How your customers’ behaviour can help your retail KPIs

By Ramy Sedra, Partner, Data Analytics Consulting Leader, PwC Canada

In the era of digitization, retailers have access to real-time data that maps the movements and decision processes of customers and can help deliver better products and services and superior customer experience. But data in isolation means nothing, so it’s imperative that we interpret it accurately to generate the maximum benefit. Viewing big data through the lens of behavioural science can be especially powerful.

The benefit of big data

More than ever before, we can anticipate consumers' needs and desires using big data. Integrating principles of behavioural economics to analyze data helps retailers understand what motivates consumers, what they like, what they don’t like and what prompts them to buy. What’s more, we can use big data to understand behavioural patterns and habits to better differentiate customer segments and enable more personalized shopping experiences.

Emotional index: Clarifying our understanding of behavioural economics

Behavioural economics is the study of how mental shortcuts, which people rely on in their day-to-day decision making, can influence stakeholder behaviour in systematic and predictable ways. Guided by the foundation of strong analytic models of purchasing behaviour, the principles of behavioural economics can be used to nudge behaviours in a way that benefits both the business on key performance indicators (KPIs) and the stakeholder in their decision-making process.

An example of this is how Amazon uses the well-proven behavioural economics bias of social norms—recommending similar products that other people have viewed or purchased (i.e. "People that purchased x also purchased x, x and x"). This recommendation service not only makes the shopping experience more helpful for customers, but also contributes to 35% of Amazon's revenue.

A Gallup poll found that companies that apply the principles of behavioural economics beat their peers by 85% in terms of sales growth and by 25% in terms of gross margin. Using behavioural economics has proven to be an effective approach for retailers, for example, when determining messaging and pricing strategies:

  • Changing a price tag from "On sale for $5" to "Price reduced to only $5" can boost response/purchase rate by up to 20%.
  • Offering a lower-end option can boost consumers' value perception of top-of-the-line options (and purchase intentions) by up to 52%.
  • Sales arguments based on time well spent, rather than money well spent, can double the number of customers and double the price they consider acceptable.

Currently, the retail sector relies heavily on market studies, but behavioural science can offer even greater insights because it grounds customer strategy in how consumers actually behave.

Though behavioural economics is still in its formative stages, it’s a critical approach that when applied in conjunction with analytics can uncover new business opportunities for retailers. It can open the door to an infinite number of ways to surprise consumers and offer them a unique experience they'll want to share with others.

Thank you to Melaina Vinski and Annie Veillet for working with me on developing this article, originally published in Le détaillant Magazine (CQCD) Vol. 17 / n˚3 / Winter 2017.

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