Servicing several industries and staying relevant – Apparel, Automobiles, & Edtech Servicing several industries and staying relevant – Apparel, Automobiles, & Edtech

autoWhen 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.

Read this detailed case study on how Sherlock AI enabled Tata Motors to acquire customers and reduced CAC by 75%!


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. 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.

Want to explore how Sherlock AI can help your business? Write to us


Subscribe to our newsletter for regular updates and interesting insights Servicing several industries and staying relevant – Retail, Luxury & The D2C Health & Wellness 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 and precision targeting high-intent consumers

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.


Towards a healthier and fit world: Sherlock AI helps D2C, Health and Wellness companies in acquiring high-intent consumers

D2CThe 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. Read more about how Sherlock AI helped BMC with tracking COIVID 19

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


 Interested in acquiring high-intent consumers? Schedule a call with us and see how Sherlock AI can magically improve your customer acquisition!

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

Ganesh Chaturthi


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. Check out how Sherlock AI is enabling clients across D2C, Luxury, Retail, Health & Wellness to acquire high-intent consumers reaches high-intent target audiences by understanding user behaviour

Target Audiences 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.


How does Sherlock AI understand consumer signals and create these high-intent target audiences?

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. See how Sherlock AI uses these to acquire consumers in Health & Wellness


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.

Case Study: How Sherlock AI helped Tata Motors acquire consumers and reduce CAC

Following up on our previous post, Tata Motors, a USD 4 billion leading global auto company and an Infinite Analytics client, in its diverse portfolio, includes an extensive range of cars, SUVs, trucks, buses, defense vehicles etc.  They saw a whopping 75% reduction in Customer acquisition cost (CAC) upon using Sherlock AI. The client started using Sherlock AI a tool developed by Infinite Analytics with the mandate of addressing a few issues and challenges which were:

The client started using Sherlock AI with the mandate of addressing a few issues and challenges which were:

  • To find out people who have visited their showrooms or that of their competitors (a challenge faced by most automobile manufacturers).

  • Looking for consumers who are currently looking to buy a vehicle, and also finding the different consumer signals which help identify the intention of purchasing the said vehicle.

  • They were also looking for dataset acquisition. An algorithmic setup to blend data layers is a computationally intensive task and needs specialized and seasoned data scientists to execute it successfully. 

How Sherlock AI rose to occasion and provided just the solutions that were needed 

We started by mapping the layout of all car showrooms and consumers visiting the dealerships were tracked as well. We then combined the mapping with IA’s proprietary analysis to help in understanding the locations where the ***device has shopped***, where the individual lives, and other metrics such as prosperity level (insert prosperity blog**), transactional data, automobile dealership visitation, search trends on digital platforms (Google, Car aggregators), etc. to create classifiers based on the person’s interest in purchasing a vehicle.

Tata Motors

After doing so, we ran precisely targeted campaigns to the people who were mostly to convert (as customers of Tata Motors) on Social media platforms such as Facebook, Instagram, and Google. These activities led to some amazing results for Tata Motors as they witnessed a whopping 75% reduction in Customer acquisition cost (CAC). 

 These kinds of results have been made possible as we at Infinite Analytics are First-party data independent, 100% GDPR & CCPA Compliant, and track the most comprehensive real and digital signals from 40+ datasets and 350 million consumers. 

Hear directly what Tata Motors has to say:

As a testimonial, Rajan Amba, VP, Sales & Marketing, Tata Motors PV, said, “Infinite Analytics has been a partner to Tata Motors, in the last one year. Their platform, Sherlock AI is helping us scale our network expansion, both in the passenger vehicle business. It also delivered what it promised – a reduction in CAC and a new perspective in customer acquisition that no one in the market provided. They are essential to our growth ambitions and we look forward to deepening our relationship with them.”

Want to explore how Sherlock AI can help your business? Write to us

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How AI Has Helped Food Delivery Cos Reach Greater Heights

Food delivery companies all over the world are using AI to reach greater heights. The same is true about apps such as Zomato, Dunzo, Borzo etc in India. If you are in India and remember the Swiggy app of yore, you may also remember how it was just another option when other apps didn’t work or delivery partners were not available. Today, Swiggy boasts of an order volume that has grown over 200%. Applying AI to its workings, the company generates terabytes of data week after week. 

Food DeliveryThe delights of using the app today are such that it has converted dedicated users of rival apps to being their own loyal customers. How did they do it? In their own words, this was achieved by real-time, micro-optimization of dynamic demand-supply, over and over many times during the day. With this they were able to provide the urban consumers with hitherto unexperienced levels of convenience.  

With the recent hit of the pandemic, more and more people have begun to realise that ordering food online is much more easy and convenient than going to a restaurant. This has opened up a wide range of opportunities for restaurants to go digital and reach a wider range of customers. This seem to be accelerated by COVID, with a big wave of people starting to ‘order-in’

The How

Swiggy achieved its goals by creating a three-way hyper-local marketplace wherein the company matched the demands of the consumers with supply from vendors i.e. restaurants, cafes, and stores as well as deliver executives (mostly people looking for quick money and side jobs). They used AI across this marketplace to deliver a delightfully seamless customer experience to achieve unparalleled growth and also drive operational efficiency. Infact, they are now so dependent on AI for their growth that they consider it impossible to go back to the time wherein they relied just on human intelligence to achieve their goals.

Behaviour of the consumer

Collection of consumer data helps Swiggy get hold of the behavioral aspect of things. By knowing their customer’s behaviour through this data they can deliver personalized experiences. This is achieved using Catalog Intelligence with which ML models help enrich the Swiggy catalog with meta-data. For example Classifying foods on offer as vegetarian, egg, or non-vegetarian and even categorizing similar products under sections for example: salads, soups, main course, rice, breads, and dessert. 

Use of Customer Intelligence helps the company in customer segmentation on the basis of their affordability (derived using their past buying behaviour) and also log customer churn i.e. when a customer stopped using the app or service. Customized and relevant content is shown to the customers  using catalog intelligence and customer intelligence. You may notice the app showing you your previous order and prompting you to re-order the same. 

This happens as the app may have noticed you ordering the same food from a particular place again and again. This even includes showing you restaurants nearby you depending on your current location and not your usual home or office location. Their Live Order Tracking feature is one of the most popular features among customers. They even get to know of delays and when the delivery partner is at their doorstep.

Want to use Sherlock AI in acquiring higher intent consumers? Drive up app installs, app engagements and user acquisition using Sherlock AI. See how it works here

Vendor X Food Delivery

To tap in the right vendors Swiggy uses AI for time-series based demand prediction models which help the restaurants plan ahead to meet the demand of the customers. The Company also uses ML to cut financial losses by identifying and preventing abuse.

With such advanced uses that are being improvised upon as you read this blog, the food delivery landscape is bound to change even more in the times to come.

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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 online 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.

How are online grocery retailers leveraging AI?

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.

Online Grocery

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. Based on the recent survey carried out by Information Resources Inc., more than 52% of online shoppers normally select their favorite grocery store considering the store that offers quality item at lowest prices. 

Nevertheless, based on the prevalence of stores like whole food stores and others, it is quite obvious that people are usually ready to spend little more extra when they are paying for not just food but impressive shopping experience. Majorities of online shoppers usually move to the store that is not just providing them not just with what they need in the store but also make them feel belonging. 

Also, doing all you can to make the customers feel personal relationship which will make grocery shopping an easy and simple thing to do at any point in time. Customers will not see shopping as a chore anymore when you offer them an iPhone or Android shopping app that will make it easy for them to get your ads, coupons, and everything they need, just with a tap on their Smartphone and website. 

Take advantage of easy Grocery Store Customer Acquisition, Loyalty and Retention through data-digital marketing- Use Sherlock AI!  See how Sherlock AI identifies high-intent target audiences

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Customer Acquisition in Gaming: How AI is Helpful

The gaming industry is all about the number of ‘active users’ without whom the companies would come crumbling down. To prevent a mobile game from being a flop show, players are needed. So how does one acquire players for the game? A well-thought user acquisition strategy is the key to success.

Customer acquisition for mobile gamings can be achieved through two ways: Paid or Organic. Paid customer acquisition simply means converting users with the help of paid ads on various social media platforms as well as advertisement networks. These typically involve app installation ads that are prompted on the screens of users to insta;l the game. This strategy is quite effective in mobile ames as backed by data it helps gaming companies reach high-quality users. This also makes your game reach a wider audience. Reliant on data, campaign management is increasingly becoming automated and more efficient. Organic customer acquisition on the other hand involves discoverability of the game so that users can install it without the help of paid advertising. To do this one needs app store optimization, posting regularly on your own social media to increase awareness and make a community around your game.

Use Automation

Automating the customer acquisition campaigns got a long way in defining the success of your game. The Automated App Ads (AAA) option of Facebook demystifies the entire process of creating ads, especially if you are not a pro at media buying.  Backed by machine learning, not much input is required in automated campaigns as compared to standard app install campaigns. They are also beneficial as they help in testing multiple creative combinations making it possible to reach out to more users.

Combining two strategies

A combination of paid and organic customer acquisition is ideal. When a company begins its ad campaign they opt for paid campaigns as this encourages more downloads and once that is achieved, the game shows up higher in search results, increasing the discoverability, post which the company opts for organic campaigns. Using a variety of channels helps your ad and thus reach out to more and more people.

Setting KPIs

Key Performance Indicators or KPIs are truly important in measuring the success of customer acquisition campaigns. The mobile game owner would definitely want to know the number of installs along with Cost Per Install (CPI), Cost per Acquisition (CPA), and Customer Acquisition Cost (CAC). In-app metrics too help in knowing a lot about the customers one has acquired. The end goal of customer acquisition is also acquiring quality customers who not only play the game on a regular basis but also spend on apps via purchases. 

How AI helps Travel Marketers in Customer Acquisition

AI enables personalized marketing tailored to the needs of individual customers; helping marketers in the travel industry overcome their challenges of catering to personalized product recommendations as well as information that is tailored to their needs. There is a plethora of  opportunities which marketers can explore with the sheer amount of data they have such as  geo-location data, demographic data, behavioral data et al. The obstacles are seen in the form of high customer acquisition costs and low conversion rates, diminishing brand loyalty from the customer end, and high rate of booking abandonment, which can go as high as 80%.

Getting across the apt content to customers at the right time is quintessential. Travel marketers can use a variety of tools for customer acquisition such as:

AI-based personalization

AI backed customization engines predict future behaviour of customers on the basis of customer eyeball data and their behaviour. Customized recommendations at each and every step are helpful to the brands.

Homepage Reccomendations: On the basis of the customer’s search history, they are shown information that is most relevant to them when they are on the homepage of a travel website. Example: A customer searching for hotel stay in Milan will be shown the best deals on all Milan hotels. This increases their chances of booking and such personalized home page recommendations can get the company relatively higher CTRs.

Product Recommendations: Product Recommendations help on the basis of the interest of the customer in higher conversions, especially if the recommendations are contextual. Sightseeing packages, honeymoon packages, etc. can be shown.

Category page reordering: This is a simple case of showing the preferred products of the user first. If a customer has a tendency to look at home stays rather than hotels, then the travel marketeers can recommend home stays at top resulting in good conversion rates again.

Exit popups: Customers often browse a lot before picking the end product or service. If a customer tries to leave your website a customized exit popup may just help them stay or make them think og coming back to your website.

Besides, personalized emails through tailored recommendations as well as push notifications may lead to conversions. To add to these methodologies, rule-based personalization or in simple terms, designing a whole website experience on the basis of the customer’s location, type of device used etc. can help in greater conversions. The advances in AI and ML have brought in a stream of opportunities for travel marketeers. Using AI for customer acquisition is definitely the way forward.

How advertisers can get around Facebook Ads Aggregated Event Measurement

The Apple’s iOS 14 updates have made advertisers using events for conversion optimization or call-to-action such as the sales of tickets to a Coke Studio Live concert), to switch to the Aggregated Event Measurement with a caveat that one can have only eight events (such as a concert or the release date of a particular product like Vanilla Coke) per domain (a number which was previously unlimited). Events are used to create custom audiences on the basis of actions users have taken on an app or a website. These audiences can then be targeted with ads relevant to them when they visit Facebook. Let us see how we can continue to use Facebook ads well even after the iOS 14 privacy update.

Remove irrelevant events: If you have events which are unused in current ads when you see the Results or Optimization Events columns in Facebook you can choose to remove or skip these events from the new Aggregated Events Measurement setup. Doing so will save you a lot of time and optimize your ads.

Combining events: When you don’t have more event spaces left try and combine events which are similar in nature. For example, two different product launches which would have the same call-to-action can be clubbed. Content events too, can be clubbed as one such as blog views, guide views, video views etc. You could also club events for seasonal actions in one place. While on your Aggregated Events, when you use custom conversions with the combined actions, only one event is created, instead of a lot of events with limited slots.

Using what is there: Though there are only eight spots for optimization and conversion tracking, one can still make any number of events. If the events you have set up are not in the top eight for Aggregated Measurement, you can create audiences to use for ad set targeting (in other words a group of customers shall be targeted for a particular event). When you create audiences you can choose from the eligible events to be used as audience source and create retargeting ad sets on the basis of particular event actions to try and get the user or your probable customer to the final conversion action.

Not all of these strategies may work in all events but some may work in certain situations. It will take a bit of trial and error before we arrive at what works best for us. What we would also like to say here is that one must make use of specific targeting options while they’re still available but also to prepare for what lies ahead. Broad targeting using Facebook’s ad delivery system helps find potential customers one would not have known about otherwise. Targeting expansion can help improve the advertiser’s campaign performance by allowing Facebook’s system to reach a wider spectrum or group of people than what is chosen by you in targeting selections. Both broad targeting and targeting expansion may be good strategies to begin with!