If you run any local business, you know the buzz: a new
five-star review is up, and you are in cloud nine of social proof; but one
negative review? That will rather feel like someone spray-painted a bright
yellow tag onto your storefront reading, "AVOID AT ALL COSTS."
Over the past two decades, we have gone on a journey,
beginning with flipping through the Yellow Pages, then drifting across Google
Maps, to finally reading AI-generated summaries today. In the current search
terrain, we are wading through a quagmire of acronyms beyond SEO — namely GEO
(Generative Engine Optimization), AEO (Answer Engine Optimization), and the
upcoming LLMO (Large Language Model Optimization). At the root, all of these
are still machines' SEO, which synthesizes information and does not simply rank
web pages.
Local reviews have lost their status as a side benefit;
today, they are key to an entire local SEO strategy and visibility scheme.
Reviews team up with various other local signals, most importantly, your Google
Business Profile (GBP), other local citations that also must remain accurate
and up to date, and anything else you can think of. In the AI-dominated search
environment, all aspects of your online presence—from your online reputation to
social proof—become tens of thousands of data points to be conformed to machine
evaluation.
That is one major change; we do not just rank websites or
local listings anymore; we feed the machine-learning models synthesizing
information from your reviews, your site, third-party listings, social media,
and more. These systems do not just crawl and index; like search engines do,
they answer predicted language patterns based on stuff they saw across the web,
courtesy of your reviews. They return answers based on trends, sentiment, and
context. Now, what people are saying about your business and how they say it is
really very crucial.
Here are the three major ways in which LLMs will be
leveraging reviews to influence when and if AI-powered search experiences
recommend your business.
1. Sentiment and authenticity: LLMs read between the stars.
LLMs put each review rating through its paces, investigating
all shades of opinion to identify customer satisfaction or dissatisfaction or
the trustworthiness of the review. An authentic, positively biased review is
implicitly understood thus by models to be a trustworthy indicator of
reliability toward thrusting the vendor to advanced ranking in their summaries.
If a review fails to convey emotion, the 4-star one can be arbitrated upon by
the model to be greater than a 5-star review, which would say, "This is
truly good."
LLMs, moreover, do assess beyond a straight opposition
between “good” and “bad,” moving on to identify entities and link them to
sentiment descriptors:
It is nothing more than a very sophisticated pattern
recognition tool. For example, if repeatedly you start getting reviews about
being “unprofessional” in service, forget about your star ratings. This is my
first admonition: do not attempt to jump the line here and load the listing
with fake reviews, for Google will rightly flag them.
Let’s see some cases in point. The screenshot below shows
how Chat GPT has selected this dentist in London based on "reviews,
recommendations, and local popularity."
Get on top of reviews to minimize surprises due to negative
testimonials that are either exaggerated or outright false due to spam by
unprincipled competitors. Don't let reputation in your industry suffer
unduly from spam.
2. Volume & recency: The "Is this business still alive?"
signal
A regular stream of recent testimonials sends positive
signals to LLMs about a business's reputation and reliability within a local
market. LLMs favor businesses that feel active. A constant stream of new
reviews signals ongoing dealings, current service delivery, and operational
credibility to customers and the models assessing reputation. Thus, for models
intended to offer trustworthy recommendations in real time, a fabric of recent
social proof is of utmost importance.
While AI Overviews often source their analyses from
listicles, the commonality among the winning recommendations is not just
placement, but rather a steady stream of fresh, high-quality reviews. What's
even telling: The linguistic styling of those star Google reviews often closely
matches the wordings of the AI-generated summaries.
Pro Tip: When it comes to marketing, providing the greatest
services to your customers is the very best approach, so make sure that you lay
down the workflows, via emails, SMS, and even face-to-face people gathering
testimonials. Make it a habit to respond constructively and quickly to every
review, whether it is from an angry customer who wrote in all caps or one who
praised your services. Even add-ons from local marketing utilities such as Moz
Local are explicitly created for monitoring reviews and responding to them in
real time.
Never Miss Another Review
Moz Local makes the process of managing reviews easy. And
you can get back to running your business!
3. Keyword relevance: Why rich reviews are gravy for LLMs
An astonishing fact: some of the best signals you can send
to both Google and AI models about your business are those that come out of the
content of the reviews. For instance, your site may list HVAC repair as a
salient service. But review text in your Google listing may elaborate, stating,
"They repaired my broken AC unit, during the middle of a heatwave in under
an hour-exceptional service!" This kind of review works as a signal in 4
ways:
• A service
term (AC repair)
• A product
context (AC unit)
• A
customer sentiment ("exceptional service")
• A
positive outcome (repair done in an hour, with no complaints)
With that added depth actually comes better and richer
contextualization, giving the LLMs much more useful context. The review,
instead of just supporting your service, lends additional organic relevance to
your business listing, almost like tagging on an additional category.
These keyword-rich testimonials may themselves contain some
copy that might trump the published content on your website. LLMs scour reviews
for mentions of products, service details, location, and contextual hints that
would align with any given query. Highly descriptive and relevant reviews can
really prove to be your secret weapon here.
Pro Tip: While you can't put pen to paper for your
customers, you can guide the narrative of their reviews by providing unmatched
service and asking for specific feedback. An example would be encouraging a
local fine-dining restaurant to ask customers for feedback regarding their
meals, ambiance, service, and other key features that could swing things to
their side and pull in a rich mix of foodies. A few other suggestions that
encourage more reviews include:
• Ask
specific follow-up questions: “What did you enjoy the most?”, “What impressed
you most about our service?”, etc.
• Offer QR
codes or short URLs on receipts or signage that directly lead to your listings
(e.g. Google Business Profile).
Searching additional bright ideas to elevate more reviews?
Please check out the Local SEO courses in Moz Academy.
Recap: Common review pitfalls that hurt visibility
To secure the trust of LLMs and users, steer clear of these
mistakes that would ultimately prevent any worthy recommendation of your brand:
• Publishing
fake reviews: As mentioned, this can lead to being flagged and subsequently
harm the reputation of your brand.
• Not
responding to complaints: Silence by itself leans toward negligence, so best of
luck to you in getting back to users who are genuinely complaining.
• Only get
reviews from Google: Collect reviewer opinions from diverse places,
particularly those that are most frequented in your niche.
Future prospects-LLMO is the new local pack
Search is no more about traffic and clicks; it has become
visibility, representation, and exposure of your target audience on whatever
platform they are using. In this AI-dominated world, some users begin querying
LLMs & search engines for their summarized answers and not a bunch of links
to review.
This is how the view into the future may play out:
• AI chat interfaces blow up and garner users another entry
point into searching beyond traditional search engines.
• LLMs will continue to improve by surfacing the most
relevant recommendations based on prominence, customer sentiment, and context
clues.
• Mentions of brands and user-generated content across the
web will become signals specifying the significance of having reviews across
various platforms.
At the end of the day, local SEO is not dying. ChatGPT,
Gemini, or Claude are all interfaces for the users to do their research;
optimization of these sources that they would most use to recommend local
businesses would be the most important thing.
Stop losing business to your competitors
Dominate local SERPs with Moz Local
Conclusion: Reviews are signals, not silver bullets
LLMs will reward clarity, consistency, and credibility in
the battle for local search. Reviews are an important piece of the puzzle to
maximize your business presence, yet do not expect them to sprinkle down from
the skies. This is not something that can or should be gamed, but it can be
guided. Instead, work on collecting meaningful, descriptive, timely reviews for
all of your local listings. Here are some action steps to put into place:
• Audit your latest reviews: How many reviews do you have
over the past 90 days? If customer testimonials have dried up, that's not a
good sign.
• Respond to all reviews: Now, engage with your customers
and show Google and LLMs you're keeping up with testimonials.
• Encourage customers to share specificity: Ask your
customers to leave in-depth, context-rich reviews related to your target
keywords.
• Cover all major review platforms: "To Google"
has become part of vernacular English, but don't get so nearsighted with local
marketing. Include as many relevant platforms as possible.
• Centralize your strategy: By using something like Moz
Local, you can supercharge your listings, monitor reviews, respond to
customers, track your local rankings, and post across social media
platforms-all from one place.
Next time someone asks ChatGPT or googles on for the best
[insert your service] in your locality, ensure that the recommendation is for
your business.
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