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Nov 11, 2020, 07:31am EST |
How Retailers Are Using Tech To Take Their In-Store Customer Experience Online
Alison ColemanSenior Contributor
Bridging the gap between in-store and online
The COVID pandemic has had a devastating impact on high street retail, with in-store footfall continuing on a downward spiral in markets all over the world, and retailers forced to accelerate their move into e-commerce.
One of the challenges they face is how to incorporate some of the best elements of their in-store experience, for example, personal shopping, face to face consultations with sales staff, and the tactile, sensory aspects that make shopping enjoyable, into an exceptional online customer experience.
This is particularly challenging for the high-end and luxury retailers that have struggled to translate their brand successfully online. And at the other end of the scale, the mass retailers, who, in the absence of a healthy physical footfall, are missing out on impulse purchasing.
It is a challenge they need to find solutions to, as retail experts now predict that the changes in shopper behaviors driven by the pandemic are likely to become permanent. That, coupled with growing consumer demand for convenience, personalization, and value, is forcing retailers to shift their focus from bricks and mortar to e-commerce and invest in technology that will help them make the transition.
Here are four retail tech startups helping businesses to bridge the gap between a great in-store customer experience, and the reality of mass migration to online sales.
Stylyze
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Designed specifically for the home, fashion, beauty, and skincare sectors, Stylyze is a Merchandising-as-a-Service platform that recreates all the elements of an in-store experience and is used to drive sales for clients, including Neiman Marcus, Target, and Home Depot.
In the middle of the first lockdown it launched the Neiman Marcus Connect app which drove $60 million in sales in the first 90 days of launch and played a part in the retailer recently exiting bankruptcy proceedings during the most challenging of retail climates.
With the Neiman Marcus Connect App the platform provides the data and digital toolset to offer stylist-powered omnichannel experiences at scale, which the app harnesses, enabling store associates and stylists to offer white glove styling experiences to customers both in-store and online.
The company has recently moved into cosmetics and beauty with Target, enabling one-to-one dynamic merchandising and product recommendations on the fly to meet overall shopping trends and individual customer preferences.
Nextatlas
As the old saying goes 'once you react to a trend, it's already too late', but spotting the next big thing before it gets started is a huge challenge for all retail businesses. Nextatlas uses social media data and AI to 'listen' to influential innovators and pick up emerging trends before they hit the mainstream.
Last year Nextatlas hosted a pop-up store at London's Westfield Center, basing its stock entirely on what was trending that day on social media. This is based on tracking over 400,000 global trend innovators, or influencers, using machine learning to establish what's hot and what's not.
This ability to spot future trends before the competition will become an increasingly important part of retailers' business armory. Established in 2012 by brothers, Allesio Morena and Luca Morena, and headquartered in Turin, Italy, the technology has helped with many corporate strategies and product innovations, including Heineken, Lavazza, and Nestle.
Restaurants are also venturing into the deep tech industry. Last year personalization company Dynamic Yield was acquired by McDonald's for an estimated $300 million to make its menus more 'technologically dynamic', allowing the fast-food giant to provide digital menu boards at the drive-thru that use machine learning to offer items based on customer preference, time of day and what is popular.
Dynamic Yield's decision technology will increase personalization, pulling in data such as weather, time of day, and trending menu items, while restaurants can then instantly suggest additional items to a customer, based on their current selection. The technology was quickly deployed across its U.S. system, by August last year it had rolled out to 8,000 drive-thrus, and by October, it had reached over 9,500. As well as moving into international markets, the plan is to integrate the technology into other digital products, including the McDonald's mobile app.
Invertex
An app that can instantly capture and analyze a person's anatomy in detail and in 3D is of huge value to apparel retailers looking to tailor their existing products to their customers' specific needs and also create new, fully customized product lines.
In 2018 Nike bought Israel-based computer vision firm Invertex, a developer of scanning and imaging technologies for e-commerce solutions. The purpose of the acquisition was to strengthen its digital technology offering, particularly in computer vision and AI, and 'create the most compelling consumer experience at every touchpoint,' according to Nike's chief digital officer Adam Sussman.
Invertex uses AI and 3D imaging technology to analyze a customer's feet and then suggest the most suitable models and sizes in-store. The technology can also be deployed online, with customers using smartphones to scan their foot via an app and receive recommended individualized recommended products.
Alison Coleman
I'm a freelance journalist, founder of Coleman Media. For the last 20 years I've covered business stories for national and international online and print publications,
I'm a freelance journalist, founder of Coleman Media. For the last 20 years I've covered business stories for national and international online and print publications, with a special interest in entrepreneurs and their startups. Away from business, I'm an accomplished ghostwriter: 'Pure Dynamite - The Autobiography of the Dynamite Kid', was a satisfying journalistic diversion. Follow me on Twitter @alisonbcoleman or see my latest work at www.alisoncoleman.co.uk