Anyone who hasn’t been living under a rock for the past 5 years has probably heard the phrase “Brick and Mortar Retail is dying, e-commerce is taking over.” However, in 2016 over 90% of purchases were made in brick and mortar stores, so why the hype?
The truth is that Brick and Mortar retail isn’t really dying, it is evolving. The digital and physical worlds of retail are in a symbiotic relationship. For example, by some estimates, 73% of in-store purchases are digitally influenced while 55% of online shoppers prefer to buy from a merchant with a physical presence. Digital activity impacts in-store experience and vice versa.
Ladies and Gentlemen, welcome to the age of “Omnichannel”, where every sales channel and touchpoint (online, offline, telephonic etc.) comes together using innovative tech and big data to enrich your experience (get you to buy more). Say it a few times, feel how it rolls off your tongue and get used to it because omnichannel is going to be the retail buzzword for the next decade.
Globally, in-store tech startups have raised over $3.2 billion dollars since 2012 with the year 2016 recording the largest number of deals. Most of the business in the space occurs between large legacy retailers who partner with startups that bring software, technology and AI into their retail locations to
improve conversion rates and user experience.
Sensors, Sensors, everywhere
Physical stores have historically been a black box with managers having to depend on inaccurate footfall data and a general idea of consumer demographic, busy periods etc. This is changing with retailers integrating a slew of sensors that feed data to back-end analytics which in turn enable operational efficiencies.
Camera, I/R and laser sensors solutions track footfall and demographics. This data helps retailers capture operational efficiency metrics like conversion ratios. Forecast staffing requirements and even inventory. Another major USPs of people counting is capturing the marketing impact on footfall in real-
time. Mall retailers assess visual merchandising by measuring the ratio of people who enter the store after seeing a storefront display. Retailers measure advertising effectiveness by benchmarking upticks in footfall against historic data during ad campaigns.
Consumer Path Analysis
Wi-Fi and BLE (Bluetooth low energy) sensors track consumer routes to create in store heat maps. This information is aiding retailers to optimise store layouts and deploy marketing tech at congregation areas. Mall operators use consumer route data to set store rentals and to place marquee stores in the highest traffic locations.
Consumer behaviour in the physical retail world is now being tracked at a granular level much like it is on e-commerce sites. It starts at the store entrance where sensors track the MAC address of consumers entering the store. This is used to identify return customers or if a customer visits other locations of the same retail chain. This can be linked to CRM data for a personalised welcome message or relevant offers based on the consumer’s history.
If a customer dwells in close proximity to a product, beacons record the purchase intent event which is then added to a consumer graph much like it would be done online. Retailers with a high level of integration will be able to serve relevant sales content to this consumer on other channels.
The reverse scenario is also applicable. If a consumer has viewed a product online (typically on the retailer’s website,) it is possible to serve content to this consumer when they are in close proximity to the product. Some ways retailers are reaching customers is by playing relevant content on in-store
display screens and through SMS alerts.
All this data is ingested at a large scale by analytics engines that provide retailers with the ability to identify the most efficient promotions, forecast future business and target the right consumer at the right time. A lot of platforms employ machine learning to constantly improve themselves over time.
Next-gen technologies like robotics, Augmented Reality, Artificial Intelligence and Virtual Reality are finding use cases in retail. Globally, since 2012 frontier tech companies have raised over $2.0 billion.
Robots have been doing the heavy lifting (literally) in warehouses for some time. They are now being adopted at front-end retail stores as well. Mainly used as mobile assistance kiosks, robots have started employing natural language processing for more complex voice interactions. Robots can guide
consumers to products in store and serve contextual messages.
Robots are also being used to visually monitor inventory on the shelves of retail stores. Image processing engines eliminate the need for inventory checks by FMCG field workers.
AI in retail is mainly used on digital channels for improved text searching or image-based searches. There is some adoption in retail for AI powered in-store assistant apps and chatbots. Consumers can interact using natural language queries like “I’d like to buy my wife a gift” and engage in a conversational recommendation process.
AR and VR
Augmented Reality tech like smart mirrors has several natural use cases in retail. The most compelling one is that they allow the user to virtually try on products. Smart mirrors are seeing adoption in clothing, make-up and accessories like sunglasses.
AR is also being used as a promotional tool where AR info and campaigns are served to users in-store when they view products through an app.
Virtual reality is currently being used as a B2B tool. Retailers use this tech to visualise store layouts and product displays easily and at a much lower cost than physical methods.
Omnichannel has spawned an ecosystem of technology companies, systems integrators and big data operators. However, the reality is that 84% of consumers believe that retailers need to better integrate their online and offline presences and only 8% of companies said they currently provide a very integrated customer experience.
Omnichannel has a long way to go especially in India. The opportunity lies in bringing in-store technology and analytics together and completing the loop by adding content that effectively leverages the insights.
(The author is the Co-founder of Jossbox)
Disclaimer: The views expressed here are solely those of the author and do not in any way represent the views of exchange4media.com