At the recent Phygital Retail Convention in Mumbai, Devangshu Dutta anchored an engaging “Fireside Chat” with Bhavana Jaiswal of IKEA India and Kapil Makhija of Unicommerce , on retailers engaging with their customers across channels and formats, and the opportunities as well as challenges in managing experiences seamlessly across online and offline interfaces.

Watch the video at this link:

In this piece I’ll just focus on one aspect of technology – artificial intelligence or AI – that is likely to shape many aspects of the retail business and the consumer’s experience over the coming years.

To be able to see the scope of its potential all-pervasive impact we need to go beyond our expectations of humanoid robots. We also need to understand that artificial intelligence works on a cycle of several mutually supportive elements that enable learning and adaptation. The terms “big data” and “analytics” have been bandied about a lot, but have had limited impact so far in the retail business because it usually only touches the first two, at most three, of the necessary elements.

“Big data” models still depend on individuals in the business taking decisions and acting based on what is recommended or suggested by the analytics outputs, and these tend to be weak links which break the learning-adaptation chain. Of course, each of these elements can also have AI built in, for refinement over time.

Certainly retailers with a digital (web or mobile) presence are in a better position to use and benefit from AI, but that is no excuse for others to “roll over and die”. I’ll list just a few aspects of the business already being impacted and others that are likely to be in the future.

1. Know the customer: The most obvious building block is the collection of customer data and teasing out patterns from it. This has been around so long that it is surprising what a small fraction of retailers have an effective customer database. While we live in a world that is increasingly drowning in information, most retailers continue to collect and look at very few data points, and are essentially institutionally “blind” about the customers they are serving.
   However, with digital transactions increasing, and compute and analytical capability steadily become less expensive and more flexible via the cloud, information streams from not only the retailers’ own transactions but multiple sources can be tied together to achieve an ever-better view of the customer’s behaviour.
2. Prediction and Response: Not only do we expect “intelligence” to identify, categorise and analyse information streaming in from the world better, but to be able to anticipate what might happen and also to respond appropriately.
   Predictive analytics have been around in the retail world for more than a decade, but are still used by remarkably few retailers. At the most basic level, this can take the form of unidirectional reminders and prompts which help to drive sales. Remember the anecdote of Target (USA) sending maternity promotions based on analytics to a young lady whose family was unaware of her pregnancy?
   However, even automated service bots are becoming more common online, that can interact with customers who have queries or problems to address, and will get steadily more sophisticated with time. We are already having conversations with Siri, Google, Alexa and Cortana – why not with the retail store?
3. Visual and descriptive recognition: We can describe to another human being a shirt or dress that we want or call for something to match an existing garment. Now imagine doing the same with a virtual sales assistant which, powered by image recognition and deep learning, brings forward the appropriate suggestions. Wouldn’t that reduce shopping time and the frustration that goes with the fruitless trawling through hundreds of items?
4. Augmented and virtual reality: Retailers and brands are already taking tiny steps in this area which I described in another piece a year ago (“Retail Integrated”) so I won’t repeat myself. Augmented reality, supported by AI, can help retail retain its power as an immersive and experiential activity, rather than becoming purely transaction-driven.

On the consumer-side, AI can deliver a far higher degree of personalisation of the experience than has been feasible in the last few decades. While I’ve described different aspects, now see them as layers one built on the other, and imagine the shopping experience you might have as a consumer. If the scenario seems as if it might be from a sci-fi movie, just give it a few years. After all, moving staircases and remote viewing were also fantasy once.

On the business end it potentially offers both flexibility and efficiency, rather than one at the cost of the other. But we’ll have to tackle that area in a separate piece.

(Also published in the Business Standard.)

Retailers seem to be fighting a losing battle against the growth of ecommerce, and it is only the nature of the shopping activity, especially for fashion – interactive, social, and immersive as it is – that has kept many retailers relevant and in business.

However, the defensive stance is changing, and now they’re using technology to get the customers back into the store. Forward-thinking retailers are reimagining trial rooms, stores, business processes and entire business models. It’s not a physical versus virtual approach but an approach that integrates both sides. The idea is to create a more immersive experience than pure digital retail can be, using some of the same tools as ecommerce.

It is important to remember that the whole retail environment is a “suggestive” environment. Due to cost and other operational factors most retailers are ill-equipped to provide appropriate levels of excitement, suggestion and support during the browsing and buying process.

For many, the simplest move could be screens serving up their catalogue to customers within the store. For instance, US department store chain Kohl’s has initiated connected fitting rooms that identify products the customer is carrying, and bring up not only those items onscreen, but additional colours and sizes that are available. If the customer wants an alternative, a message goes to a sales associate who can fetch the requested option. Macy’s and Bloomingdales are using tablets in the trial rooms, while Nordstrom, Neiman Marcus and Rebecca Minkoff are attempting to boost their fashion sales using magic mirrors to provide similar enablement. These devices and the processes empower and involve the customer far more, while leaving store staff free for other activities.

A step up, Puma is using “virtual trials” for its apparel products by having a customer take images of herself in specific positions, and then mapping styles on their own images to visualise how they might look. While this needs more work and investment, this is still only a more developed product browser technique from the customer’s point-of-view.

The next level, augmented reality trials and virtual fit, are significantly more sophisticated at creating simulations of a selected garment image draping and falling on the customer’s body even as he or she moves normally. Imaging and texturing of the simulated garments is technically challenging and expensive, repeated for each new style and option. The imaging also needs to mimic the “wearer’s” movements. Nevertheless, retailers such as Polo Ralph Lauren are finding it worth their while to investigate these new technologies, as these reintroduce the much needed “theatre” that are integral to a successful retailer.

For the customer virtualisation expands the number of items “taken” into the trial room, and creates more convenient product discovery. More products can be seen in the same shopping time, and sharing of images and videos with friends and family, engages them in the shopping process as well.

For retailers, the benefits multiply. Inventory can be optimised, and there is reduced handling and shrinkage. Even without sales associates, it is feasible to prompt for alternatives and related products, improving conversion and transaction values, reducing space and costs of physical trial rooms, and increasing the number of customers serviced especially at peak traffic times.

A phenomenal advantage is the data captured that is relevant while the customer is in the store, but which can be linked to future promotions. Valuable intelligence, such as what is being tried and for how long, can help the retailer to quickly gauge demand patterns, and adjust pricing and promotions. Normally retailers only capture sales transactions (post-fact), and miss out the rich information on in-store behaviour that etailers do collect and analyse.

However, massive hurdles to virtualisation remain, including data input accuracy, product accuracy, and the technical capabilities of the tech solution adopted. A bigger concern is whether technology is intuitive and seamless, or whether it gets in the way of the shopping experience. Further, consumers do have privacy concerns about the images and other data collected.

Its important to remind ourselves that, on its own, technology is just a novelty – huge transformation of business processes, organisational capabilities and behaviours must happen as well.

That is perhaps the biggest mountain to climb.