Has your brand ever received a negative review about something outside your control? Has a customer’s misconception about your product led to scathing comments on your social media pages?  

Before the age of AI-powered search, these isolated incidents, while upsetting, were limited to a narrow audience and rarely cropped up in search about a brand, its products, or its services. Now that AI search is on the rise, however, brands can no longer ignore consumer conversations. 

AI search engines like Google Gemini and ChatGPT respond to user prompts about brands with all available inputs — including user reviews, online forum discussions, social media posts, content aggregators, and more. Is your brand prepared for AI to shine a light on all customer sentiment, both the good and the bad?  

Here’s how AI impacts brand perception and what you can do to maintain effective brand reputation management for AI search.

Before AI-powered search, prospects and customers searching for a product online most often found a brand’s website and one or two close competitors. They might also see product listings or places nearby to make a purchase, often with an average star rating — but no specific user comments.

AI engines, however, cast a much wider net and are happy to share their findings with any user searching for information about a brand or product. Whereas traditional search engines primarily returned results from brand websites, AI engines are casting a much wider net. They scan user reviews, Reddit threads, and online forums with voracious appetites, ingesting content, learning, and forming opinions about brands. They use datasets licensed from other companies and scan the web themselves, finding every post, every comment, every review, and every tweet.

AI-powered search is a great tool for comparative shopping. Users can quickly ask AI to compare a set of products or services between brands. This is easier than traditional cross-shopping, where a user would need to visit multiple websites to compare features.  

And while your overall review set or brand sentiment may be positive, what if you had a run of negative reviews late last year about a temporary issue with your customer service, and an AI engine chooses to present that to the prospect? What if a handful of customers feel your price is high relative to your competition, and had a lengthy discussion about it on social media? An AI engine could note that shoppers find your brand’s customer service lacking, or that you’re more expensive than others in the market. 

These factors influence how your brand is represented in AI-powered search. Furthermore, AI has been shown to mistake fake or satirical content as real, stating it as fact, which can further exacerbate issues of sentiment and brand image. It’s no longer enough for brands to know if they’re represented in search — they now must also know how they are represented in search, contending with the sentiment and context surrounding AI citations.  

To tackle these new challenges, brands must begin to monitor their presence in AI-powered search. For example, develop a series of prompts to enter into leading AI engines and review responses. Alternatively, partner with an AI search monitoring solution for more robust reporting. 

Brand management strategies come next. Identify any sentiment that doesn’t accurately reflect your brand and its products and build an action plan. Here are a few examples: 

• Review management: Identify sources of negative user reviews and work internally to close gaps and improve the client experience. Respond to reviews quickly while the iron is hot and engage with irate customers directly to overturn opinion and drive a positive experience. Proactively solicit positive reviews from happy customers, both on major review platforms and any platforms where your brand may have a less-than-sterling reputation. 
• Build authority: Develop an authoritative voice on your brand’s owned channels — such as your website, social media channels, and blog —where you can speak confidently about the benefits of your products while addressing common user questions. Leverage AI to gauge what questions consumers are asking, and provide thought leadership in your space, propping yourself above the competition.  
• Revise product descriptions: Dive deep into consumer sentiment about your products and how they compare to the marketplace. What competitive advantages does your brand offer, and how can you build content to attract users? Seek to understand the language shoppers use in their searches and align your marketing and brand language accordingly. 

These are just a few suggestions to pivot your brand toward the emerging world of AI search. Staying informed about developments in this space will enable you to continue to be a leader in consumer sentiment and AI exposure. 

AI presents a brave new world for marketers, full of challenges and opportunities. LLM-powered search places a high priority on user-generated content, folding that data into answers in ways and at scale not seen before in the digital search space. Marketers who are quick to adapt to these changes will influence how customers perceive their brand, while those who ignore this emerging space will be at the mercy of AI engines and user commentary. 

Stay tuned for more updates on emerging trends in AI-powered search and marketing. 

Want to know how an AI-powered distributed growth platform can empower your channel partners to drive results? Explore the Ansira platform to learn more.