Why Reviews Are Becoming Important in the Era of AI-Recommended Businesses

The way we search for businesses is changing little by little.
Until now, it was common to search for keywords on Google, compare the businesses displayed in search results or on Google Maps, and then check websites, photos, and reviews to decide where to go.
Of course, this way of searching will not disappear suddenly.
However, with the spread of generative AI, the option of narrowing down candidates while consulting with AI, rather than just 'searching by entering keywords yourself,' is beginning to increase.
For example, here is how you might ask.

• What are some restaurants that are easy to visit with children?

• What are some hair salons that are easy to consult with even for a first-time visitor?

• What are some vehicle inspection shops where the staff is polite?

• What are some shops where the customer service is highly rated in reviews?

• What are some shops that help with choosing gifts?

This is a much more consultative way of asking than the conventional 'region name + industry' search.
In response to such questions, AI organizes and presents businesses that seem to fit the criteria while referring to information on the web and Google Maps.
When considering this change, Google Business Profiles and reviews become important once again.
Until now, reviews have mainly been treated as 'evaluation information' that users read before visiting a store.
That role will not change in the future.
On the other hand, it is thought that the presence of reviews will also increase as an information source for AI to understand stores and organize their characteristics.
I believe this is a quite significant change.

1. Information on Google is increasing its presence as a reference source for AI

There is an interesting study when considering the changes in AI search.
According to an analysis of Google AI Mode published by Profound, between April 15 and June 30, 2026, the citation share of google.com increased 8.4 times, making it the second-ranked citation domain in AI Mode.
Driving that increase were information areas that Google itself owns and displays, such as Google Business Profiles.

Reference:
Google AI Mode's shift to citing itself

For store businesses, this is a change that cannot be overlooked.
Until now, the emphasis has been on having users come to your own site from search results and conveying the store's appeal and service content there. The importance of your own site will not change in the future.
However, in AI search, there is a possibility that cases where users complete a certain amount of comparison and judgment by looking at information on Google or summaries by AI before visiting the official site will increase.

We also actually investigated the citation sources of AIO for a certain hair salon.

We asked AI multiple questions regarding store selection, such as 'region name + recommended hair salon,' and aggregated the domains cited in the answers.
As a result, the most frequent citation source we could confirm this time was google.com. Checking the citations, store information from Google Business Profiles was referenced, with 36 citations. Next was Hot Pepper Beauty with 18 citations, and citations for the company's own site were relatively low, resulting in Google citations being overwhelming.
Of course, this is one example targeting a specific hair salon and set of questions. It does not necessarily mean the same results will occur for all industries and regions.
Even so, when we actually investigated, Google Business Profiles were cited more than I imagined. This is a point that left a strong impression on me personally.
AI does not introduce stores by looking only at official sites. It constructs answers while crossing multiple information sources, such as Google Business Profiles, beauty portals, and official sites.
That is precisely why it is important for stores to keep not only their official sites but also the information and reviews on their Google Business Profiles in order.
To put it a bit bluntly, it means that there will be more situations where 'conveying appeal only after having them come to your website' will be too late.
From the store's perspective, it has become impossible to ignore not only 'what to write on your own site' but also 'what information exists on Google and how it is read.'
It will likely strengthen its role as an information foundation when AI understands stores, compares them with other stores, and introduces them to users.

2. Google Maps from a 'Store List' to a 'Contact Point for Consultation, Questions, and Summaries'

The role of Google Maps is also beginning to change.
Until now, Google Maps was a place where users searched for 'nearby restaurants,' 'region name + hair salon,' or 'station name + clinic,' and compared stores themselves from the displayed list.
Currently, features have been added where AI organizes store information and helps with judgment.
This flow can be seen by dividing it into three major parts.

Ask Maps: Consulting AI for finding places

Google introduces 'Ask Maps' as a new feature of Google Maps on its official blog.
Ask Maps is a feature where AI combines multiple pieces of information to answer when a user asks questions about places or routes.
As of the announcement in March 2026, it has started to be provided on Android and iOS in the United States and India. It is necessary to consider it separately from the current provision status in Japan, but it is a feature that clearly shows what kind of experience Google is aiming for in the future.
Google explains that Google Maps analyzes information about over 300 million places and reviews from over 500 million contributors.

Reference:
Google Official: Ask Maps / Immersive navigation
Not just opening a map and looking at candidates, but consulting 'Where is a place that fits my criteria?'
Google Maps is expanding toward such usage.
Personally, I think this is the part where the experience of searching for shops will change significantly.

Asking questions about places: Resolving doubts on the store page

Not only overseas-first features like Ask Maps, but even within Japan, the experience of asking questions about places on Google Maps is spreading.

For example, what users are concerned about are things like the following.

• Is there a parking lot?

• Is it easy to enter with children?

• Is a reservation required?

• When are the busy times?

• Do you offer takeout?

• Can I consult with staff while choosing products?

In the past, you had to search for official websites or reviews yourself and read through the relevant information.
Moving forward, we will likely see more situations where people ask questions on the spot while looking at a store page to resolve their doubts.
This is convenient, isn't it?
On the other hand, from the store's perspective, if the information a user wants to know does not exist on Google, the AI cannot answer it. The importance of registering information is greater than ever before.

Google Summary: Seeing Features Before Reading Reviews

Google is also strengthening its features for summarizing and displaying information about stores.
The official blog for Japan introduces review summaries by Gemini and "Place Tips," which analyze reviews and online information to display insights.
Before a user reads all the reviews, the store's features and points of note, organized by Google, are displayed first.
Until now, users had to read and compare multiple reviews themselves to judge things like:
"The customer service seems good,"
"It seems usable even with children,"
"The wait time might be long."
From now on, there will be more situations where Google and AI take on some of that organization.
Ask Maps, the feature to ask questions about a place, and review summaries.
Although these are separate features, they are heading in the same direction.
Google Maps is starting to change from a place to simply find stores to a place to consult about, understand, and compare stores.
And one of the sources of information that supports this experience is the reviews accumulated in Google Business Profiles.

3. Reviews are a clue to knowing the 'actual customer experience'

So, why are reviews important?
The reason is simple.
Because reviews contain the actual experiences of users that cannot be understood from the store's explanation alone.
Stores can say the following on their Google Business Profile or their own website:

• Customer service is polite

• Safe for first-time visitors

• Easy to use even with children

• We support your product selection

However, to put it a bit harshly, this is ultimately just a self-introduction from the store side.
On the other hand, if reviews say:

• The staff explained things kindly

• I was able to use it with my children with peace of mind

• It was easy to consult even for a first-timer

• They explained the differences between products in an easy-to-understand way

• The wait time was short, and the process was smooth.

If there is content like this, it becomes material for understanding what kind of experience is actually being created at that store.
This is useful for people to read, and it is also helpful for AI when organizing the characteristics of a store.
To avoid any misunderstanding, I should mention that Google has not officially stated that they 'value specific reviews more highly.'
What I want to say here is that as AI increasingly analyzes reviews and information on the web to create hints, answers, and summaries about locations, the information contained in reviews itself becomes material for understanding stores.
What can be understood from a single phrase like 'It was good' is inevitably limited.
On the other hand, if it is written that 'It was my first time, but they explained the differences between the products one by one,' the characteristics of that store's customer service and suggestions become visible.
Reviews are not just comments that supplement star ratings.
They express the actual customer experience occurring at the store.

4. Not just 'whether it is evaluated,' but 'what is being evaluated'

When looking at reviews, I think the first thing most people check is the number of stars and the number of posts.
I check that first too (laughs).
The fact that star ratings and the number of reviews are important will not change in the future.
Stores with low ratings or extremely few reviews may become a source of anxiety when users are comparing them.
However, in situations where AI recommends stores, not just the height of the rating, but 'what about that store is being evaluated' will become more important.
Even for stores with the same 4.3-star rating, the content written in the reviews varies.

• Stores where customer service is evaluated

• Stores where the clarity of pricing is evaluated

• Stores where support for those with children is evaluated

• Stores where professional proposal ability is evaluated

• Stores where ease of access is evaluated

• Stores where product selection is evaluated

What users are looking for is not necessarily the 'highest-rated store.'
In many cases, it is a 'store that fits their situation and purpose.'
For example, for someone looking for a 'store that is easy to consult with even for the first time,' experiences like 'the explanation was polite,' 'it was easy to consult,' or 'they treated me kindly' are more of a basis for judgment than just the height of the stars.
Even when AI recommends a store, if there is no information that can explain these differences, it cannot respond to the user's detailed wishes.
Reviews are not just an indication of whether a store is good or bad; they are also information that expresses what kind of value that store provides in the customer's own words.

5. Viewing GBP reviews as 'store information assets'

Google reviews are not strictly first-party data owned by the company itself.
They are user-generated content accumulated on a third-party platform called Google.
On the other hand, what is written there is information based on actual customer experience.
Sometimes, strengths that the store side had not noticed, customer service that customers appreciate, anxieties during use, and reasons for being chosen are revealed.
In that sense, I think it is a bit of a waste to view reviews only as 'reputation management' or 'improvement of star ratings.'
As AI search spreads, the characteristics of a store written in the customer's own words will also become material for AI to understand that store.
Reviews should be considered one of the store information assets in the AI era.
However, caution is also required when collecting reviews.
In Google reviews, it is a prerequisite to request frank posts based on actual experience without specifying a particular rating or content.
You must avoid requesting only from favorable customers or specifying the content of the post, such as 'please write about the customer service.'
This is important, so I will dare to write it clearly.
The purpose is not to induce the content of reviews for the convenience of the store side.
What should be aimed for is to set up a flow where customers can look back on their experience without difficulty and convey it in their own words.
On top of that, create a state where the current customer experience is continuously accumulated.
I think this will become an important theme in GBP operation in the AI era.

Summary: Reviews are 'evaluation information read by people' and also become 'information sources read by AI'

With the spread of AI search, the touchpoints between stores and users are beginning to change.
Before users check search results one by one, they compare stores based on information organized by AI. Such store searching might not be rare in the future.
At that time, Google Business Profile and reviews are not just auxiliary information.
Google Business Profile is an information foundation for AI to understand stores.
Reviews are an information source for knowing what kind of customer experience is actually being created at that store.
The fact that reviews are evaluation information read by people will not change in the future.
To that, the role of store information that AI also reads will be added.
That is why it is important not to look at reviews only by the number of posts and star ratings, but to grasp them as information assets that express the store's appeal and customer experience.
In an era where AI recommends stores, stores that can convey not only 'whether they are highly evaluated' but also 'why they are chosen and what they are evaluated for' should be easier to understand.
I have looked at many reviews so far, but the true appeal of a store is often expressed in the specific experiences written below the number of stars rather than the number of stars themselves.
It is precisely because it is the AI era that human voices become important again.
It is a bit strange, but don't you think it's an interesting change?

Advertisement: Introduction to Staff Value

Up to this point, I have talked about how reviews are not only 'evaluation information read by people' but also become information sources for AI to understand stores.
However, in the actual field, it is not easy to collect specific voices that convey the store's appeal, as reviews may not continue even if requested, or they may end with just 'it was good.'
At SoldOut, we provide a mechanism called Staff Value that allows customers who visit the store to look back on their own experience and naturally put it into words as a message to the staff and the store.
The collected voices can be used not only as praise delivered to the staff but also as information assets that convey the store's appeal, such as Google reviews, websites, SNS, and in-store displays.
For those who are thinking not only about 'increasing reviews' but also about wanting to leave behind why they were chosen and what is being evaluated in the customer's own words, please also take a look at this article!