COVID-19 is driving the importance of data in retail: Part 1: The Research Perspective

As a small but perfectly formed Business School we enjoy a precision focus on one industry. Our industry was challenged from many directions before Covid-19 came along but now our imperative to support fashion businesses of all sizes through our applied research and knowledge exchange has never been greater.  In this series of two articles we show how our strengths in data analysis uncover promising tools for future forecasting and how this research is translated into impactful knowledge exchange through our close alignment with industry partners.

Liz Gee, Associate Dean: Fashion Business School, London College of Fashion, University of the Arts London

By the time COVID-19 disrupted the UK economy, the retail industry was already showing signs of distress with a decline in footfall and consumers estimating that they spend less than before (PwC, 2019). The government-imposed lockdown has effectively turned off the tap of physical retail sales in the UK with McKinsey (2020) showing that spending on apparel will record a precipitous decline as a result of COVID-19. Therefore, the fashion industry must shift its business models and strategies to mitigate the downside risks and leverage potential opportunities. Take for example Primark, once turning over £650m per month and now nothing due to a total lack of online presence (BBC News, 2020a). Fashion businesses just like others now need to accelerate their digital innovation and e-commerce initiatives to survive and succeed in what will be an even more competitive market (BOF McKinsey & Company, 2020).

Successful shifts in business models will require extensive market research in a resource constrained world where consumer behaviour is continuously evolving (Forbes, 2020) and changed further by the pandemic itself (Kantar, 2020). These shifts mean that reliance on historical data to forecast and predict is useless. There is now a need for current data-driven insights to support investment decisions; modelling the demand for new products, technologies and business practices; their acceptance and adoption under these new patterns of consumer behaviour.

With demand for fashion brands moving online and potentially remaining online as behaviour changes post lockdown, research measures need to follow. There is now a need for accepted measures of online consumer behaviour with the analysis of likes, comments, tweets and even online search interests as valid measures of consumer needs and wants. With COVID-19 expected to increase the demand for e-commerce, fashion businesses of all sizes can benefit through the adoption of a more data-intensive decision-making approach to understand the consumers’ needs and wants. Researchers at the Fashion Business School at London College of Fashion presented the idea of using Google Trends as a proxy for fashion consumer behaviour in 2019 and this study may be more relevant today with global consumers under lockdown as Google continues to dominate the worldwide search engine market (Net Market Share, 2020). Given that there is a sound broadband coverage (Figure 1) in the UK, it is not surprising that consumers, who are now ‘stuck’ at home are shopping online (Business Insider, 2020; WARC, 2020).

But it’s not just fashion where the shifts in consumer behaviour need to be understood. Businesses of all sizes, operating in FMCG sectors could use Google Trends as part of their forecasting toolbox to interrogate demand shifts leading to better stock purchasing decisions and more efficient use of their constrained cash resources. Our first example considers the change in consumer preference following the lockdown curtailment of the nation’s coffee-shop habit. Over five years, based on the analysis of search popularity, tea was more popular than coffee, both on average, and across most months (Figure 2).

Figure 1. Broadband coverage in the UK (Source: Ofcom).

However, as seen in Figure 3, COVID-19 has disrupted the popularity of tea in comparison to the popularity of coffee with UK consumers since 17th March 2020. It is also noted that over the last five years, coffee has never been more popular than tea in the UK in the March - April period. Accordingly, Google Trends indicates a shift in consumer behaviour towards coffee and market data can corroborate this result (Financial Times, 2020) with coffee being identified as one of the six products that are booming in sales in the UK during COVID-19 (BBC News, 2020b). Interestingly, the Financial Times article was published on 14th April whilst the BBC News article was published on 29th March. Google Trends show signs of coffee overtaking tea long before these articles were written (Figure 3).

Figure 2. Google trends for ‘tea’ and ‘coffee’ over the last five years (accessed: 28.04.2020).

Figure 3. Google trends for ‘tea’ and ‘coffee’ over the last 90 days (accessed: 28.04.2020).

At times of crises and as the “new normal” of the post-pandemic world starts to emerge, there has never been greater imperative for businesses to be able to interrogate their cashflow forecasts. Tools are needed that help refine the real-time prediction of cash requirements. If Google Trends can shorten the forecast horizon, even just evidencing recent “hindsight” then it could be one more tool in the economic fight for business survival. See for example the search interest for ‘sanitizer’ in the UK as shown in Figure 4. It is easy to dismiss retrospective Google Trends analysis as a mere formulation of anecdotal “hindsight” – everyone knew hand sanitiser was trending because they could not get it! But, whilst Google Trends can demonstrate that the surge in demand for ‘hand sanitizer’ was short-lived as lockdown negated its need, as restrictions relax then demand will change again and Google Trends may help this longer tem demand modelling and purchase decisions.

Figure 4. Google trends for ‘sanitizer’ over the last 90 days (accessed: 28.04.2020).

If you are interested in finding out more then please read: Silva, E.S., Hassani, H., Madsen, D.Ø. and Gee, L. (2019) Googling Fashion: Forecasting Fashion Consumer Behaviour Using Google Trends, Social Sciences, 8(4), 111. If you are a researcher interested in exploring this area further, then The Centre for Fashion Business & Innovation Research would love to hear from you. Please contact Dr Emmanuel Sirimal Silva, (e.silva@fashion.arts.ac.uk) to discuss your ideas.

By Emmanuel Sirimal Silva and Liz Gee, Centre for Fashion Business & Innovation Research, Fashion Business School, London College of Fashion, University of the Arts London

Read Part 2 here