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Choosing What You Eat- Made Easier!

After stepping into the field of shopping and OTT, here’s another arena that AI walks into – Grocery. After successful trysts at Netflix and Amazon, recommendation systems are ready to get into the kitchen now, through the task of grocery shopping.

Grocery shopping surely is not the most fun activity in the world, and I guess this feeling resonates with those of most humans in the world. How often have we gone shopping to buy ingredients for dishing up a particular meal and have missed out on certain constituents, thereby rendering the whole plan of cooking a particular dish futile?

Imagine a scenario like this – You are shopping on your regular grocery app. You have tortilla chips, jalapenos, salsa, tomatoes, and cheese in your cart. You are going to make nachos. You place your order and then realize that you could have probably ordered some mayonnaise and sour cream as well. Well, placing an order for just a couple of items is not worth the delivery cost, so all you can do is wistfully imagine how delicious your meal could have been!

Here’s where product recommendation systems come into the picture. In an alternate scenario where the grocery app had a product recommendation system built into it, it would have suggested other constituents that might pair well with the ones already present in the cart, thereby ensuring you get a wholesome meal, just the way you planned! In case of the non-availability of a particular product, it provides a recommendation of the products that are similar to the original product or alternate products that other consumers have purchased.

Product recommendation systems work by providing suitable suggestions in the following ways:

  1. Recommendations depending on the user’s preferences and purchase history-what they have added to their carts or what they have seen.

  2. Recommendations depending on the choices made by the people having the same background as the user (age or sex)

  3. Recommendations depending on product categorization. For instance, if a person has bought bread he would likely be inclined to buy jam, cheese or butter.

Food shopping when you are allergic to certain agents can be a daunting task that has to be performed with utmost caution. The same applies to people who are trying to embrace a healthier lifestyle and are trying to sidestep certain agents in their diet. These recommendation systems can play a paramount role in these use cases, by providing personalized recommendations and food swaps, thereby making the process of embarking on a journey of selective eating easier.

According to a report by Deutsche Bank, only about 3 percent of grocery purchases were done online, till the onset of the pandemic. However, this figure is bound to swing higher, with the advent of online-everything. Product recommendations can enhance the shopping experience for users and might be fruitful in amassing a larger crowd towards online grocery shopping.

Product recommendation AI has the power to transform the face of online retail shopping. It acts as a supportive tool that helps customers make smart and healthy food choices. It can help build a strong relationship between the customer and retail stores, by letting retail stores cater better to the requirements of their customers. It also helps customers save time on shopping, while simultaneously making the experience a lot more wholesome and personalized.

So what’s the future of this system?, a Los Angeles based start-up, works on grocery specific AI. It has raised close to 1.9 million USD in seed funding and is aiming to reshape grocery shopping with its grocery recommendation engine and personalized recommendations for shoppers. It has already started its partnership with several leading online grocery companies.

A major challenge in developing a system like this would be data sparsity. This is because often individual buyers buy just a minuscule fraction of the total products that a grocery store sells. However, if successfully implemented, this system would provide a win-win situation for both the customers and the retailers, and let’s admit it, it sounds pretty exciting. Let’s hold our horses and see how it pans out!


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