What Impending AI Search May Mean for Digital Shelf Management

As Amazon unveils Rufus in beta, there’s much to ponder about the future of purpose-built retailer AI and its impact on digital shelf management. 

Rufus is Amazon’s take on integrating natural language Generative AI in product searches. Think of it as “ChatGPT for shopping” on Amazon.

By allowing customers to converse with an AI shopping assistant, it is poised to transform the way we interact with ecommerce platforms and find products online.

Evolving the Digital Shelf

Today, consumers use a restrictive set of learned keywords to shop before refining their consideration set with filters and PDP content consumption. 

Gen AI search renews the shopper-centric approach to digital retail. Consumers can interact with a Large Language Model (LLM) to shortcut the search, creating the newest challenge in achieving visibility for your portfolio.

While Rufus is currently in beta for limited Amazon app users (as of April 2024), we know the major sources of information Amazon will leverage – PDP content, consumer feedback, and some external data.

Knowing these inputs allows us to act now to set up for success.

 

1. Embrace clean, clear, and thorough content

If Rufus is utilizing Amazon’s own platform for information, your product’s potential is only as strong as the story you tell on its page. In other words, your content’s quality will directly influence your product’s visibility to more complex, detailed search behaviors.

Brands in general have also leveraged the fact that consumers are naturally drawn to visuals. This practice can be impacted by the developments surrounding Gen AI.

As we discover more about Rufus, we also have to learn how the team behind it is prioritizing the ability to ingest information from images as compared to texts in order to sell effectively.

So, all things considered, your first moves should be focused on:

Auditing Your Existing Content

It is crucial to find and fill content gaps so you can “train” the search on your products. Relevance in conversational consumer search also highlights the need to limit internal jargon or excessive brand-speak. Those might not click with the wider audience or Rufus.

Content for Rufus and Forthcoming AI

We will have to see how effectively Rufus can draw information from images, but it’s also safe to assume system capabilities will vary by retailer system.

If your key product features and selling points are highlighted in images, you will want to ensure they are also reflected in the AI’s source data. This doesn’t mean replacing visual content, but complementing it with what any AI system can read now.

Connecting & Automating Content Optimization

As AI search integrates into retail, the models will evolve to match shifting consumer search patterns.

Winning brands will rapidly optimize their digital shelf with newly highlighted consumer decision criteria observed in AI search chats.

Those brands that rely on manual intervention will encounter a number of challenges, including the potential to miss important consumer insights.

 

2. Understand consumer reviews on Amazon and off Amazon

We have all learned in the age of ecommerce that shoppers around the globe tend to trust the experiences of fellow consumers implicitly.

This collective consumer insight becomes a powerful tool to influence AI search, knowing Rufus is parsing through reviews not just on Amazon but across the web. 

So, it’s important to take action now with a fresh insight into both positive and negative feedback, and pay attention to your products’ place in the Amazon ecosystem.

Issues like product innovation and packaging will take on new significance, as they can be at the forefront of product search.  

Positive feedback points can also be highlighted and reinforced by the brand content as well.  And if these key positives highlight product parity, it signals a moment of strategic action, be it in communications or product innovation.

 

3. Be vigilant against 3P variants, unauthorized sellers, and counterfeits

Since Gen AI like Rufus relies on the retailer’s data, it’s more critical now than ever to ensure the digital shelf positively reflects your portfolio. 

The challenge here is two-fold. While Amazon has made significant progress with AI in fighting fakes, counterfeit items still manage to appear in search results. 

Additionally, Rufus might still be on a learning curve to differentiate real PDPs from counterfeits and obsolete versions – especially considering the complexities of managing “hallucinations” from multiple information sources.

So, what’s your best move? 

Automation again is the best move here, with manual intervention to optimize and complement the automation. 

3P sellers can act faster than a brand can manually fight them. Until we know what exactly Rufus can do in terms of filtering informational inputs, it is safest to assume your PDP content and consumer sentiment will be at odds with 3P duplicate listings.

 

💡If you have not done so yet, it is also important to consider altering distributor and potentially some retailer contracts.  Adding clauses restricting ecommerce marketplace sales can address large volumes of 3P listings at the source.

 

Wrapping Up

Now, we have more questions than when we started: How will AI search transform Amazon Ads? What role does Gen AI search play in Amazon’s goals, like boosting profitability?

Time will peel back the layers on many of these questions and uncover even more. But one thing’s for certain: we’re on the cusp of a new chapter. Instead of a fleeting trend, think of it as the groundwork for a significant shift in retail.

Now’s an inflection point to get your ducks in a row. You will want to ensure the information you provide is not just there, but it’s crystal clear, and continually optimized with as much information as consumers might want to know. 

The steps we take now will shape the path forward, not just for our brands, but for the entire consumer experience.