A key challenge of personalisation (the application of analytics by retailers to identify patterns of customer behaviour to create recipes such as targeted marketing or product recommendations) is how to gather the right data about an individual customer effectively in the first place.
Understanding what really makes an individual customer “tick” – what kind of personality he or she has (as defined by using Carl Jung’s Psychological Types that categorise how an individual perceives, interprets, thinks and feels about the world around them for example) can enable a retailer to create unique, specific recipes for that individual customer that competitors can’t imitate. For retailers carrying millions of products like Amazon, applying such deep, meaningful insight could help encourage a customer to explore a far greater range of its offerings and drive stronger loyalty.
Yet gathering data for these recipes is typically an implicit activity in the customer experience, produced by observing customer behaviour such as product browsing or buying history, social media feedback and often combined with other external factors like customer location, weather or time of day. Even the more disruptive forms of engagement – such as eBay’s “emotional recognition technology” prototype that observes a customer’s physical reaction to being shown different products to identify potential connections – is arguably a passive activity. Ideally to get a better understanding of someone’s personality involves proactively asking a series of self-reflective questions for an individual to answer privately – something totally unacceptable to the retail customer experience. So, could there be a different approach retailers could apply that gives similar valuable insights without the risk of appearing intrusive or insensitive?
One response is to let customers “play” with products before they buy them, including dynamically shaping this presales engagement based on observable behaviours. When someone buys a product online or even in-store a retailer has limited (if any) opportunities to observe how a customer reacts to it – an indicator that could help determine targeted recipes that excite, motive an individual’s exact personality. Encouraging customers to play, experiment with a product before purchase could however capture similar insight.
A non-grocer retailer may already have the tools in place to encourage such structured playtime with their products such as digital mirrors or augmented reality in store, or even have digital assets of product samples for 3D printing by a customer at home. Combined with capabilities like “emotional recognition technology”, these presale activities could become critical drivers for effective personalisation as well as offering exciting, differentiated customer experiences in their own right.
Such an approach is emerging from big retailers such as Toys R Us that is looking to transform itself into an experiential destination – the retail shopping experience as participatory theatre – so why can’t the grown-up customers have just as much fun?
If you would like more information about how Sopra Steria can help your organisation benefit from cloud analytics please contact the Sopra Steria Digital Practice.