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.)

In 2016, brick-and-mortar modern retailers seemed to have begun recovering their confidence, and cautiously investing in expansion. However, currency shortage has significantly dampened demand at the end of the year. The hangover would continue into the first half of 2017, and consumers could be muted overall on discretionary purchases, including fashion, mobile upgrades and out-of-home dining.

On the other hand, while digital transactions introduce a note of caution (friction) in the consumer’s purchase decision, for e-tailers they do reduce complexity, cash-handling costs and potential returns which could provide significant unexpected wins.

I’ve written about this for years, and don’t tire of reiterating: the retail sector must recognise that shopping is a unified activity for the consumer; physical stores and non-store environments are alternative but complementary channels. Brands can and must use whatever channel mix works for them, and brick-and-mortar retailers need to invest in creating an integrated growth blueprint towards “unified commerce”.

On their part, while e-commerce companies are constrained by FDI policy, they will need to invest more in developing “old economy” strengths – strong product differentiation and distinguishable brands. Fashion, accessories, home decor and other lifestyle products are strong drivers of gross margin for all multi-product retailers, and e-commerce players struggling on the path to profit would focus on these even more, as well as on private labels. They also need to have management teams that are able to cast their minds 3-5 years into the future, while keeping close watch on immediate cash flows. Capital is available, but turning risk-averse. All businesses need to focus on up-skilling their teams, retaining good people, improving processes and adopting technology. In recent years, growth in the retail sector seems to have been driven by a “spray-and-pray” approach, not necessarily management sophistication. Spending like there’s no tomorrow is a sure way to no tomorrow.

In short, 2017 could be the year where the entire retail sector grows up – a lot. We hope.

(This piece was published in The Hindu – Businessline on 29 December 2016).

Aggregator models and hyperlocal delivery, in theory, have some significant advantages over existing business models.

Unlike an inventory-based model, aggregation is asset-light, allowing rapid building of critical mass. A start-up can tap into existing infrastructure, as a bridge between existing retailers and the consumer. By tapping into fleeting consumption opportunities, the aggregator can actually drive new demand to the retailer in the short term.

A hyperlocal delivery business can concentrate on understanding the nuances of a customer group in a small geographic area and spend its management and financial resources to develop a viable presence more intensively.

However, both business models are typically constrained for margins, especially in categories such as food and grocery. As volume builds up, it’s feasible for the aggregator to transition at least part if not the entire business to an inventory-based model for improved fulfilment and better margins. By doing so the aggregator would, therefore, transition itself to being the retailer.

Customer acquisition has become very expensive over the last couple of years, with marketplaces and online retailers having driven up advertising costs – on top of that, customer stickiness is very low, which means that the platform has to spend similar amounts of money to re-acquire a large chunk of customers for each transaction.

The aggregator model also needs intensive recruitment of supply-side relationships. A key metric for an aggregator’s success is the number of local merchants it can mobilise quickly. After the initial intensive recruitment the merchants need to be equipped to use the platform optimally and also need to be able to handle the demand generated.

Most importantly, the acquisitions on both sides – merchants and customers – need to move in step as they are mutually-reinforcing. If done well, this can provide a higher stickiness with the consumer, which is a significant success outcome.

For all the attention paid to the entry and expansion of multinational retailers and nationwide ecommerce growth, retail remains predominantly a local activity. The differences among customers based on where they live or are located currently and the immediacy of their needs continue to drive diversity of shopping habits and the unpredictability of demand. Services and information based products may be delivered remotely, but with physical products local retailers do still have a better chance of servicing the consumer.

What has been missing on the part of local vendors is the ability to use web technologies to provide access to their customers at a time and in a way that is convenient for the customers. Also, importantly, their visibility and the ability to attract customer footfall has been negatively affected by ecommerce in the last 2 years. With penetration of mobile internet across a variety of income segments, conditions are today far more conducive for highly localised and aggregation-oriented services. So a hyperlocal platform that focusses on creating better visibility for small businesses, and connecting them with customers who have a need for their products and services, is an opportunity that is begging to be addressed.

It is likely that each locality will end up having two strong players: a market leader and a follower. For a hyperlocal to fit into either role, it is critical to rapidly create viability in each location it targets, and – in order to build overall scale and continued attractiveness for investors – quickly move on to replicate the model in another location, and then another. They can become potential acquisition targets for larger ecommerce companies, which could acquire to not only take out potential competition but also to imbibe the learnings and capabilities needed to deal with demand microcosms.

High stake bets are being placed on this table – and some being lost with business closures – but the game is far from being played out yet.

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.

Devina Joshi, Financial Express

Mumbai, 8 September 2015

E-commerce, as we know it, is old news. Hyperlocal is the hot new buzzword in retail hallways, going by the recent spate of well-funded launches in this space. There is already a wide range of services on offer, from grocery delivery to home, office and personal care services. Hyperlocals, services-based or inventory-based, are largely an urban India phenomenon. Services are hyperlocal by their very nature, driven by locality or communities. When moving into a new city, for example, people would like to stabilise as quickly as possible and here, such services step in.

To put the whole picture in context, the Indian retail industry is worth $500-600 billion. Of this, grocery items account for about 67% of the revenue. However, in case of fast moving consume goods (FMCG) and grocery, modern retail formats account for less than 10% of the total sale. E-commerce or hyperlocals are obviously a tiny part of the pie just yet. Most companies, therefore, are still at a stage where they have to prove their business models and change consumer behaviour.

While on-demand grocery delivery—the model that players such as Grofers ride on—has immense potential in this space, other high potential categories include delivery of services (such as supplying peons/delivery boys, specialised laundry services, plumbers or electricians), price comparisons, food ordering apps, etc.

Hyperlocal startups in India

It is a no-brainer that an aggregation model, since it is asset-light, is less capital-intensive than the inventory-led one. Moreover, it is easier to scale up such a model. The new generation of hyperlocal start-ups is coupling aggregation with logistics/delivery, thus controlling even the last mile.

Take Zopper, a product-based hyperlocal which started off as a price comparison website for electronics but now is a platform for purchasing products from offline stores. It counts on faster delivery through tie-ups with local shops near a buyer. “City by city, we need to bring more merchants on board, and all they have to do is download an app and their product can be listed on Zopper,” says Neeraj Jain, CEO, Zopper. The company’s margins vary from 2-8%.

Home services start-up Taskbob, founded by Aseem Khare, charges a 20% commission from its servicemen. Product price comparison website MySmartPrice works on commission too, while providing a free six-month on-board period to offline sellers, where they can use the platform for gaining traction. The revenue model of BookMeIn, another home services company, includes a monthly subscription fee for a SaaS-backed system given to service providers to manage their business. Further, it gets revenues on leads/bookings done by customers on the website, along with revenues through ads of service providers. So what’s working in their favour?

A fertile environment

Indian retail is still dominated by brick-and-mortar stores, which, oddly, is an opportunity in disguise for hyperlocal players. Unlike non-hyperlocal e-commerce, these start-ups are not really competing with offline retailers, but are partnering them instead.
Hyperlocal business models spell instant, on-demand delivery as they cater to needs of a more immediate nature. The gratification is far more accelerated – the entire transaction can be completed in an hour sometimes. Customers also tend to trust hyperlocals more than non-hyperlocal e-commerce websites, as the stores they buy from through online platforms have a physical presence, making it possible to attend to any grievances quickly. Further, the start-up can tap into existing infrastructure, acting as a bridge between existing retailers and the consumer.

“Due to the convenience factor, by being able to tap into consumption opportunities that might have otherwise been missed, the aggregator can actually drive new demand to the retailer in the short term,” says retail consultant Devangshu Dutta, chief executive, Third Eyesight.

Within hyperlocals, services have higher margins of around 20% as opposed to product based models which earn 2-10% margins or even non-hyperlocal e-commerce companies, which operate on 3-7% margins, depending on the category.

This is because there is virtually no warehousing, inventory management or logistics involved in a services hyperlocal. Within services, food-ordering apps have an added advantage of the frequency of purchase as opposed to, say, e-commerce products. “The category is a high-repeat one as opposed to home repair for example,” says Saurabh Kochhar, co-founder and CEO, India, and chief business officer, global, Foodpanda.

A word of caution

While it ensures higher margins, replication of a services model is much more difficult. Training of people in services is very difficult as each individual has to be available wherever the customer is located. “Second, when a product delivery happens, I need local people to deliver it but if a person is coming to give a service, he represents your brand and should know how to handle a customer,” says Alagu Balaraman, partner and MD, Indian operations, CGN Global India, a supply chain management consulting firm.

Third, as the services industry is rather fragmented, it is difficult to form partnerships with associations or groups of such service providers, as specialists are spread out across the country. Fourth, creating a need for services might be difficult as people may already have their own local set-up in place. “But that mindset is changing, with a large group of urban people who don’t have the time or patience and need professional services,” he says.

The biggest learning will be the capability to scale. A hyperlocal that focuses on a single ‘locality’ will find it difficult to get the scale needed to create an economically viable model. Being able to identify a widespread but local need, and having a model that adapts to each new market will be crucial.

(Published in Financial Express.)