In modern-day personalization has attained the peak position in driving success for any business' marketed product or service. The machinery of traditional media started fading about a decade ago as more smartphones started making inroads in the market with cost-effective internet services and all that on the backdrop of the rising disposable income of individuals in India. Cash intensive and lacking a results-oriented approach has led the traditional marketing technique to take the back seat. Driven by the demographic approach, predominantly through traditional marketing techniques, typically physical, businesses were only able to influence a particular consumer base where they sought their flyers to be distributed, billboards to be placed, or Radio Ads running on a particular local radio channel. 

But with the advent of the internet, a new world of marketing opened. This has been on the back of the widespread penetration of digital media. It has empowered the consumer to select from a wide range of choices of anything that they want to avail of, be it the type of shirt that perfectly fits them based on their previous search or hailing their favorite SUV on lease from a self-drive car aggregator for their upcoming staycation. This personalization has not arrived out of the blue but is backed by timeless pieces of data. This data is nothing but a repository of the past preferences of customers and predicts their future behavior in availing of a product or service.

Hence, in the current times, a business' key focus while ideating a marketing campaign is to collect essential relevant data about the consumers that they are eyeing to tap. This solves a majority of the hurdle, as a consumer usually makes a decision while considering various aspects kept in mind. This is good from the perspective of understanding the consumer and predicting their approach to a product. But each consumer has had a totally contrasting experience in their life to date and their perspective might be totally different in seeing the product. So, does that mean that you would prefer the first consumer over the second? No. They both are crucial leads for a business to bring in cash flow. Also, they are just two people that we cited, but you have hundreds of thousands of people whom you want to tap who have had different experiences and have a unique consumerism pattern. Does that mean, your one-size-fits-all marketing approach is going to engage them into making them your consumer and in turn brand ambassadors? No. Personalization is the answer.

This is where the new age of marketing comes into play. Machine Learning and Artificial Intelligence (AI) have come a long way in enhancing operations of all the traditional practices that to date remain the building blocks of commerce. Be it Production, Sales, Marketing, Feedback, etc., these technologies have put forth prudent application that has enhanced the functionality of several businesses. Let's dive deeper into knowing the application of AI and Machine Learning in marketing and how it enhances the consumer experience.

Now comes the question of how do you target each individual from the enormous database with an approach that only influences him in deciding to make a move and buying a product or service while believing that the transaction will benefit as per their understanding? Here's where Machine Learning pitches in.

For example, say you shop for a particular size of a shirt of a particular brand in a particular pattern and often in select shades of color from a website/ fashion app that you are a member of. Say one day you search for new designs of shirts but don't find anything suiting up to your expectations. In a couple of hours, do you receive a notification of the app reading a message like, "(Your name), Were you finding a pink shirt from United Colours on Benetton? We're sorry they ran out of stock but here are some similar shirts in which you will look as stunning!" You might want to check out them, so you give in and click on the notification and may even end up buying an alternative. What you did in turn was, you keyed in several keywords in the search tab of the app while searching for your preferred shirts. Like, Pink shirts, United Colours of Benetton, etc. What the app did was record and learn about your preference through AI. It then filtered and surfaced only related products from various brands basis your other search preferences. This is how Artificial Intelligence made it simpler for the online apparel store for marketing while providing you as a consumer with a personalized experience.

A classic example of machine learning too can be mentioned using the same online apparel app. Say you bought a pair of trousers of size 34 from a popular brand like Raymond through this online fashion marketplace app about a year ago. Now, if you search for similar shade trousers and like one of the many listed ones, however, it is not from Raymond, but its sister brand Parx. Say you select size 34 again, but you know that each brand, even though from the same company, many have different criteria for fittings. In this case, as you select the size 34, it will suggest you with a statement below, "According to your previous purchase, size 32 will be the perfect fit for you from Parx." What happened here was it learned about your preference from the past and kept it recorded and the AI on the back end prompted you about the variation in size of apparel between two brands of the same company that might fit you ideally. This makes your buying experience seamless too and hence willing more to rely on the recommended size on the app moving forward while shopping without being conscious about the sizing/ fitting.

That is just citing an example of the application of Machine Learning and Artificial Intelligence in one instance. There are hundreds and thousands of permutations and combinations where AI and Machine learning can be plugged into marketing to elevate customer experience on the back of personalizing it at every touchpoint.

Author:

Arif Kazi, Managing Director and Founder of Dust Value