CASE STUDY: Amazon
Amazon is famous for it’s personalization and has been using a product curation and recommendation algorithm for many years. They have been hailed as one of the first ot play heavily in this space and we can continue to learn from them. Although more sophistication will be required as they move forward.
Amazon has worked hard to understand it’s consumers through data and makes recommendations based on a number of factors. Clearly there is a correlation between personalized recommendations and increased sales. This can be in the form of direct purchases through the recommendation itself, sharing products with friends (as friends often share similar interests to you) or in increased usage of the app due to the likelihood that you will find what you want with ease (even if you didn’t know you wanted it).
Amazon personalizes through a number of routes and this is an important lesson. Personalization is not simply adding a name but true personalization in the digital age is about about understanding your user and giving them a unique offering. Amazon’s recommendations include:
– People like you bought…
– Recommendations for you…
– Your Dash buttons (a product they promote)
– Continue searching for…
– Categories you regularly search in
– Review your purchase
– Inspired by your shopping trends
– Inspired by your wishlists
– Customers who viewed this item also bought
– Frequently bought together
And many more that rely on data and trends.
The results are clear. Today Amazon is one of the largest businesses in the world and this is in now small part due to their use of digital personalization. The power of this tool, if implemented as fully and effectively as Amazon did is enormous.
All businesses today should have a clear data strategy and their data managed effectively. It is totally unacceptable to be in any other position. Using this data then to create effective personalization strategies is a must within any digital strategy and should be central to everything you do from content to platforms.