The latest technologies on the high street give retailers more personal and dynamic knowledge of their customers than ever before.

The latest technologies on the high street give retailers more personal and dynamic knowledge of their customers than ever before.

For shoppers that feel a bit intimidated when simply asked by a shop assistant whether they need any help, browsing the high street of the future is going to be very uncomfortable indeed.

If the commentators’ predictions are accurate, those shop assistants won’t only know your name, they will know how you are feeling, what stimulus will make you purchase something and whether they are your preferred ‘type’ of shop assistant. The good news for these reluctant shoppers, though, is that retailers may eventually even know enough about you to ensure you never have to go shopping physically – or make decisions about shopping – again.

The key is the rise of big data and the increasingly sophisticated ways that data can be harvested. It is that which has created a complete step change in retailers’ relationship with shoppers, as Jonathan Freeman, professor of Psychology at Goldsmiths University and managing director at i2 Media Research, explains. “Many years ago you would have a local shopkeeper who would know lots about you, your family situation, your personal information – your context basically – and would therefore be able to suggest products to you and react to your situation,” he says. “Retailers are trying to recreate that relationship in another way.”

They are doing so by taking customer data to the next level, beyond loyalty cards and number crunching. With the latter, a retailer will currently know when large groups of people will want to buy ice cream, or a barbecue or wellies by overlaying historical data with weather forecasting data. With the former, they will know a person’s shopping history and be able to predict that a person with that history may wish to receive certain offers.

The next generation of data insight is about a more personal and dynamic knowledge of the customer.

“What the new technology aims to do requires a more active opt-in from the consumer, but the result is more in-depth understanding about you from the retailer and it is much more reactive to what you specify,” says Freeman. “It is a step forward in accuracy and dynamism.”

However, data alone will not be enough to get it right, says Ben Hickford, head of digital at BT Expedite. “There’s no getting away from the fact that the pure social science explaining behaviours, and the algorithms designed to identify, represent, interpret and provide a meaningful response to those behaviours are different,” he explains. “The challenge is in figuring out how academic concepts and technology influence each other to form a solution which is based in reality.”

Undeniably, some retailers – and more so technology companies – are finding that sweet spot between the two already. It is this merging of established shopper psychology with modern technological developments that is facilitating a massive leap forward in customer behaviour analysis. Retail Week reveals some of cutting-edge technologies already transforming traditional customer insights in the retail space or coming to the high street of the future.

In-store eye-tracking technology

Promising to be a more accurate way of ascertaining what shoppers look at in-store and what they actually see, eye-tracking technology has left the online space where it is a common tool for website designers and entered the physical realm.

A leading company in this field is Perception Research Services, which uses cameras supported by sophisticated software. Grant Montague, vice-president for Europe, explains the technology has multiple uses. “It provides a pure understanding of how different point-of-sale material is grabbing the attention of the shoppers and engaging with them,” he says.

“We use eye tracking to understand how a packaging design and/or point-of-sale material is interacting with shoppers within the context of the shelf and also how consumers read and engage with the communication as they come closer to it.”

It can also tell you where the best position for point of sale might be and how the shopper navigates the shelves, and also has applications in tracking individuals in-store to see what they are looking at.

Emotionally responsive advertising

“We believe that there is tremendous value for a retailer in better understanding their customers’ direct emotional response to advertising, merchandising and customer service, and to measure the effectiveness of changes, be it new products, promotions, or prices,” reveals Ken Denman, president and CEO at Emotient. “Dynamic advertising and marketing, both online and in-store, could be made much more valuable with emotional response metrics.”

Emotient is a leader in this field. The software measures emotional responses via facial expression analysis. “Our approach combines proprietary machine-learning algorithms, a self-optimising data collection engine and state-of-the-art facial behaviour analysis to detect seven primary emotions, including joy, surprise, sadness, anger, disgust, contempt and fear, as well as more advanced emotional states including confusion and frustration. The technology can also detect gender and age. Segmenting emotional response by demographic group gives retailers unprecedented abilities to tailor their marketing mix – including promotions – to specific target markets,” Denman explains.

Fashion subscription sales

Would you trust a retailer to send you a new outfit based purely on pre-set parameters you have filled in? Retailers are hoping many will. “There’s a buzz in the industry at the moment over the concept of subscription sales for fashion products, whereby a customer could give a website a budget or subscribe for a period of time, tell it their preferences – sizes, types, colours and brands – and the website will create outfit combinations and send those items to the customer on a regular basis,” explains Ben Hickford at BT Expedite.

“Personalisation techniques could be applied to these types of sales to great effect, learning each customer, what they like and what they don’t, and thus improving the accuracy of the items that get selected and sent to the customer.”

Consumer-controlled promotions

This is where consumers can input preferences via an app – a bit like creating an online dating profile – and receive personalised promotions in return. This is already happening in a number of ways but Freeman believes one of the best examples is the Regent Street app, which uses beacon technology to send information and offers to shoppers’ mobile phones. “It builds a profile of you by you giving a thumbs up to different brands, products and categories. It then generates a profile of you. So when you walk into a shop it can send you offers relevant to you. That is a great example of really useful data that the consumer has complete control over,” Freeman says.

Shopper moods software

The i2 Media Research software state model is essentially a way of responding to shopper moods and preferences using real-time mobile data and historical data. “It was developed initially through observational research, but now we have digital metrics that can work out where within a range of mindsets a consumer may be – so it looks at dwell time in particular areas of the store, for example, and has algorithms cancelling out other reasons for that dwell time such as taking a phone call or having a conversation, and then can tell if a consumer is interested in a product in that area,” says Freeman.

“We can then use data we have built up around that customer and target them.

So David might respond best to pretty blonde sales assistants, so let’s send over a sales assistant to him where he is dwelling next to the jackets to tell him he looks great in it. Or maybe David has a young child and money is tight, so let’s send over a 10% discount offer for that product direct to his phone now.”