How AI is transforming eCommerce and user acquisition models
Amazon has unveiled a new AI-powered search assistant called Rufus, billed as unprecedented and bound to change how consumers find what they’re looking for on the e-commerce giant.
Instead of a mere presentation of choices of products, Rufus is designed to engage them with their queries in a more personalised and conversational manner.
This is somewhat parallel to Google’s Hummingbird update in 2013, wherein the query behavior changed from short inquiries with keyword-sounding phrases to longer and more natural-sounding queries.
Rufus represents an important evolution in search because it aims to usher the consumer through a much more detailed discovery using AI.
If that’s the case, Rufus will alter how brands approach e-commerce optimisation and customer interaction.
Why do we care so much about the impact of Rufus on wider eCommerce?
The importance of Rufus’ launch can be understood by looking at current consumer behaviour regarding online product searches. A survey from 2023 by PowerReviews reports where shoppers start their product-related searches:
- Amazon: 50%
- Google: 31.5%
- Retail or brand websites: 14%
- Review websites: 2%
- Social media: 2%
But all this changes for Generation Z. For this demographic, Google beats Amazon, but only just:
- Google: 38%
- Amazon: 36%
- Social media: 5%
While Amazon still leads overall, younger shoppers start searching on Google. Even social media platforms like Instagram and TikTok are gaining traction as new places to commence a search.
With all this in mind, that puts Rufus into the marketplace at a very pivotal point when shopping habits are shifting to more personalised, interactive search experiences.
How Rufus Works
While traditional search engines simply display a list of products for users based on keywords, Rufus is going to be far more interactive and personalised.
Rufus uses generative AI, answering questions from users by drawing from customer reviews, product descriptions, and much more. Some of the main ways Rufus works differently are:
- Natural language processing: Rufus moves from short, product-focused searches to more descriptive, long-tail queries. Users can ask more conversational questions like “best budget laptop” or “highly rated fitness tracker under $100.”
- Customer review integration: Rufus pulls heavily from customer reviews, responding with insights into how other shoppers have experienced a product. This is all the more reason why brands need to make sure of a good review profile.
For those businesses that want to optimise their product listings for Rufus, here are a few key steps:
- Improve Product Listings: Product titles, product descriptions, and product specifications have to be full and clear. It’s from this information that Rufus draws out facts for a comprehensive response.
- Customer Reviews Management: Since Rufus builds reviews into responses, customer feedback management is not just desirable but a must. Response to reviews and maintenance of a positive profile may impact the way products are shown to shoppers.
By listening to and responding to customer questions in the discovery phase, Rufus presents a fantastic opportunity for brands to improve and fix their product listings in real time and to avoid waiting for customers’ post-purchase feedback.
Changes to Search Metrics and Advertising Strategies
As Rufus gains traction, it’s likely to change how people search, as well as the key metrics with which brands measure success in e-commerce.
Traditional metrics like share of voice will likely decline in favor of more AI-personalisation-driven metrics at the end of the growth curve.
That’s because Rufus’ one-on-one conversations with customers will pressure brands to reconsider exactly how they are measuring the performance and impact of their search strategies.
The following will be some of the metrics that might gain more traction in this new AI-driven search landscape:
- Lifetime value (LTV): This will be a crucial metric as brands look at building long-term relationships via personalised search experiences.
- New to brand acquisitions (NTB): Knowing how many new, first-time customers are coming through because of AI-driven searches will give an idea of the business growth potential.
- Path to purchase measurement: Understanding how clients navigate the discovery and purchase process will be extremely valuable and will give important insight into the effectiveness of Rufus.
Where traditional search strategies focused on driving non-branded, top-of-funnel queries might have been effective in the past, that approach is likely to become less effective as Rufus’ personalised, conversational search capabilities continue to roll out.
Brands will have to evolve towards more specific, intent-based queries and new ad formats.
The conversational interface that Rufus uses could be another way to bring a new breed of ad experience whereby sponsored ads could actually feature within these AI-driven response pages.
Looking Ahead
Rufus represents a sea change in the way search operates on Amazon and is part of the larger trend of AI and machine learning that is informing the future of e-commerce.
Competitors, including Walmart, are also launching similar AI-powered search tools, further solidifying the future of online shopping around highly personalised, conversational search experiences.
Aside from the immediate effect it will have on how users search for and find products, Rufus is a big opportunity for brands to better understand customer preferences at the time of discovery. Businesses can make sure to make appropriate product title, description, and even packaging changes once they’re aware of how consumers ask about their products prior to purchase.
In other words, Rufus is the next stage of e-commerce search. It uses AI, natural language processing, and customer data to make it all much more intuitive and user-friendly.
As brands learn how to optimise their strategies for this new paradigm of search, Rufus is set to reshape the metrics that matter and the ways we shop online.