Deep Learning in Retail: Understanding Food Data
Deep learning in retail is helping grocers develop personalised shopping experiences at scale.
Wouldn’t it be great if you had a personal nutritionist and shopper to help plan and buy your food. An expert nutritionist who knows your tastes and avoidances, who takes into account everything from the weather, seasonal foods, promotions, how spicy you like your food, what day of the week it is or what diet you’re following. They could create the perfect meal plan for you, then order it to be delivered from your favourite grocer and even help you with the instructions to cook it.
It sounds like a foodie’s dream, but through advances in AI and NLP, companies like Whisk are finally realising the potential of ‘big data’ to make this kind of personalised experience possible for everyone and helping their partners to grow sales.
Recent advances in deep learning-based natural language processing are helping food companies and retailers across the world achieve what was impossible until only a couple of years ago. We all see traditional retail being disrupted by the changes in society and technology. Everyone is trying to keep up with the technology but future-thinking retailers are leveraging this new technology to create seamless consumer experiences for the society of tomorrow.
At this year’s Deep Learning Summit in Retail & Advertising in London, Nick Holzherr, CEO and Founder of Whisk.com, shared ways grocery retailers, brands, publishers, and IoT companies use deep learning technology to create a connected and meaningful consumer experiences. Retailers leveraging the power of data are quickly seeing Increased basket size and customer loyalty.
From Rules to Deep Learning: What Changed in the Last Couple of Years?
“The whole space really has changed, it has gone from being available to people who are doing research at the universities to being available for anybody.”
– Nick Holzherr, CEO and Founder of Whisk.com
With new technologies emerging, artificial intelligence is not reserved for people with PhDs anymore. Hiring highly-skilled technicians helps companies refine algorithms and make significant improvements in steps.
Using an example from his own company, Nick commented at the event that this change was exactly what helped Whisk scale quickly over the last couple of years. “Processing large amounts of data is what feeds our Food Genome. The recent advances in technology have enabled deeper understanding of the user data, which is why we can now provide better solutions with less resources,” Nick said.
Shopping Lists Powered by Deep Learning
From inspiration to planning and purchase, there is a number of steps. Publishers, brands, grocery retailers, and even IoT companies are trying to own more of the consumer journey. Shopping lists help consumers have a connected shopping experience. Food companies are in turn seeing increased engagement by being able to delight consumers and keep them coming back.
A consumer can now save a recipe to a list, create a shopping list, and proceed to purchase in a couple of simple steps. Based on their location, they can choose one of their favorite retailers or take the list to a store if they prefer offline shopping.
The technology that powers this solution is invisible to the consumer.
Understanding Food Data with Deep Learning
Inspiration used to be disconnected from purchase. Today, it is shoppable. How did this come about?
Everything in the world of food is interconnected in some way. Whisk uses data to map all the different connections in the world of food and to understand how strong these connections are. Once all the food data is collected and mapped onto the Food GenomeTM, Whisk uses AI to layer vast datasets, such as macro and micro nutrient data, perishability, flavor, pricing and more.
The result is a platform that can create more personalised and smarter food experiences.
The Power of Deep Learning in Retail
There is a great power to be unlocked for grocery retailers thanks to deep learning technologies. With today’s rapid advancements and cheaper technological solutions, there is no excuse for retailers not to start improving their consumers’ experiences today.