MRS Analytics Spotlight: Rupert Anderton
16 April 2024

Interview with Rupert Anderton - This month's MRS Analytics Spotlight
Interviewed by Lisa Cowie, Freelance Researcher, and a member of the MRS Advanced Insights and Analytics Council.

Rupert has spent almost 30 years in marketing insights & analytics, with expertise in segmentation, marketing spend effectiveness, pricing analysis, investment optimisation and MMM.

He is currently the global MMM lead at Haleon PLC, and prior to this position he has spent time working in agency, client and consulting roles, across numerous sectors including financial services, pharma and telecoms.

Here Rupert talks about how data analytics has entered market research and how it’s changed the nature of the work.

Q. How did you start in the market research industry?

A. Started accidentally. Became a junior researcher in a fledgling Market Research Team in what was a Training & Enterprise Council in Manchester back in 1993.

Q. What attracted you to work in market research?

A. Whilst not a planned career, Market Research offered a great variety and piqued my curiosity of better understanding consumer and customer motivations and behaviours, which I find fascinating.

Q. What's the role of data analytics or data science for research purposes within your company?

A. Analytics and data science have been embraced totally by the organisation. An extensive programme of ‘Always On Market Mix Modelling’ covering over 60% of all media spend is a fundamental measure of media efficiency and effectiveness. Analytics also underpins pricing decisions.

Q. Have you seen a shift in the nature of market research during your career?

A. I have seen market research morph into insights, and then the rise of big data and analytics, and now AI/ML. I still believe that fundamentally the industry is seeking to do as always - put the customer/consumer at the heart of the business to drive performance/strategy and deliver a competitive advantage.

Q. How do you see advanced data analytics (and perhaps even machine learning / AI) impacting your business in the future?

A. There will always be a need for measurement. I believe that AI/ML will augment analytics and research but will never replace the need for human understanding to make sense of complex information. I do envisage that we will no longer have such a distinction between insights and analytics, as combining gives a fuller picture

Q. How do you and your team combine market research with data analytics in a day to day sense?

A. In the main it is 'triangulation' of sources - how do the findings from advanced analytics support insights/research findings and vice versa?  How can a story be created from combining outputs from each?

Q. Have the research questions that your clients bring to you changed over time? Have the solutions changed?

A. Questions have changed to become more strategic - where are the opportunities, where can greater revenue/profit be obtained for example rather than very tactical questions.  Much more openness to analytics and data - a realisation that data can also be a source of competitive advantage

Q. What are some successes and challenges you've encountered working across both an insight function and a data function?

A. I have been fortunate to be early in the process so have been able to carve a career using data and insights. A big win is being able to translate what the findings mean for the business and also what the business needs from analytics/insights.  Historically a challenge to have insights/analytics driving strategy but I do believe this is changing. Insights/Analytics are uniquely placed as work across the business not in a silo.

Q. What are the key challenges for data scientists working in market research rather than other industries?

A. A major challenge is really understanding what the business requires.  Often data scientists may create brilliant statistically valid work but fail to understand how the business will use it or are unable to explain it to the business (commercial) teams.

Q. What three pieces of advice would you give to a data scientist entering market research?

A. Make time to understand the business (not just the data), find time to interact with consumers/customers and remember common sense :-)