Few would deny the globe-conquering vision of Jeff Bezos and Amazon. When others were scoffing at the potential of e-commerce, Bezos was busy laying the groundwork for the world’s first “everything store.”
Yet what if flipping retail from something you do in a store to something you do in your pajamas is only the beginning? What if you could turn the act of online shopping into something truly personalized and social?
How Amazon Scout works
The idea is simple: Today, our impetus for visiting Amazon is generally need-based. When batteries or food supplies run low, Amazon is but a mere click away. Amazon Scout offers consumers a new way to interact with the platform, one that mimics the experience of window-shopping. By liking or disliking products, users receive recommendations from Amazon’s sophisticated machine learning algorithm.
The ultimate goal is to deliver an experience that surprises and delights a consumer. After all, there is little joy in simply ordering a new set of replacement batteries. Yet discovering an item that you never knew you wanted is deeply appealing (just consider how much better a favorite song sounds when you randomly stumble across it on the radio, rather than going through the process of cueing it up yourself).
Amazon Scout is currently in its testing phase, and the company is deploying the service in especially visual product categories such as home decor and women’s shoes. By rolling out Scout, Amazon hopes to outmaneuver Pinterest’s development of “buyable pins,” while also incorporating some of the personalized elements that have allowed e-commerce competitors such as Stitch Fix to carve out a niche in the online retail space.
Amazon is taking on Pinterest: Is your brand ready?
Though Amazon has previously attempted to update their browsing experience with additional curating or personalization, Scout seems to be a broader-focused (and possibly more significant) development. With Scout and Alexa, Amazon hopes to gently guide consumers away from traditional modes of product search into something that’s deeply-informed by their own data and preferences. Amazon’s vast library of visual imagery and a treasure trove of data should make Scout one of the more-powerful recommendation engines of its kind.
Given the critical importance Amazon holds for today’s brands, it’s a smart idea to pay close attention to Scout’s rollout. This means studying how the recommendation algorithm works, discerning patterns and then optimizing (for image quality and other variables) whenever possible.
At the moment, Scout’s usefulness seems somewhat limited, as the algorithm tends to frequently deliver repeat suggestions. Yet as with any machine learning tool, Scout’s performance should improve with use, as more data is collected.
Scout represents the next phase of Amazon’s larger plan to create a more personalized and social shopping experience, and as such, brands should make every effort to leverage this development for their own benefit.
We are ready to help you make that happen. Whether we’re developing powerful Alexa Skills or creating high-impact multi-platform marketing campaigns, BIGEYE has the tools to help brands derive maximum value from Amazon marketing.