, Kantar, Consulting Division
In conversation with…
Kate Hamilton, Global Consumer Insight Lead, Chivas Regal

14.15 Afternoon comfort break

14.35 Capturing big qual brand insights using AI virtual moderation platforms 
In Q1 2021 Diageo commissioned the MRQual research agency to undertake a moderated Big Qual research study using its Deepr service. Diageo chose this approach because they wished to gain qualitative depth at quantitative scale within one study. This was driven mainly by time considerations, as well as the number and nature of the different customer segments it wished the research to encompass. 
This case study will explain how the research was undertaken, from recruitment to questionnaire design and then fieldwork, analysis and the debrief. It will include details of the timeline, as well as an explanation of the roles of AI and Natural Language Processing within the research, an illustrative selection of raw results, and details of the sample.
Richard Clark, Director, MRQual 
Shomik Ray, Senior Brand Manager, Diageo 

15.05 Delivering agile, large-scale, qualitative international research
In 2020, HSBC undertook a large-scale qualitative piece of research across 8 markets to help re focus the business on its target audience. The pandemic has led to a greater desire for HSBCs brand research to be more iterative, responsive and agile.
Join Differentology and HSBC as they reveal how an iterative research process which combined AI methodologies and traditional in-depth interviews led to the delivery of broad and deep global, qualitative insights required for fast changing markets.
Lizzie Gilthorpe, Managing Director, Differentology
Seb Mitchinson, Global Insight Manager, HSBC
Georgie Elston, Senior Marketing Manager, HSBC


15.35 Unapologetic stories: Using AI-accelerated qualitative analysis to scope out the true size of the women’s health data gap 
Women are under-represented in data, medical trials and drug development. This project, commissioned by the Health Tech Hive, is designed to reveal the scale and form of this data gap. By finding the real unmoderated voices of women online from 251 online sources - including forums, social media, literature reviews, influencers, activists - and plugging them into’s machine-learning platform, the team were able to identify the multiple conditions affected by this gap and show the tangible ways in which women are suffering and let down. This project unapologetically highlights the scale of the problem. 
Rose Crabb, Director, 
Hannah Marcus, Associate Director,  

16.05 Close of conference

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