Local business discovery is changing rapidly. Consumers are no longer relying on a single platform to find and evaluate businesses, and the rise of AI is accelerating that shift.
New data shows nearly half of consumers now use generative AI tools for local recommendations. At the same time, expectations around ratings, review quality, and trust are increasing.
AI is the starting point – not the final decision
Consumers are increasingly using AI for recommendations, but they still want those recommendations to reflect the truth. AI is becoming the starting point for local business research, not the final authority.
This makes a local business’s presence across review sites more important than ever. Our recent survey found that 74% of consumers only care about reviews from the past three months, so if the business has a weak or outdated presence on the review site, this will inevitably widen the trust gap with the consumer during the decision stage.
Rising expectations are resetting the bar
Two forces are driving the sharp rise in consumer expectations, the first is economic anxiety. The global economy is facing rising prices and some industries are seeing a decline in product quality, so consumers have been far more protective of their spending. A 4.5-star rating now acts as an insurance policy against wasting hard earned cash on below average businesses or services.
The second factor is rising expectations. As businesses actively improve their reviews and ratings, the bar keeps climbing, while AI-driven search surfaces fewer choices. The result: consumers are seeing fewer low-rated businesses than ever before.
I believe this is a permanent reset. I don’t expect AI to change how it combs reviews, and I don’t foresee consumers settling for less – especially if the services they receive live up to the online reputation.
Fresh reviews are now essential
In the SEO industry, we have often been guilty of using the wrong language when it comes to online reputation. We talk about ‘getting more reviews’ rather than building trust and reputation in our businesses. The downside of this, is that it reduces a long-term, strategic business imperative to a narrow tactical exercise.
While a business does need a system in place that generates a consistent flow of recent feedback, it’s vital that your customers are being listened to. Your staff can play a critical role in this. Train and coach employees to give them important context on reviews and help build their confidence. As consumers are more likely to write about a positive experience, incentivise staff with rewards based on reviews generated and ratings.
To help make this practice feel more natural for employees, feedback could be embedded into existing practices such as email, SMS, adding links to a receipt, etc., so it becomes a natural step of service delivery.
From single platforms to “Reputation Everywhere”
It is vital that businesses understand exactly which platforms their customers use to find and select services. While many have relied on a ‘Google only’ or ‘Google mainly’ strategy in the past, we’re seeing a shift. In this year’s Local Consumer Review Survey, we found that consumers use an average of six review sites, meaning reliance on the major review sites is no longer enough.
As we move into this new era of local discovery, businesses need to do three things:
- Adopt a ‘Reputation Everywhere’ strategy, moving away from a single-platform focus to ensure success. Businesses should build their authority not only across Google, but also the specific sites where their customers and even AI models spend their time. By showing up at every possible point of discovery, a business will establish trust with its customer base.
- Invest in video-first platforms like YouTube and TikTok, especially for younger consumers.
- Promote their business where customers actually spend their time. Diversification is essential, but it must be balanced by keeping Google at the core of their efforts.
Optimising for AI means controlling the inputs
Since businesses are unable to control how an LLM summarizes their reviews, they need to focus on the quality and consistency of the ‘ingredients’ the AI is consuming.
Start by eliminating any inconsistencies. Inaccurate data or conflicting review sentiments create a trust gap. When an AI isn’t confident in the information it finds, it is likely to overlook that business entirely.
A steady cadence of reviews is also critical. Businesses need a steady flow of reviews that ideally come in on a weekly or monthly basis, ensuring that both the training data (used to build the model) and the retrieval data (used for fresh web updates) reflect a current and accurate picture of the business. A business’s ‘Reputation Everywhere’ approach should include the specific niche or major sites (e.g. Yelp) that LLMs actively crawl for local sentiment.
Trust still sits with the brand
AI still faces credibility issues due to its tendency to hallucinate or generate fictional information rather than fact. Ultimately, the responsibility for establishing and maintaining trust and reputation lies firmly with the brand itself.
Brands must ensure that wherever customers find information about them, they have made every effort to manage it effectively. Negative reviews should be countered with positive ones; content on owned platforms should consistently highlight the services offered and quality delivered.
It’s up to the brand to manage its presence thoroughly across all mediums. If done right by being complete, consistent, and clear, then AI platforms will also accurately reflect this information based on their data sources.
