How Big E-commerce Players Are Harnessing The Power Of Artificial Intelligence To Increase Sales Numbers This Festive Season

With the increasing battle for the market share amongst the online retailers and the addition of new players each day, capturing the bigger slice of the cake and thriving in this red ocean has become a challenge.

E-commerce players having thousands of products in the inventory with every customer having a unique taste, e-com teams are trying to match this gap in the market to convert every visit into a sale and increase average order values(AOV). This has led the e-commerce market to leverage the power of artificial intelligence and machine learning tools to analyze the petabytes of data to uncover the treasure of insights into consumer tastes and preferences.

This has led to the birth of Recommendation Engines or Recommender Systems as gone are the days of ‘segmentation’ or ‘personas’, every consumer wants to be treated as an individual and expect brands to curate as per their tastes. AI and machine learning has been pivotal of the recommendation engines along with the data and is being used by the top players in the market for service differentiation and better user experience.

But how is it done? Call it a gold mine, or the new oil — data is fodder for artificial intelligence. These eCommerce sites collect consumer data from the stage of their searches, browsing behaviors, size preferences, cookie data, transactions, the brand followed, and so on. Usually, a huge e-commerce company generates 10–15 terabytes of data in a single day. These big players then use this data to optimize the product displays on their websites and apps be it on the landing pages, product pages, or ancillary products under the cart during these large festive sales and thus increasing sales and AOVs.

With the increased efficiency of recommender engines and more data feeding, e-commerce brands have achieved a higher level of personalization which in turn reducing product returns and cart abandonment.

But, this comes with a challenge, Adoption of artificial intelligence is a challenge for most of these companies due to the high cost of resources required to put in and with a huge bunch of patience to sit and wait for it to reap the profits. However, things have changed forever after the launch of the new and a very less explored market of recommender as a service.

RAAS(Recommenders as a Service) are the companies that provide the no-code & easy to plug platform for such e-commerce websites and apps. Such a platform comes with a functionality to add both Implicit data and explicit data into the platform through API endpoints, CSV import, and Plugins. And Provide real-time content and product recommendation to the audience and engage them! One of such products I came across was Alie.ai provided by a New York-based company at very low prices.