How can hyper-personalization help to grow online retail business instantly?

Posted On November 11th 2020

Marketing strategy took a paradigm shift from being 'product-centric' to 'customer-centric' as consumers started seeking personalized retail experiences. We are living in a technologically literate environment, where information is just a click away, and consumer behavior relies heavily on reviews, influencers, and user-generated content. To improve retail conversions and to retain brand affinity, brands must invest in the right technology and infrastructure to support hyper-personalized product content to engage their customers and increase eCommerce sales conversions.

Is Hyper-personalization the need of the hour?

Rising customer expectations and the growing popularity of omni channel retailing along with technological advances in data analytics has made hyper-personalization a top corporate priority for global retailers in 2020.

And yes, hyper-personalization is the need of the hour because:

1. Customization strengthens client engagement

It holds true for retail brands where personalized product recommendation has shown to increase e-commerce sales conversion.

For example, the e-commerce giant, Amazon has mastered the art of providing personalized product recommendations and a seamless shopping experience with hyper-personalization and predictive analysis. They offer a personalized homepage for each of its customers based on their shopping history, wish list, and items selected in their shopping cart.

2. Customer loyalty through personal communication

Every customer is unique. On that note, crafting personal communication based on their needs will ensure meaningful interactions and retain customer loyalty. For instance, Starbucks focuses on creating personalized customer interaction programs to establish an emotional connection with the brand. As per Fortune's most admired companies list for 2017, Starbucks stands third. This shows how the brand has been able to engage with their market by implementing personalized strategies.

3. Customer retention with personalized recommendations

AI-driven recommendation engines help in extracting and analyzing customer data and help to generate recommendations based on the viewer's history, preferences, content type, etc. This has largely supported various OTT platforms significantly in custom curating the watchlist for its subscribers.

Video streaming behemoth, Netflix, for instance, added 15.8 million subscribers in the first quarter of 2020 and registered a quarterly revenue of $5.77 billion. This tremendous growth was largely driven by the personalized OTT recommended watch list provided by Netflix, as more people were in home confinement with the lockdown.