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As the global economy moves towards normalcy, retailers must think on their feet to adapt, survive and go on to thrive, not only in the second-half of 2020, but also for several years to come. The impact of COVID-19 will be paramount in the grand scheme of things and the more knowledge retailers have about the post-pandemic retail narrative, the better.
This is precisely why we at Vue.ai launched R-Vue Connect, an exclusive digital summit for retail professionals across the globe. R-Vue Connect isn’t just about helping the retail community stay informed, but also about building a dependable community of retailers and experts that can share their insights and grow together.
At our latest episode of R-Vue Connect, experts Abraham Thomas, Chief Data Officer at Quandl and Anandamoy Roychowdhary, Investor at Sequoia India spoke about the one element that has fueled the success of several retailers during this difficult time— the accelerated adoption of technology and AI!
The world is in the middle of a data explosion. Everyone is carrying a supercomputer in their product and companies are obsessed with it. And the amazing thing is that a lot of information out there is still untapped!
There are data trails everywhere. There’s no piece of economic activity that doesn’t leave some sort of record in some database somewhere.
Companies (big and small) that have seen profits during the months of April, May, June and July have one thing in common – they are obsessively tracking and measuring every aspect of their operations and their customers. They don’t simply track this data, they also put it to use. How? Read on to find out.
Abraham Thomas took us through the significant types of data at R-Vue Connect, and placed emphasis on the 4 pillars of data that retailers need to focus on, namely:
A big factor here is competitor data, for example, Uber has to pay attention to what Lyft is doing- the rates they’re offering, the coupons they’re giving, everything!
And customer data. A great shopping experience 30 years ago would have the shopkeeper knowing the names of a customer’s family. It might not seem scalable, but with technology, it can be, and retailers can build rich customer profiles.
So how do retailers act on data? Henry Ford had the answer 100 years ago with his assembly line. Every company, no matter what industry, has a data assembly line consisting of 4 steps:
Every part in the data assembly line is a specialist role, because each one has its own challenges and requirements. This data assembly line works miraculously for businesses and is the future. Every business needs to focus on this for success.
Retailers are often faced with the dilemma of building their own tech tools versus buying them from specialists. For that, Anandamoy Roychowdhary, the tech expert at R-Vue Connect, said, “Sometimes a small tiger team with the best engineers focused on solving problems for your customer is a better approach than writing 3000 lines of code to build something that might not even matter.”
Very rarely do CTOs consider the cost of building. Very often it starts as a hero’s journey, only later do they realise that building is extremely hard in terms of time and resources.
Everything is changing at an incredible speed! Retail CTO should be talking to startups that are building incredible tech to keep up the pace.
Default to buying first and building if and only if buying doesn’t work. You can always make a case for yourself when it comes to building.
“Let the specialists do their specialist thing” chimed in Abraham, at R-Vue Connect.
If retailers leverage the amount of new tech out in the world, they will be able to significantly improve not only their own operations but also their customers’ shopping experiences.
Generative AI is the future – its ability to demonstrate value in both the front end and in the back end is invaluable. It can completely change the way retailers think about processes and how to go about a job.
Vue.ai’s VueModel for instance, generates images of human models, so fashion retailers don’t have to do any photography! Just pass on the garment images and AI generate the model wearing the garment across different sizes, different accessories and more.
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