5 Tech Trends Ushering Era of New age Retail

There are a lot of tried and tested machine learning models/solutions which help brands learn about the consumer, segment them in profiles and personalize their experience going forward.
5 Tech Trends Ushering Era of New-age Retail

The retail market in India is estimated to reach a whopping $1.1 trillion this year, making this year an extremely significant one for the retail industry. While fashion trends change every year, every season, the current retail trends will rule the roost this year too. For instance, an omnichannel presence for any brand is still the necessity of the hour. For online-first brands, setting up offline stores becomes imperative as 75% of the retail market is still offline. While for off-line players, establishing an online presence has become important as the market is growing at full speed and a large percentage (as high as 75% according to some estimates) of consumer consideration funnel originates online. Thus, an omnichannel strategy leveraging synergies between channels, and the pace at which brands make the shift will decide success in the space.

Another trend in the offline retail space is the use of new-age marketing channels like digital marketing, SEO, Email and Telephone marketing which garner higher ROI as compared to traditional media. Leveraging new age channels like YouTube, TikTok and OTT platforms have become important,even for offline players as they compete with online brands who already use these channels extensively for both revenue generation and brand building.

Tech-impact on offline shopping experience

Meanwhile, technology will continue to play a major role in the offline shopping experience. A typical retail conversion cycle works as follows: Consideration-Discovery-Conversion-Retention

Consideration – This is when a potential customer considers buying a product and contemplates on the brand choices. A large part of the consideration funnel starts online, even for offline retail, be it in the form of digital marketing or SEO or location-based searches. This is where tech can play a huge role to build a brand’s consideration among its customers. Research and studies have reaffirmed that 75% of India’s offline brand introduction in Tier 1 cities is decided basis online consumer searches.

Discovery – 60% of India’s population is estimated to own a smartphone by 2022 and hence the usage of smartphones for discovery while shopping is going to go up even further. The gap between online and offline is shrinking rapidly & this will continue to shrink with the increase in ease of internet accessibility.While creating offline shopping consumer journeys, retailers must be mindful of the fact that the consumers are comparing prices, viewing reviews, reading details online while going through the aisles. Retailers can also make use of this opportunity by creating an endless aisle experience in the stores wherein they can expose their entire merchandise width to a consumer standing in the store, especially post they are comfortable with the touch, size and fit of the brand through trials in the store. Brands also need to invest in enabling more personalized conversations at the store through investment in data systems and analytics. In all of this, omnichannel brands again have a significant advantage over brands that focus on a single channel.

Conversion – brands are making use of new-age technologies like NFC, self-checkouts, etc., to ensure that from the point when consumers have picked their preferred product to the point that they own it, the journey is quick and seamless. The much-evolved logistics eco-system also enables retailers to offer different forms of delivery options to the consumers. Retailers are already using a variety of tech-enabled payment options from cards to UPI transactions, mobile wallets to improvethepost-discovery consumer experience.

Retention – it should take a business at-least 5 times (for some brands it is close to 25 times) lesser marketing investment to retain a consumer compared to acquiring a new one. Businesses can expand their bottom-lines by 25-30% by a 5% increase in consumer retention. Brands have started leveraging data-sciences, new-age marketing/CRM, and different technology platforms to enhance the post-purchase experience for consumers. Apart from a clear product/service differentiation, this becomes the most important driver for getting consumers back to the brand. Consumer feedback collection, segmentation, personalization, lifecycle management, loyalty programs become important tools increasing the probability for a brand’s consumers to come back and shop again.

AI(Artificial Intelligence), ML(Machine Learning) will continue to be game changers

The availability of significant volumes of internal and external anonymized data (especially with tech-led retailers) has now made it possible for retailers to go beyond traditional business analytics and explore artificial intelligence and machine learning-based models to solve consumer and business problems.

Consumer retail brands can benefit from AI in two major directions. First is in offering an ideal, hyper-personalized consumer experience wherein every touch point of the brand with the consumer models itself according to the needs of an individual. This has its applications in performance marketing, offline store experience, cross-selling, consumer care response, pricing/discounting, etc. There are a lot of tried and tested machine learning models solutions which help brands learn about the consumer, segment them in profiles and personalize their experience going forward. New-age products that make use of image processing, in-store VR experiences, sentiment analysis, voice recognition etc. to create a ‘customer wow’ while a consumer is interacting with a brand are also being experimented.

The second benefit that retailers can draw is in driving business efficiencies which result in measurable savings in costs and an increase in profitability. A few of the most established impact areas of data sciences in retail are merchandise planning, price elasticity, promotion/marked-down optimization, programmatic marketing, fraud transaction detection, omnichannel inventory allocation, cataloging, etc.

There are market estimates of ~$2 billion being spent by retailers on AI and ML-based solutions in 2018 and this number is predicted to grow by over 350% by 2022. Indian retailers would not want to be late in adopting new-age data science solutions and trailing in the race with their online or global peers.

The author of the article is Anuj Gupta, CRO, Zivame, a leading omnichannel player in the lingerie segment.

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