Quick Answer
G2 reviews are customer write-ups published on the software marketplace G2, each moderated before it goes live, and they now do two jobs: they reassure a buyer, and they supply wording an AI assistant can quote. G2's March 2026 survey of 1,076 buyers found half now start research in a chatbot and rank review-site citations as their top trust signal. Reviews will not make a model recommend you, but they decide what it has to work with.
Most founders treat a review site as a badge. You collect eight or ten reviews, put the logo in the footer, and move on.
That was reasonable while the buyer read the reviews. It is less reasonable now that the first description of your product a buyer sees is written by a chatbot that read them first.
G2 surveyed 1,076 software buyers and decision-makers in March 2026. It found 51 percent now start research with an AI chatbot more often than with Google, and 69 percent chose a different vendor than they had planned because of what the chatbot recommended.
This walks the chain from one customer's sentence to an AI answer, then gives you the five questions to send a customer so the review carries their words and not yours.
How G2 Reviews Reach the Answers Buyers See
G2 reviews reach an AI answer the ordinary way: an assistant fetches the review page, reads the text, and repeats the parts that answer the question it was asked. Nothing about that is special to review sites.
A review site is not only a trust layer. It is a language layer, which is why the wording carries more weight than the star count. A star is a number an assistant reports, and a sentence is something it quotes.
1. Buyers Open the Chatbot Before the Vendor Site
G2's March 2026 survey of 1,076 B2B software buyers found that 51 percent now start with an AI chatbot more often than with Google, up from 29 percent in its 2025 Buyer Behavior Report. Seventy-one percent use one somewhere in the process.
Tim Sanders, G2's chief innovation officer, puts the effect in one line: "AI chatbots have compressed weeks of vendor research into a single prompt."
So the first sentence written about your product is not yours. It is a summary, and the summary is assembled from pages the assistant was able to read.
2. Assistants Fetch Review Pages With Named Crawlers
OpenAI documents the bots that do the fetching. OAI-SearchBot is "used to surface websites in search results in ChatGPT's search features", and ChatGPT-User is what visits a page when someone asks a question that needs one.
Perplexity documents the same pair, PerplexityBot and Perplexity-User, for the same two jobs. Your G2 profile is a public web page, so it is fetched like any other public web page.
GPTBot is a third name and a different job: OpenAI says disallowing it "indicates a site's content should not be used in training". That distinction is worth holding onto, because retrieval is the part you can observe and influence, and training is not.
Some of it does not need a crawler at all. In September 2026 G2 announced that its verified reviews and buyer intent data are reachable through the Data agent in OpenAI's ChatGPT Work, drawn from six million reviews across more than 200,000 products. Your wording travels further than the page it sits on.
3. Specific Sentences Survive a Summary and Generic Ones Do Not
A summary keeps what separates one option from another. "Great product, easy to use" describes every product in your category, so it tells a buyer nothing and falls out.
A sentence like "we replaced three spreadsheets and cut month-end close from nine days to four" survives, because it answers a question somebody actually asked. That is the difference between a review that flatters you and a review a large language model can use as evidence.
G2 asks reviewers for exactly that shape. Its community guidelines tell reviewers to mention "the level of experience you have with the tool, any integrations you use in conjunction, or any unique use-cases you're addressing".
4. Consistency Across Your Profiles Raises Buyer Confidence
G2 found that buyers treat consistency as a signal of its own. When ChatGPT, Gemini and Claude describe a vendor the same way, confidence goes up, and when the answers conflict, buyers dig until they work out which version is true.
The practical version is blunt. The phrase your customers keep using in G2 reviews should be the phrase on your homepage.
If your site says "revenue intelligence" and every review says "call recording", you have handed the assistant two categories and no way to choose. Fix the site to match the reviews, not the reviews to match the site.
5. How to Check What the Chatbots Say About You
Write down the five questions your buyers would type, run them in ChatGPT and Perplexity on the first of each month, and record three things: are you named, is the category right, and does the description use your customers' words or generic ones.
Google is blunt about the search half of this. Its documentation states there are "no additional requirements to appear in AI Overviews or AI Mode, nor other special optimizations necessary" — a page has to be indexed and eligible for a snippet, and that is the whole entry fee.
The common mistake is reading a missing mention as a technical fault. Usually the public language is thin rather than the markup being wrong, which is the argument we make in AEO versus SEO when nobody has heard of you.
So an AI SEO service that only touches pages you own is doing half the job. Better Marketing counts your review profiles as part of the surface, because that is where the other half of the answer is written.
Why a Small Review Set Carries Outsized Weight
With eight G2 reviews, a single review is one eighth of everything that page says about you. With eighty, it is noise. That arithmetic is the entire argument for treating early reviews as positioning rather than proof.
Picture the eight. Three say setup was quick, two praise support, two describe a narrow use case, and one complains about missing enterprise features.
A reader skims that and forms a view. An assistant asked to describe your product does much the same, and the narrow use case is now a quarter of what it has to work from.
The same holds on Capterra and anywhere else your customers write in public. Volume eventually averages the wording out. Before volume arrives, every review is a vote on what your category is.
Which Customers Should Write Your G2 Reviews
Ask the customers who look like the market you want, not the ones who answer fastest. The fastest reply often comes from the smallest deployment, and a review from a small deployment quietly tells the market you are a small-deployment product.
The same account list a B2B demand generation agency would build for outbound is the list to ask here. Sort by fit, not by warmth.
- Role fit: the person using it holds the job title you want to sell to next
- Problem fit: they bought for the reason you want to be known for, not an edge case
- Evidence fit: they can describe a before and an after without being coached
If you have four or five customers in total, this is selection rather than strategy, and the mechanics of asking are the same ones in getting testimonials with four customers. Most content marketing for tech companies is written to persuade; a review is written to describe, which is why the two read so differently and why buyers trust the second one more.
When to Ask for G2 Reviews and What to Ask For
Ask in the week a customer has just told you, unprompted, what changed. After a rollout lands, after a support thread ends well, after they quote a number back at you in a call.
That timing matters because the review then contains the language you want preserved, rather than a polite paragraph written from memory three months later.
Then ask for detail rather than praise. Five prompts, sent as a short note, get you most of the way:
- What were you doing before this, and what was wrong with it
- What changed after you rolled it out, in whatever units you measure
- Who on your team uses it, and how often
- What else you looked at, and why you did not pick it
- Which single outcome mattered most to you
Do not script the answer. Prompt for the territory and let them write it, because a coached review reads coached, and both a buyer and a model discount it.
The same five questions are worth keeping for the rest of the business. A B2B demand generation agency will ask you for exactly this material before writing a single outbound line, and your G2 reviews are where it already exists in the customer's own words.
How Generic and Specific G2 Reviews Differ
The gap is not enthusiasm. Both kinds of review are positive, and only one of them leaves anything behind.
| What you are judging | Generic review | Specific review |
|---|---|---|
| What it says | Easy to use, great support | Replaced three spreadsheets, close went from nine days to four |
| What a buyer learns | Somebody liked it | Whether it fits their situation |
| What an assistant can quote | Nothing that separates you | A sentence naming the problem and the result |
| What it does for your category | Leaves the category to the model | States the category in a customer's words |
| What it costs the customer | Thirty seconds | Five minutes, once |
The right-hand column is not harder to get. It is harder to ask for, because asking for it means sending a question rather than a link.
What G2 Allows When You Ask for Reviews
You may offer an incentive, within limits G2 publishes. Its community guidelines cap the value of any incentive offered in exchange for a review at 100 US dollars, and G2 labels an incentivized review as incentivized when it publishes it.
What you may not do is make the incentive conditional on a good rating, run a collection campaign that targets only your happy customers, or contact a reviewer to pressure a change. Every review passes moderation before it goes live.
Reviewers may also publish without a name, a photograph or a company. An unattributed review still shows the reviewer's job category and industry, so your G2 reviews can carry the role behind the opinion even when the person stays private.
Read those rules as a design brief rather than a restriction. They describe the review set that is worth having: real accounts, mixed opinions, and specifics a competitor cannot copy.
When More G2 Reviews Will Not Help You
Reviews are not the constraint when your buyers do not shop in a category directory. If your product is new enough that no G2 or Capterra category describes it, the reviews land somewhere nobody is looking, and the work belongs on the category question first.
They also will not help if your own pages contradict them, or if nobody has used the product long enough to say anything concrete. A review written at week two describes onboarding, which is the one part of your product every competitor also has.
The category problem is the deeper one, and it is the same problem as a product name with zero search volume: nobody can look for a thing they cannot name. Content marketing for tech companies solves that on pages you control, and reviews confirm it on pages you do not.
None of that is an argument against asking. It is an argument for fixing the naming first, because a review describing a category nobody searches for still helps the buyer who already found you, and nobody else.
Treat Your First Twenty G2 Reviews as Positioning
Pick the customers who look like your next market, ask them in the week they describe a result out loud, and ask for the problem, the change and the alternative rather than a rating. Then move the phrases that recur into your homepage so the two sources agree.
That is the cheapest AI SEO service work a founder can do without hiring anyone, and it compounds from the first handful of customers. Better Marketing does it in that order for the same reason: trust is built in specifics, never in slogans.