E-commerce juggernaut Amazon has announced its latest foray into the virtual assistant space with the launch of shopping assistant Rufus.
It may sound like the name of a particularly fluffy puppy, but Rufus promises to transform customers’ experiences by answering questions on shopping needs, products, and comparisons.
The tool will be integrated into Amazon’s existing customer portals, and equipped with knowledge and data on its full catalog of products.
Moreover, Rufus will have access to customer reviews and community Q&As, allowing it to make informed recommendations to shoppers.
All these capabilities are on display in the video below.
Powered by generative AI, Amazon describes Rufus as an “expert shopping assistant” that will enhance the shopping experience by making it easier for customers to locate the best possible products to fulfill their needs.
Initially being introduced within the Amazon mobile app in beta for a selection of US customers, the plan is to release the assistant in waves – making it available to all US shoppers in the next few weeks.
But how will it be received by users? And will it really be the game-changer that Amazon has promised?
In Practice
Like many technological innovations, it is difficult to get a true understanding of the product until you can sample the software for yourself – the digital version of kicking the tires, if you will.
Those of us of a certain age will all remember being told by a friend about this incredible new video game called Grand Theft Auto V – but hearing about it could never do justice to the thrill of your first five-star police chase.
Unfortunately, with no set date on when Rufus will be starting its global tour, shoppers outside of the US will have to make do with some of the practical examples that Amazon provided in their press release.
From Provider to Researcher
One of the biggest ways in which Rufus will change the shopping experience is by housing the research and purchasing elements of e-commerce in one place.
Every shopper will have experience of wanting to purchase an item but not being completely sure which product is the best fit, whether it be for a new hobby, an event, or ethical reasons.
With Rufus, rather than flicking through hundreds of conflicting web results, shoppers can ask questions directly within the app, such as “what are clean beauty products?” or “what do I need for cold weather golf?” They will then be provided with suggested product categories, helpful information, and related questions from other shoppers.
This feature expands beyond making product filtering more seamless; it also allows users to ask for more niche recommendations, like “what should I buy my boyfriend for his 30th?”
But Rufus actually takes this a step further by letting customers ask questions about specific products.
The examples that Amazon gives are queries such as, “is this jacket machine washable?”, or “is this cordless drill easy to hold?” The assistant will then use the aforementioned data from customer reviews and Q&As to provide answers and suggestions.
With the launch of Rufus, Amazon is clearly intent on providing customers with a more universal end-to-end experience. By combining its considerable stores of customer data and feedback with a GenAI-powered assistant, the e-commerce giant can be present throughout the entire customer journey.
In discussing Rufus, Rajiv Mehta and Trishul Chilimbi – Amazon’s Vice President of Search and Conversational Shopping, and Vice President and Distinguished Scientist of Stores Foundational AI, respectively – commented:
With Rufus, customers are now able to shop alongside a generative AI-powered expert that knows Amazon’s selection inside and out, and can bring it all together with information from across the web to help them make more informed purchase decisions.
Amazon also offers the opportunity for businesses to build conversational experiences of their own via Lex – its conversational AI platform. Lex comes with several GenAI-powered features, as outlined in our article: AWS Demonstrates How to Augment Lex With Generative AI.
