Lessons Learned From Amazon’s Marketing Personalization




  • — December 1, 2016

    How Amazon is using market Personalization


    It is no secret that Amazon is a force to be reckoned with when it comes to marketing personalization. Amazon dominates the e-commerce market because of its ability to personalize content to each individual across the entire customer journey. They have perfected the personalization of the shopping experience by connecting the dots between customer interests and creating customer-centric campaigns tailored to the right individual at the right time and place.


    We all know that Amazon’s personalized marketing emails and use of big data create a truly unique experience. Let’s take a look at the other factors involved in Amazon’s perfectly personalized model.


    1.Seasonal Personalization


    Amazon becomes an e-commerce powerhouse during the holiday seasons. Why does Amazon see such a dramatic spike in sales during the holidays? Amazon’s personalization strategy focuses on analyzing browsing history and past behavior. Amazon uses this data to generate the most relevant recommendations for each individual. Amazon weaves seasons and holidays into their recommendation algorithms to maximize the effectiveness of these recommendations.


    For example, Christmas holiday season is more about buying products to be given to other people. Customers tend to focus more on the interest of their friends and family, rather than their personal interests. Amazon recognizes this change in customer behavior. They shift their recommendations to feature more products based on past behavior during Christmas holidays and products that are popular during the holiday season.


    2. Wisdom of Crowds


    The opinion of the many can be the most effective personalization technique. >

    Use the wisdom of crowds for more effective personalization.


    The wisdom of crowds refers to the concept that the many are smarter than the few. Essentially, the collective opinion of a group of people is more valuable the opinion or beliefs of a single expert. Amazon does a fantastic job of leveraging their massive user base to benefit the company and increase personalization. Amazon is driven by user opinions and reviews, focusing on what the customers want. It is that collective opinion on what is desirable, which allows Amazon to personalize products to each customer. Amazon applies this wisdom of crowds towards market segmentation, employing the power of “segments of one.” With this strategy, Amazon has been able to divide their large customer base into groups and categories based on shared characteristics. From there, Amazon uses the wisdom of crowds within each group to create a personalized user experience while involving popular products relevant to each customer.


    3. Recommendations


    As a retailer, the goal is to provide relevant products to consumers. Amazon focuses on products they know customers will be interested in purchasing. Amazon’s personalization techniques have enabled them to understand each and every customer. They can then tailor their web pages towards each specific customer. This means that Amazon knows exactly what a customer has looked at, and what to recommend based on their behavior. Why is this a successful method? Once a customer has hit the checkout button, they are in the “buy now” state of mind. Amazon’s personalization has enabled them to recommend products to customers while they are still in that “buy now” mentality. The most important part of their process, though, is that Amazon recommends these products after purchasing items. They are careful not to break the buying mentality, so as to not risk a customer converting or returning products.


    There are a plethora of lessons to be learned from Amazon’s successful personalization strategy! They key to their success and dominance in e-commerce lies heavily on the idea of a personalized shopping experience. Your company can implement these winning strategies by using a personalization solution.

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    Author: Amrit Kirpalani


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