Chris Bolton, founder Prompt Reviews

Why business reviews matter more in the age of AI

by Chris Bolton

LLMs love reviews and so should you

Online reviews are generally an over-powered and underutilized signal that has a direct relationship on your bottom line.

In fact, a 2025 study by BrightLocal showed that 98% of online shoppers read reviews before making a purchase.

More from the study:

89% of those surveyed said they expected business owners to respond to reviews.

74% said they check at least 2 review sites.

And 83% said they check Google Reviews

Getting consistent, positive reviews increases visibility, traffic, conversions, and more importantly . . . revenue.

I think most businesses could benefit greatly by repurposing the time they spend trying to “win the algorithm” on social media by simply working on their review game–not to mention the intrinsic benefits that come from talking to your customers, but I digress . . .

Why do LLMs care about reviews?

Well, LLMS care about reviews because humans care about reviews (98% of us in fact).

AI tools like ChatGPT, Claude, and Gemini use reviews to understand who you are, what you do, and whether you can be trusted. They analyze customer sentiment to see what people generally love, hate, and feel “meh” about.

With search engines shifting from links and rankings to conversations, reviews have become the connective tissue between your business and the AI models that may or may not recommend it.

It’s less about stars. More about content.

Historically, Google has ranked local businesses based on the number of reviews, the rate at which reviews are received, average star rating, and these things still matter, but AI can go deeper.

When an LLM looks at reviews it can:

  • Spot recurring themes
  • Compare with competitors
  • Analyze sentiment
  • Detect geographic signals
  • Identify outcomes and results
  • Validate expertise and experience
  • Understand trust and credibility
  • Extract Descriptive keywords

For this reason, what your customers say about your business matters more.

And while Google Business Reviews are still one of your most powerful tools for getting found online, LLMs like ChatGPT also look for reviews across a variety of sites in order to get a full picture of your customer experience, your best qualities, as well as your most common complaints.

Freshness matters more

Most modern AI systems are trained on large amounts of data on a periodic basis. This means in order to get the most current information from today, yesterday or last month they need to go out and find it online.

To do this they use RAG: Retrieval-Augmented Generation. RAG works like this:

  1. An AI model receives a question.
  2. It retrieves outside information from search, business profiles, and publicly available sources.
  3. Customer reviews are often the strongest and freshest retrieval source.
  4. The AI blends that retrieved information into its answer.

This means your reviews aren’t just influencing potential customer–they’re influencing AI-generated summaries, comparisons, and recommendations.

For example, if a user asks an AI tool:

“What’s the best taco shop in LA near Echo Park?”

The system will pull phrases like:

  • “best taco shop in LA”
  • “authentic tacos”
  • “affordable and fast”
  • “Echo Park location”
  • “family-owned”

If those phrases appear in your reviews, you get surfaced. If they don’t, you don’t show up.

RAG has made the quality and specificity of your reviews a powerful visibility factor.

Why Keyword Phrases Inside Reviews Matter

AI models extract entities (things like “taco shop,” “web designer,” “Plumbing company”) and qualifiers (“best,” “trusted,” “affordable,” “family-friendly”). They also detect geographic markers like “in LA,” “in Seattle,” or “near Echo Park.”

When a review includes a phrase like:

“This is not just the best taco shop in Echo Park, it’s the best taco shop in Los Angelos. Their adobada is incredible! I go almost twice a week.”

…it produces multiple high-value signals:

  • Category (taco shop)
  • Superlative (best)
  • Location (LA, Echo Park)
  • Dish specificity (adobada)
  • Commitment/loyalty (I go almost twice a week)

Reviews like this become semantic anchors. AI uses them to answer questions, rank results, and generate local recommendations. Without these phrases, AI has no reason to interpret you as the “best taco shop in LA” even if you actually are.

So how the heck do you get your customers to write more reviews, and then to actually include the phrases that will cue LLMs to mention you?

Your customers want to support you—But they need some direction

In order to survive as a small business, you need to make people happy, grateful, satisfied, delighted

. . . and you have to convince them to give you money. (So you’re already performing miracles on a daily basis.)

Getting more and better reviews is a whole lot easier then what you’re already doing, but it does take some practice as well as the right strategies and tools.

Your customers don’t wake up determined to write a stellar review for your business. In fact, writing a review can feel like an inconsequential chore.

Most customers:

  • Don’t know if you even care if they write a review
  • Don’t know where they should write you a review
  • Don’t know what to say if they did write you a review
  • Don’t remember key details about your business
  • Don’t know what is helpful or not helpful to put in a review
  • Don’t know what makes a review valuable to you

And this is where you can help them! Let them know, give them tools, make it easy and painless and they will come through.

This is why I built Prompt Reviews, to help small businesses like yours connect with their customers and grow their online presence by solving these problems.

Here’s how Prompt Reviews can help your customers

  • A delightful user experience for composing reviews
  • By providing context to help customers recall and better represent their experience
  • Provide inspirational prompts that spark creativity
  • Give access to ai-assistance for composing drafts and checking grammar
  • Directing users to the right pages on reviews sites to submit reviews

This leads to richer, more authentic reviews—reviews that work for humans and AI.

AI Needs Context, Not Compliments

AI models don’t care much about:

  • “Great service!”
  • “Five stars!”
  • “Highly recommend!”

Those phrases are nice for social proof, and improving your star rating, but they do almost nothing in AI’s semantic world.

What matters to LLMs is very often the same stuff that matters to humans:

  • What specifically did the business do?
  • What made it valuable?
  • What problem did it solve?
  • Who is the business best suited for?
  • What category, service, or location is being reinforced?

Topic Extraction and Why It Matters

AI systems extract topics from reviews automatically. If your reviews consistently mention:

  • “fast turnaround”
  • “great communication”
  • “complex technical problems”
  • “safe delivery”
  • “gluten-free options”
  • “pet-friendly”
  • “responsive team”

AI will associate those topics with your business.

This affects:

  • Local search
  • Conversational queries
  • Product recommendations
  • Category rankings
  • “Best of” lists
  • Summaries generated in AI overlays
  • Autonomous agent selections
  • and more.

Multi-Location and Multi-Service Businesses Need More Structured Reviews

AI struggles when businesses offer many services or operate in multiple locations. It needs clear signals about:

  • Which location performed the service
  • Which service the customer is describing
  • Which audience segment is relevant
  • Which outcomes are associated with which offering

If a business has:

  • 4 locations
  • 8 services
  • 12 customer types

But all their reviews say is “Great service,” AI can’t build a coherent picture and may just choose a business where context is more readily available.

Prompt Reviews solves this by letting you tailor review collection to focus on a specific service, event, product, even individual employees. Because Better structure and more context = better AI interpretation.

Freshness and Velocity Are RAG-Weighted Signals

AI systems heavily weight recent reviews. This helps them avoid outdated or misleading summaries. If reviews are slow, sporadic, or stale, AI sees the business as stagnant.

PromptReviews maintains velocity with:

  • Automated workflows
  • Timed follow-ups
  • Category-specific prompts
  • Link-sharing QR codes
  • Event-based review capture

You get a continuous stream of fresh, high-value signals.

Authentic Reviews Rank Better

AI is surprisingly good at detecting unnatural patterns:

  • Identical phrasing
  • Too many reviews at once
  • Generic language
  • Obvious incentivization
  • Repetition of the same adjectives

PromptReviews avoids all of that by:

  • Never rewriting reviews
  • Never generating content on behalf of customers
  • Never using templated text
  • Always respecting authenticity

Instead, it gives customers clarity so their voice shines through.

Reviews Shape the Narrative AI Uses to Introduce You

When AI describes your business to a potential customer, it pulls directly from patterns in your reviews:

  • “Customers love their fast turnaround.”
  • “Known for solving complex technical issues.”
  • “Popular taco shop in LA with standout adobada.”
  • “Trusted by B2B companies for strategic web design.”

So yeah, reviews matter more now then ever

They now shape:

  • What AI retrieves
  • How AI summarizes you
  • Which categories you’re associated with
  • Whether you’re recommended
  • Whether you appear in conversational search
  • Whether autonomous agents choose you automatically

Ready to start getting more keyword-powered reviews?

Drop me a line. I wear both “app founder” and “AI Search consultant” hats, so chances are I can help.

Chris

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