As we get closer to the end of the first half of the year, high street retailers will be hoping that this Q2 shows a marked improvement in sales compared to the first quarter. The run-up to Christmas 2018 was not the magical time of the year high street retailers hoped for and research from published in April paints an equally bleak picture.
According to PwC research compiled by the Local Data Company, 16 stores are closing per day on our high streets and only nine are opening in to make up for them. Things are on a downward trend with the number of daily openings at almost half the level it was five years ago. On the 500 most popular shopping streets in the UK, there was a net loss of 2,481 stores, taking into consideration that there were 3,372 openings and 5,833 closures. In addition, the number of store opening by chains has decreased by 17.4% in year-on-year.
Lisa Hooker, consumer markets leader at PwC, said of the findings: “In 2018 we saw an acceleration in footfall decline on the high street with businesses continuing to see the impact of online shopping, increasing costs and subdued consumer spending.”
Can data be utilised to improve and even turn around this sorry state of high street shopping affairs? Perhaps. According to three experts, this can happen if physical retailers make of the most of the advantage they have over online-only retailers. That advantage is a physical space in which to analyse, connect and communicate with customers IRL (in real life).
The view of Jean-Pierre Van Tiel, chief operating officer at DPL, a customer analytics and technology company, is that the retail environment could do with a little bit of pizzazz with high street shops at the moment being a bit underwhelming.
"Retail is lacking ’theatre’ and an engaging experience."
He said this is because they are cutting corners to compete at the same price level as the online retailers which is putting off the customers. This is leading to a lacklustre experience for the shopper who may have wanted to interact with the product and/or with a salesperson about the product. He said: “Today, retail is lacking what I call ‘retail theatre’ and an engaging experience in store.” He said that retailers can create that experience which online pure players cannot and data can help them do that.
Van Tiel said that there is now technology available that uses data and analytics and by adding behavioural analytics, allows retailers to take a picture of a customer walking into a store. From that image, the salesperson is then given, almost instantaneously, the support and information to know the best approach to take with that individual, as well as information on the volume and nature of their past purchases.
He said that his company can assess potential customers with regard to the five traits: openness, contentiousness, extraversion, agreeableness and neuroticism. As a result, the salesperson can tailor their pitch to that person specifically. For example, he said that a highly conscientious person with children would want to know about a washing machine’s ability to kill bacteria, which would not be the case for an extroverted person with a low level of conscientiousness.
"The salesperson needs to be able to read you."
He said: “We’ve all had that experience of walking into a store. The salesperson needs to be able to read you, say the right things, respond to you the right way and give you the right amount of time. We do that at scale through technology and therefore that experience can be replicated over and over again.”
Van Tiel also said that digital displays of appliances could also adapt to different types of customers. Here he gave the example of a store selling home appliances such as fridges. Once a data-driven smart fridge has detected the type of customer approaching it, it could generate a visualisation inside of it for the potential customer of groceries and produce that they would typically buy.
"It doesn’t take any time to make that analysis."
None of this could be done without the correct permissions in place, Van Tiel was keen to stress. He said: “Before walking into the store, the customer is alerted that this is being done and that they have to give their consent. With all the approvals in place, it doesn’t take any time to make that analysis.”
Retailers that have both online and high street stores can take customer data from the former to inform decisions about the latter. This is the case with the clients of Peak, an artificial intelligence company. Peak’s chief executive Richard Potter gave the example of trainer and sportswear retailer Footasylum. He is working on the assumption that buyer activity and behaviour online will be mimicked by activity and behaviour in store, having seen a link between the two.
Peak observes people in a particular geographic area behaving a certain way online and the retailer can optimise the stores in the same region so that those online shopping patterns can be easily replicated in the bricks and mortar shop. This can be in terms of trading and merchandising decisions and could result in having particular products in stock or displaying certain products in a particular way.
"Products that sell together can be reflected in store."
“If we can see that certain products sell well together or are attracting people’s eyeballs in an e-commerce environment, that could be reflected in visual merchandising in the store, different shop layout and different products next to each other to achieve that pull through between two different product categories,” said Potter.
Andrew Fowkes, head of the Retail Centre of Excellence at SAS UK and Ireland said much of the same. He said: “Most of our clients on the retail side have at least 25% online sales. The ones that are doing the best are joining the store performance with the online performance.”
Fowkes explained that at SAS there is a concept called ‘trade area analytics’ which looks at how customers within a certain geography buy from a particular retailer. The learnings from that mean that the physical retailer might cease to sell a certain product in store because customers prefer to buy that item online.
The sources of customer retail data are numerous: loyalty schemes, email marketing, promotions, online behaviour, customer feedback as well as social media activity. When asked if there are any less obvious sources of customer data, Fowkes pointed out the growing importance of influencer or social media marketing.
Social media users with a high subscriber or follower count on visual platforms such as YouTube and Instagram form partnerships with brands to display or review their products. With access to detailed social media analytics from the influencer, the brand then has detailed data on a niche audience of potential customers.
Fowkes said: “That gives an advanced show of what they are going to buy or what they are thinking about buying and get their reactions. There is a whole new platform around data and insight and the feedback those people can give you.”
Of course, this data could be used to influence the promotion of certain products online but it could also be used to help the retailer decide the region in which to host a pop-up shop or feature products that appeals to a certain demographic that heavily represented in that area. This is a tactic used by Gymshark.
Potter made a salient argument for the need for physical retailers to make the most of customer data. He said that consumers are going to come to expect the conversation between themselves and the brand to be an ongoing dialogue and not just an interaction of them being sold to. He went on to say that by employing hyper-personalisation, engagement with a consumer is going to be much, much stronger than if they are on the receiving end of blanket, catch-all advertising. If detailed data is the key to that personalisation, the high street store can be the avenue.