Sherlock.ai: Servicing several industries and staying relevant – Apparel, Automobiles, & Edtech

Sherlock.ai: Servicing several industries and staying relevant – Apparel, Automobiles, & Edtech

When you know your audience, your audience knows. That car ad on our mobile, that ‘shop from hmonline’ ad on our Instagram account, that ad for a ‘complete blood profile test’ at an esteemed lab, or that ‘preview invite’ for a luxury brand delivered to our inboxes are not mere coincidences. Marketers across industries offering different products have one goal – they follow their audiences for their likes, dislikes, preferred products, where they live, what they do, where they would like to buy the products or avail of the services, and how much will they be willing to spend on these products and services, and basically every little detail about their audience is of relevance.

 

Visiting India Fashion Week? When we browse Instagram for fashion choices and check new collections of JJ Vallaya, Sabyasachi, Manish Malhotra, and other favourite designers on their respective handles, AI works parallelly to help the Apparel industry in labeling us as fashionistas. Those of us who follow fashion trends, fashion bloggers, and designers on Instagram, shop at their stores, and more are all identified and delivered targeted ads for specialty clothing/ occasion wear, especially during the festive seasons. Diwali is round the corner, party invites have started trickling in, and who can resist that ad for the festive outfit we are already on the lookout for? Besides, Sherlock also tries to find out how far, we, as customers are traveling from our home locations to the stores, along with other stats such as if we need our shopping delivered home and if we are likely to shop at multiple designers, and so on.

 

When we go to buy an automobile we usually have certain brand preferences/loyalty and a budget in mind. For a long time, as Maruti or LML Vespa buyers, we never looked elsewhere. But, when we are leaning towards buying a car brand ‘A’, and it doesn’t fit in our budget, and we happen to get an advertisement on our Social Media platforms of a car brand ‘B’ whose dealership showroom is located near our home or office, and the prices are within our budget, we may actually end up visiting the showroom and buying that very car. This is not serendipity. This is targeted marketing with the help of AI.

 

So how does an automobile showroom analyze the competition in the market, how does one know what vehicle are we, the customers looking to buy and in which segment, which competition showrooms are we visiting, and which are the places where showrooms or vehicle charging stations should be set up and more? Brand loyalty makes customers travel to faraway places to have a look/test drive at their preferred automobiles. Sherlock.ai comes into play by mapping the layout of all automobile showrooms. Consumers visiting the dealerships are tracked as well. Our current vehicle or mode of transport is also determined. This data is then combined by mapping it with IA’s proprietary analysis to help in understanding the locations where we have shopped or what is called transactional data (using our digital footprints and use of debit/credit cards/wallets etc.), where we live, and other metrics such as prosperity level and thus the ability to spend, automobile dealership visitation, search trends on digital platforms (Google, Car aggregators), etc. to create classifiers based on our interest in purchasing a vehicle. Precisely targeted campaigns are then launched on Social media platforms such as Facebook, Instagram, and Google for those of us who are most likely to convert.

 

As parents of Class 12 students, we are often hustling – trying to get brochures for the best colleges for our children, doing the math for affordability, looking for counselors who provide help at every step, from finding the right courses in the right colleges and handholding up to the visa interviews. AI helps Edtech optimize tasks by bringing in personalization to customize course requirements to match the students’ requirements taking into account things such as intelligence, mobility issues, preferred study destination, affordability, and many more such criteria. It starts with identifying us as the parents of K-12 students and even identifying college students as higher studies abroad or within the country are classified as undergraduate and postgraduate. Besides, school students are constantly looking to upskill to stand a chance at Ivy League admissions or admissions to other prestigious colleges. Working parents, teachers, and professors are also identified along with target parents who are involved in their child’s education. All these criteria help the Edtech industry delivers targeted ads that can be of immense use for both the advertiser and us parents, looking for such services. 

 

These are only a few of the industries that are being helped by Sherlock.Ai. Our next part to this blog will discuss more fascinating insights from some other industries. Stay tuned.

 

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.

How can marketers use Sherlock AI’s Ganesh Chaturthi data from Mumbai beaches

How can marketers use Sherlock AI's Ganesh Chaturthi data from Mumbai beaches

The beaches of Mumbai turn into leisure grounds providing space for a multitude of activities, especially on weekends. From spotting celebs in the famous Juhu Beach to the lively sand beach at Gorai and mouth-watering food stalls at Aksa, beautiful walks at Versova- Mumbai’s beaches offer a plethora of things to do all-round the year. 

But what makes it even more popular among locals and tourists alike in the month of August & September? Thousands of people celebrating Ganesh Chaturthi (*cue* images of splendidly decorated idols of Lord Ganesha, gigantic and festive pandals throughout the streets of Mumbai and the public processions with mesmerizing music ranging from devotionals to Bollywood!). All these festivities end with people thronging the beaches leading to the visarjan after a lively procession.


A look at Mumbai’s ‘famous’ beaches


Sherlock AI: The superlative number-cruncher


It is no secret that people like to visit the beaches on weekends, holidays and festive occasions, and especially during the festival of Ganesh Chaturthi. Sherlock AI plotted the data of the number of people visiting the beaches starting August 24-26, 2022 i.e. weekdays, and saw the numbers going up 100% on Sundays, dropping again to 31% and 27% respectively on Monday and Tuesday i.e. August 29 and August 30. These numbers were expected to continue to be low on Wednesday and Thursday or August 31 and Sept 1, 2022, respectively as these were weekdays. Sherlock AI found the number going up again (89% on Aug 31 and 60% on September 1 which were weekdays) as these were festive days of Ganesh Chaturthi and people were seen thronging the beaches even though these were not the designated ‘visarjan’ days. Overall, during the Ganesh Chaturthi festival days, the number of people visiting the beaches was even higher than on weekends.


Is it just enough to understand the “footfall” of people visiting the beaches? After all, it’s almost common knowledge that the number of people visiting beaches during weekends or Ganesh Chaturthi is higher than on normal days. These are people that actively participate in religious festivities like Ganesh Festival, Navratri, Dusshera, Diwali, et al. It’s nice to know the exact quantitative “surge”, but wouldn’t it be even better if we could understand more about these people visiting the beaches- where they come from, their spending capacities, their demographics? Oof, we know hundreds of marketeers who would kill for this level of precision targeting!


Finding the home location of crowds & their consumer behavior


Besides the data on numbers and days of the week, what would be nice to know is where these people are coming from. Sherlock AI also determined just that. While it’s obvious that people who live close to these beaches would visit them, what is even more interesting is that people who live further east and in fact, even as far as Navi Mumbai and beyond, visited these beaches on the Western side of Mumbai on Aug 31, 2022.


Home locations of visitors to various beaches in Mumbai on Aug 31, 2022

The yellow towers indicate the home locations of the devotees and the height of the towers indicate the number of devotees from that location.

Marketeer’s delight


Once the marketers know where these people are coming from, a lot falls into place. They can, for example, see the Sherlock prosperity index © of the places these people come from. The prosperity index gives an indication of the prosperity of the 150m block in a city/town. It has been created using 8+ econometric datasets that now accurately predict whether people living in that block can afford a product/service or not.  They also know these people are the right target audience for any goods and services related to religion, spirituality, and festivities. How to sell gold to this audience on the occasion of Akshay Tritiya – shops like Tanishq and other jewelers can really benefit by tapping into this specific audience rather than advertising to a larger audience. How to tap these audiences to buy puja ingredients online or will they be willing to buy such ingredients online? How to advertise the services of astrologers, and tarot readers to them? How to sell precious and semi-precious jewels to them? Besides religion and spirituality marketeers looking to sell lifestyle goods, two-wheelers, set up kiosks at the beaches, and perhaps  even Diwali-related lines, can all benefit from this data. Sherlock Ai brings you nearer to your audience by telling you who they are and where exactly you can find them and advertise to them

Sherlock.ai reaches high-intent target audiences by understanding user behaviour

Sherlock.ai has been constantly getting better at helping clients reach out to not only their target audiences but ‘high-intent’ target audiences or those who are most likely to convert into their customers. This is done by analyzing and understanding different datasets – Visitation Data, User Behaviours, Purchases, and Digital Footprints.

 

Visitation – As the name implies, this dataset gives access to which specific types of places are the people visiting. Are they going to automobile showrooms, theaters, apparel stores, salons, or beaches repetitively? How much time do they spend in these respective places and what kind of activities do they take up while there? Also, what time of the day are they visiting these places? In the case of branded products and services, their brand affinities also become a part of the datasets. Once we know the type of places they have been visiting, we are able to predict their behaviour on the basis of that. For example, in a case study around the coffee shops in Mumbai to determine the best places to open coffee shops here on the basis of the prosperity index, the number of people visiting these locations, and their visit timings. The map of Mumbai was broken into blocks of different colours, each indicating the prosperity index of the area – the darker the colour of the block the more prosperous the area is. All locations of all coffee stores in Mumbai were also plotted on it including Starbucks, CCD, Barista, etc and overlaid them on the prosperity index. The map also gives the revenue potential of these stores. It also indicates the number of people visiting that store in a time frame and which stores are clearly doing well, which are average, and which aren’t performing well. One could also figure out the number of people picking up coffee as a takeaway and those who were staying in the coffee shop to drink. The map also has circles indicating the colleges in these areas and the enrollment number of each of these colleges. In some of these colleges with a lot of enrollments, there is no coffee chain. This data could help those looking to set up stores or kiosks. Coffee chains can use all this data to determine the location of their next coffee shop.

 

Digital footprints – When people browse the internet in various ways and using various tools, they leave behind digital footprints which are immensely valuable to marketers and companies selling goods and services. The digital footprints provide insights into what people are searching online, and the kind of apps they download and use – gaming, shopping, luxury, grocery etc. All these provide insights into their online buying behaviours. Post-pandemic digital sales have skyrocketed and these insights help in shaping the consumer strategy and reaching out to the TA with the most intent of buying their wares. Additionally, one can also see how social media reflects their behaviour.

 

Purchases – The next dataset which is of big help is how the purchase behaviours of customers are like – Are they impulsive buyers or do they research and buy or do they shop for discounts before picking a product. What segments are they spending on? If they are spending on branded things or does branded retail not matter to them? Additionally, a lot of intel is also gathered about the customers by working with credit card companies & Point-of-Sale cos, as their spending patterns can be picked up from here – cash sales, credit cards, debit cards, e-wallets, etc.

 

User behaviors – Combining the purchase patterns of customers with other indicators like the place they live, their spending capacity, where they work, what are their travel routes every day and their mode of transport; if they own bikes or cars; what is the number of members in their family; the prosperity index of the place they live in – all these help arrive at a holistic view of the consumer.

 

All the above datasets helps optimize their marketing spending as they are able to cut out all the fluff while trying to reach out to people. They are now armed with the knowledge which helps them reach out to those with the intent to buy. These are also people who match their brand’s profile and are most likely to convert into customers.