Sherlock.ai: Servicing several industries and staying relevant – Retail, Luxury & The D2C Health & Wellness

Sherlock.ai: Servicing several industries and staying relevant – Retail, Luxury & The D2C Health & Wellness 


As consumers of luxury goods, we love shopping for Kate Spade, Louis Vuitton, Jimmy Choo, and other such bags at malls. What we may not notice is that the ad on our phone for the latest collection of Michael Kors was targeted at us on the basis of our last few purchases and visits to luxury goods stores. This is done with the help of data from the Identifier for Advertising (IFA) cookie on our phone, which is picked up with metrics such as age, gender, or demographics as well as our behavioral data i.e., likes and dislikes or psychographics. It is also determined which location of the store we traveled to, how much time did we spend at the store, and if at all we made a purchase. Furthermore, it is also analyzed if we went to any competition stores along with more such data which is of immense use to the marketers.


Luxury Retail brands also use visitation data, user behaviours, purchases, and digital footprints to reach out to buyers. The prosperity index and visitation data can tell who is looking to buy luxury goods and if they can afford the Villeroy & Boch tea set that the company wants to market. This can be done by identifying people who visit high-end urban locations such as DLF Emporio in Delhi to classify them as affluent. Visitation data can further help in choosing new store locations. Details such as how far are we traveling from our home locations to the store also help as they give out a lot about how much we, as customers, are willing to travel to buy our desired products.


The D2C Health & Wellness industry is one of the industries using AI exponentially. As a fitness-conscious person, if we hit the gym often – say on certain days, or perhaps even all days of the week, and are health conscious (are spotted signing up for a one-off yoga session every now and then or try to fit in that pilates or air yoga class in our workout schedule), we may notice a sudden uptick in ads on our social media about protein shakes, naturally sweetened laddoos sans refined sugar, gluten-free crackers, ethically sourced food products, organic fruits and vegetables, milk alternatives, etc. We may also become the TA for companies selling fitness equipment, labs doing complete blood profiles at attractive prices, and home pick-up of samples. All this comes our way upon being identified as the customer who is most likely to buy these products or services. With the help of AI and marketing, it has been established that hypochondriacs or people who constantly worry about getting very ill may be visiting pharmacies, clinics, and hospitals way too often. Such people can be identified as the TA for those who want to do frequent blood profiles to know that their body is functioning just fine. Not only this, but we then also become the ideal consumers for protein shakes, calcium-boosting drinks for healthy bones, and so on. Philips Future Health Index India 2022 report has indicated that Telehealth and AI are top priorities for Indian healthcare leaders. The report is based on proprietary research from nearly 3,000 participants across 15 countries and looks at how healthcare leaders are using data and digital technology to address the challenges due to the pandemic.


So how are we picked and identified and targeted with these ads? Sherlock, for example, determines the kind of ailments people visit hospitals for. On a map of Mumbai, all the major hospitals and clinics were plotted. GDPR) compliant data from cellphone app data providers was used to look at the movement of people in and out of these hospitals. Sherlock was able to distinguish the hospital staff from patients or their kin based on the longevity and frequency at which they come to the hospital. At Tata Memorial Hospital, for example, they could identify the number of people coming in for treatment of cancer. Furthermore, it was also determined how many people were simply visitors and not patients. Predictive Analytics can help in managing operations and administrative challenges faced by hospitals. The above data, for example, can, among others, be used in the early detection of the rise in Covid-led hospitalization (or other such phenomena) and can alert hospitals of the need for more staff in the coming days. Hospitals can thus be alert and better prepared for what is coming their way – equipment supply and maintenance (like oxygen cylinders during Covid) can also be taken better care of.


AI’s relevance across industries can thus not be undermined. It is time to buckle up and make the most of it.

Online Grocery Retailers Ride The AI Wave for Customer Acquisition

As Machine Learning has become more accessible, more retailers are leaning towards adopting it for customer acquisition. The same is also true about grocery retailers who are trying to strengthen their relationship with customers using AI and ML. AI uses personalization and other tools to provide better experiences to customers.

Hyper personalization: Long and never-ending product lists are fast getting replaced by personalized offers to entice customers into buying more. Online retailers are bidding to meet customer expectations in unique ways by making the customer experience better. Not only products but product recommendations need to be in tandem with the requirements of the customers, even before they know they want a particular product. AI steps in here by offering experiences customized to individual consumers rather than a discount or offer available to all. This is done on the basis of what products an individual is most likely to buy. It is a win-win as the customer gets gratification, the retailer strengthens the bond with customers, and also records an increase in sales.

ML for personalization: For online retail AI relies on ML algorithms trained with behavioral data to understand customer requirements in a better way. E-commerce players can use this data for personalized product recommendations to customers and present customers with a user-oriented shopping experience. This goes over and above just selling a product.

Diderot effect for AI in online retail: Have you noticed how online e-commerce stores gently nudge you towards a container to go with the new pasta packet you just bought or cooking oil spray to go with the potatoes you just purchased? This is what is referred to as the Diderot effect which is defined as follows – obtaining a new possession often creates a spiral of consumption which leads you to acquire more new things. It is basically an impulse buy on the part of the customer. Though this kind of selling is well-known to marketers in the physical retail space, in e-commerce, such behaviour can be brought about by personalization which is done by analyzing clicks and purchase history or searches of the users. These are then used to make not only relevant but near-apt products which are almost certainly bought by them.

Besides other tools for personalization towards the goal of customer acquisition include email marketing customized for each customer, welcome texts which are personalized, e-shop navigation according to customer visit history, chatbots etc.