Personalized recommendation: One size doesn’t fit all!
“Personalization” is the buzzword doing the rounds today and retailers are in search of magic bullets.
Although personalization extends to much more than just welcoming back a returning customer, Amazon is still the 800-pound gorilla in the room when it comes to personalized recommendation in the e-tail space.
For a long time now, Amazon has been providing us a personalized user experience, with product recommendations based on browsing and transaction history. They have been the frontrunners of user analytics and personalization – delivering sharp product recommendations and displays of relevant offers.
The holy grail
It’s well established that today’s discerning shoppers want their favorite retailers to tailor promotions and communications to their individual purchasing habits. Retailers are focusing on elevating the shopping experiences for their consumers and at the same time simplifying the shopping process through the use of various digital experiences.
Today, it’s about using what data retailers have about customers to create an engaging experience that encourages the customer to take action and/or come back again, online or offline. Subsequent personalization campaigns can encompass an extensive area of online and offline media, including: web site optimization, segmentation, email marketing, merchandising and promoted messages.
Often retailers who have been successful in offering personalized interactions have built their strategies on the back of robust predictive analytics technology. Some have tried to meld their brick-and-mortar operations with faster-growing e-commerce operations.
An example would be a clothing retail brand which successfully harnessed analytics so that shoppers are provided with personalized style recommendations, consultants, in-house stylists and style recommendation apps, all under one roof.
Diving into data
Joining forces with solution providers to establish personalization strategies, retailers are focusing on collecting and analyzing customer data. Personalization platforms use a consumer’s Social Data, along with NLP, Machine Learning, Semantic Technologies and Predictive Analytics to predict consumer behavior, personalize user experience and provide actionable insights to retailers.
Whether the initial goal is to drive conversion rates or simply raise awareness of a product release, personalization efforts ultimately are designed and executed to influence individual consumers purchasing habits.
Analytics is thus enabling retailers to provide a stellar customer experience and the future looks bright with new and shiny offers!
Author – Dr. Solomon Pushparaj
Dr. Solomon Pushparaj heads the Analytics Team in EdGE networks. With over 15 years of rich analytics experience, he has implemented predictive analytics and machine learning projects for various clients in Retail, Automobile and HR domains.
His solutions helped clients see impact in areas such as reduction in promotion costs and employee attrition. He has done his research in the field of Hybrid Machine Learning and he has two publications in international journals.
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