SEO

71 SaaS Category Competition Statistics and AI Shortlists

71 statistics on how crowded software categories are, how short buyers keep shortlists, and how few vendors AI answers ever name.

Author:
Leon Claassen
Contributors
Vlad Shvets
Date:
October 28, 2026

G2 lists 2,505 products in its CRM category. We put three of a CRM buyer’s questions to ChatGPT and Google AI Mode, ChatGPT twice, and across those nine answers the engines named 11 different vendors.1

A crowded category looks like a bigger prize: more buyers, more room. In the answers buyers now start from, the room does not grow with the category. The list stays about the same length, and the size of the category decides only how many companies wait outside it.

This page counts both sides for software. How many products each category lists, from our census of G2 and GetApp, and how many of them reach an AI answer, from our run across 110 G2 categories, set beside the published research on how buyers shortlist, every figure read at its origin.

Highlights

99 products sit in the median G2 software category, and 358 products in the median category of its AI group.2
2.7 products make the average buyer’s shortlist, and 83% of buyers shortlist three or fewer.3
51% of buyers of B2B software told G2 they now begin research in an AI chatbot more often than in Google, against 29% a year before.4
14 different vendors were named across a category’s nine answers in our run, in categories under 50 listings and of 250 or more alike.1
2.5% of listings in categories of 250 or more products ever reached an answer, against 39.3% in categories under 50.1
8.6% of categories of 250 or more products had no vendor named in every answer, against 32% of those under 50.1
47.6% of answers on Google AI Mode cited a community page such as Reddit in categories of 250 or more products, against 9.5% under 50.1

Read together, they say the field and the answer have come apart. Categories hold about a hundred products and AI ones several hundred, buyers still keep about three, and the answer that now hands them those three names the same number however crowded the category. In a crowded category the names are settled, and the pages behind them belong mostly to someone else.

How Many Products a Software Category Lists

Empact Partners, a consultancy that has spent six years doing go-to-market work inside the marketing teams of B2B software companies, read the listing count on G2’s own category pages on 28 October 2026, for 729 categories in a random draw from the 1,895 software categories in G2’s taxonomy:

99 products in the median category; a quarter list fewer than 51 and a quarter more than 202.2
49.7% of categories list 100 or more products, 23.7% list fewer than 50, and 5.9% list 500 or more.2
358 products in the median category of G2’s AI software group, the most crowded group in the draw, across 31 categories.2
72.5% of reviews belong to the first ten products on a category’s page, in the 543 categories with enough reviews to measure, from 90.2% where it lists 10 to 49 products to 48.5% at 500 to 999.2

A typical software category is a field of about a hundred, and most of what buyers have written about it sits with the ten names at the top of its page.

Bar chart of 729 G2 software categories by the number of products each lists: 5 list 0 to 9, 168 list 10 to 49, 194 list 50 to 99, 222 list 100 to 249, 97 list 250 to 499, 32 list 500 to 999, and 11 list 1,000 or more.
More than half of the categories list between 50 and 249 products; the two short bars past 500 hold the most crowded fields.

GetApp prints a product count beside every one of its 994 categories, so its census is complete. The median GetApp category lists 136 products, 610 of the 994 list 100 or more, and 8 list 1,000 or more.5 Two directories with different taxonomies give the same shape, so the shape belongs to the market rather than to one site’s filing.

Both counts are listings, and a product filed in three categories counts three times. G2’s own totals take the overlap out: it listed 151,264 products when it computed its 2026 awards, and 4,692 of them had the ten reviews in a year needed to be ranked, 3.1% by our division.6 Behind them stood 116,198 vendors.7

Capterra publishes reviews for more than 45,000 software products in more than 1,200 categories.8 G2, which announced in January that it would acquire Capterra, GetApp and Software Advice, says the four together span more than 2,000 software and service categories.9

Leon Claassen
Senior GTM Consultant @ Empact Partners
The number on your category page is not your competition. It is the field a buyer, a directory and now an AI engine weigh you against before you have said anything, and it is far longer than the list of rivals a founder can name from memory. Most positioning work never looks at it, which is how a company ends up filed in the most crowded category it could have picked.

Fields Fill Fast, and the Maps Stopped Fitting

The fastest-filling fields are the new ones. G2 measured its own AI categories in August and October 2026:

630% more products across G2’s 111 AI categories than a year earlier, 30,274 in all as of July 2026.10
103 new categories created between September 2025 and September 2026, 41 of them AI-native, up from 28 of 70 the year before and 5 of 88 the year before that.11
77% of products in 12 AI-native categories, 3,297 of 4,292, had no verified review yet, against 34% in Help Desk, 47% in CRM and 60% in SEO Tools.11

A new category fills with listings long before it fills with reviews, so most of a young field is a name and a product page.

One category shows the pace end to end. G2’s Answer Engine Optimization category, which launched as Generative Engine Optimization, held 7 products in March 2025 and over 150 ten months later.12 By September 2026 it listed 623, of which 417 had no verified review.11 On 28 October our census read 698.2

Line chart of products listed in G2's Answer Engine Optimization category: 7 in March 2025, over 150 in January 2026, 623 in September 2026 and 698 on 28 October 2026.
The category grew about a hundredfold in nineteen months, and most of that growth came after its first ten months.

Answer Engine Optimization is the category we know best, and the least neutral on this page. Qvery, our sister company, sells AI visibility software in it and its research appears further down, so weigh our reading of both accordingly. The counts are G2’s and ours, and every Qvery article is linked where it is used, so its method can be checked.

Outside the directories the curve looks the same. CB Insights says the AI agent landscape went from roughly 300 players in March 2025 to thousands by November, and it chose its map from a pool of over 1,700 companies.13

The people who draw category maps for a living reached the limit first. What the best-known landscapes now print:

150 to 15,505 marketing technology products on the martech landscape between its 2011 and 2026 editions, with growth in the last year down to 0.79%.14
40% fewer new entrants reached the 2026 martech map than the 2025 one, 1,488 against 2,489, while removals rose 13% to 1,367.14
139 to 2,011 logos on the Machine Learning, AI and Data landscape, from its first edition in 2012 to 2024.15
About 1,150 logos on its 2025 edition, after its author cut the map from more than 2,000 to keep it legible.16
760+ of 1,961 companies in DHRmap’s HR technology directory make its published map.17
1,000 unique companies on Momentum Cyber’s CYBERscape 4.0, up from 803 on the edition before.18 IT-Harvest counts more than 4,100 cybersecurity vendors, and says all of Gartner’s cybersecurity Magic Quadrants together include 144 of them.19
Over 3,500 companies on the UT Dallas sales technology landscape, which found that of about 1,800 companies in the database it inherited, about 800 still operate independently.20

A landscape is a shortlist drawn by a person, and when the field outgrew the page, the people drawing it cut. An AI answer makes the same cut, only it makes it at the moment a buyer is choosing.

The Buyer’s Shortlist Stayed Short

TrustRadius surveyed 1,862 technology buyers in January 2026, each involved in a software or hardware purchase in the year before:

2.7 products on the average shortlist, 3.2 for high purchase prices, and 83% of buyers shortlisted three or fewer.3
67% of buyers bought the product that was their first choice when they made the shortlist.3
79% of buyers had heard of the tool they bought before they started researching.3
13% of buyers bought a product that was neither an established leader nor a niche product for one segment.3

A shortlist of under three, mostly settled before the research starts, leaves little room for a company the buyer has not already met.

Three other surveys, each of its own population, point the same way:

49% of buyers in G2’s March 2024 survey had one to three products on the shortlist, up from 33% in 2023, while four to seven fell from 45% to 31%.21
95% of purchases went to a vendor on the buyer’s day-one shortlist, up from 85%, after buyers evaluated 5.1 vendors, in 6sense’s study of nearly 4,000 B2B buyers whose purchases topped $25,000, a third of them software.22
About 4 vendors made the shortlists of buyers disappointed with a purchase, against 3 for those who adopted successfully, in Capterra’s survey of 3,385.23

A longer list did not buy a better choice. Buyers are also cutting the number of tools they hold. The companies whose software Zylo manages run an average of 305 applications,24 and 84% of the decision makers G2 surveyed in June 2026 had folded at least three best-of-breed tools into all-in-one platforms in the past year.25

Leon Claassen
Senior GTM Consultant @ Empact Partners
A buyer’s shortlist has always been short. What changed is who writes the first draft of it. When that draft comes from an AI answer, the companies on it were chosen from pages the buyer never opened, and the ones left off rarely learn why. That is the part of the funnel most software companies still do not measure.

The Shortlist Now Forms Inside an AI Answer

G2 surveyed 1,076 B2B decision makers in March 2026 for its report on how AI search is changing software buying:

51% of buyers told G2 that an AI chatbot now opens their software research more often than Google does, against 29% in April 2025.4
69% of buyers ended up with a different vendor from the one they had planned on, after a chatbot steered them.4
33% of buyers bought from a vendor they had not known before.4
85% of buyers think more highly of a vendor an AI chatbot names in a recommendation.4

The answer is now where a shortlist gets made, and it can put a stranger on it.

G2’s June survey of 1,038 decision makers put review sites and AI chatbots almost level as the top sources shaping a shortlist, 38% and 37%.25 Buyers who took chatbot recommendations bought from their first shortlist more often, 80% in at least three of their last five purchases against 65%, an association rather than a measured effect.25

Two instruments agree that the list an answer hands over is short:

5 products in the median ChatGPT answer in our run, and 6 in the median Google AI Mode answer.1
4 companies in the median ChatGPT answer and 5 on Google AI Mode in August 2026, in Qvery’s daily tracking of buyer questions, with two to six named in 82.00% and 78.60% of answers.26
7.20% of answers on ChatGPT named eight or more companies in Qvery’s records, so long answers were rare.27

Empact Partners ran this test for this page: 113 G2 categories from niche to crowded, three unbranded buying questions each, asked on 28 October. For partners we run it every week on their own category with the Empact Panel, on the questions their buyers ask, as the measuring half of our Generative Engine Optimization work.

A Bigger Category Does Not Get a Bigger Answer

Our run put the same three questions to 110 categories whose G2 pages print a listing count, and read every product the 989 answers named:

14 different vendors were named across a category’s nine answers at the median, and 14 in each size band; the rank correlation between a category’s listings and the vendors named was effectively zero, -0.007.1
1,600 vendors were named across all 110 categories, which list 31,308 products between them.1
39.3% of listings were ever named in categories under 50, against 11.8% at 50 to 249 and 2.5% at 250 or more, and 0.8% in the six categories of 1,000 or more.1
11 vendors reached an answer for CRM, 0.44% of its 2,505 listings.1
45.8% of mentions went to a category’s three most-named vendors, about the same in every band.1

The engines answer a crowded category with a list as long as a niche one’s, so the bigger the category, the smaller the share of it a buyer ever hears about.

Combo chart of 110 software categories in three size bands: the median category lists 35, 113 and 569 products on G2, while the different vendors named across its nine AI answers stay at 14 in every band.
The bars grow sixteenfold from the smallest band to the largest, and the line does not move.
An AI answer is not a market to win share of. It is a handful of seats, and the size of the category decides only how many companies queue for them.

Qvery’s tracking shows the same concentration over two months. In the typical market it follows, the five most-named companies took 47.78% of mentions on ChatGPT and 36.48% on Google AI Mode, and 40.42% of the companies ChatGPT named at all appeared in exactly one answer.28

The penalty for being rarely asked about compounds. From companies named on half or more of their market’s questions to those named on under 5%, Qvery found the share of all answers naming them falls 684.21 times on ChatGPT.28 A category’s long tail is not a little less visible than its leaders. It is close to absent.

Leon Claassen
Senior GTM Consultant @ Empact Partners
When a partner tells me their category is crowded, the count I want is not how many competitors it has. It is how many names its answers hold, and who holds them. In our run that list stayed the same length however big the category got, which makes a crowded category a different problem from a small one, not a harder version of it.

Crowded Categories Have Fewer Open Seats

Length is one half of it. The other half is how settled the list is, and our run measured that three ways:

8.6% of categories of 250 or more listings had no vendor named in all nine answers, against 16% at 50 to 249 and 32% under 50.1
80.4% of vendors ChatGPT named for a question came back when we asked it again, from 77.1% in the smallest categories to 82.2% in the crowded band.1
50.5% of vendors named by either engine for the same question in a crowded category were named by both, against 41.7% in the smallest categories and 71% in the six largest.1

A small category’s answer is still moving between askings and between engines. A crowded category’s has settled on its names.

Horizontal bar chart of software categories where no vendor was named in all nine AI answers: 32% of categories under 50 listings, 16% of those with 50 to 249, and 8.6% of those with 250 or more.
The bigger the category, the likelier at least one vendor holds a seat in every answer.

Reviews move the other way. In our census the first product on a G2 category page holds a median 15.8% of reviews, from 23.6% where a category lists 10 to 49 products down to 8.1% where it lists 500 to 999.2 As a category grows, the review record spreads across more names. The answers do not spread with it.

Qvery measured how firmly seats are held, and where they open, in its own records:

4 of 5 places in project management answers’ top five were held by the same product in every asking, on both engines, in September and October, and 2 of 5 in CRM, two categories Qvery calls crowded.29
72.47% of companies ChatGPT named first were in the top three the next time the question was asked, and of all the companies a daily question drew in a month, 41.99% appeared once, in Qvery’s ChatGPT records.30
59.86% of companies ChatGPT named came back when the same question was asked the next day, but only 23.09% carried over from a short query to a longer situation question in the same topic.31
1.86 times as many products surfaced for narrow questions as for broad ones, in the same number of answers, in three young categories, where the top three took between 25.59% and 45.97% of the broad answers’ mentions.32

The open seats sit in the narrower question, where the list still moves.

We saw this before we measured it. In a January 2025 workshop our team put several partners’ core-category questions to the engines live, and the one place a partner did better was a narrow category with few competitors. The broad “best X software” questions were the hard ones.

Choosing where to compete is positioning, and it comes before any visibility work. Empact Partners works it through with partners in our Brand Marketing work: create a category, narrow one with a qualifier, or compete inside it, then file the product in the directory category that matches, since that filing sets the field it is counted against.

Who Fills the Answer in a Crowded Category

Which pages an answer reads moves with the size of the category too. Our run classed every cited page as a vendor’s own site, a directory, a community such as Reddit or YouTube, or a publisher:

47.6% of answers on Google AI Mode cited a community page in categories of 250 or more listings, against 25.3% at 50 to 249 and 9.5% under 50, and answers citing a publisher rose from 39.2% to 51.4%.1
88.8% of answers on Google AI Mode cited a vendor’s own site, in every size of category, against 41.4% of ChatGPT’s.1
42.9% of answers on ChatGPT cited no source at all, with web search on, against 0.9% on Google AI Mode.1

In a crowded category Google AI Mode reads more of other people’s pages before it names anyone, while ChatGPT answers close to half its buying questions without citing a page.

Dumbbell chart of Google AI Mode answers citing each kind of page, in categories under 50 listings against 250 or more: vendor sites 89.2% and 88.6%, publishers 39.2% and 51.4%, directories 31.1% and 36.2%, and community pages 9.5% and 47.6%.
Vendor sites hold steady across sizes, and community pages are where crowded categories differ most.

Qvery’s studies of software answers point to the same pages:

71.20% of answers in CRM cited a CRM company’s own pages, while G2, Capterra, GetApp, Trustpilot and Software Advice together appeared in 6.40% of CRM answers and 1.60% of AI voice-agent ones, in Qvery’s study of the two categories.33
8 sites reached four fifths of the sourced shortlist answers in email marketing software, a category Qvery picked as crowded enough for every kind of site to turn up.34
8.89% of answers on ChatGPT named the median brand in the top quarter by presence on cited best-of lists, across eleven software categories, against 5.56% for the top quarter by backlinks, a gap Qvery says category size partly explains.35

Buyers trust the directories more than the engines cite them: 45% told G2 that review-site citations are the most confidence-inspiring signal in an AI answer.4

In a crowded category Empact Partners works on the pages the answer reads before it names anyone: the Reddit threads where buyers compare tools, the list articles the engines cite, the directory profiles. Then we follow, week by week, which of those pages the engines begin to cite, read against the sources each engine leans on in that category.

Leon Claassen
Senior GTM Consultant @ Empact Partners
In a small category a company can often get named by being good and easy to find. In a crowded one the answer has already chosen its names from pages the company did not write, so the work moves off its own site and onto those pages, and it is measured in quarters rather than weeks.

What This Run Cannot Settle

Every figure of ours above carries the limits of how it was made:

Sample: our 110 categories were chosen by hand to run from niche to crowded, so a pooled figure describes them, not every software category. Each got three questions in US English on one day, ChatGPT twice and Google AI Mode once, and the sharpest figures for the largest categories rest on six of them.
Census: the G2 count is a random draw of 813 of the 1,895 software categories, 729 of which print a listing count. Our scraping budget ran out partway and G2 refuses plain requests, so we stopped rather than go round it. GetApp’s count covers every category.
Listings: a listing is not an active competitor. Most products in G2’s new AI categories have no review, so the field a buyer would seriously weigh is smaller than the count.
Reading: a model read the products out of each answer, checked by hand on a sample, and products were folded to their company by name, which can split or merge a vendor at the edges.
Cause: all of it is association. We can see that crowded categories’ answers hold their names more firmly and read more community pages; we cannot say why, or that a company placed on those pages will be named.

Count the Seats Before You Choose the Category

Before choosing where to compete, or deciding why you are missing from the answers in your category, count three things:

The field: how many products your directory category lists, which is the number you are weighed against.
The seats: how many names the answers to its buying questions hold, and how firmly they hold them.
The pages: which pages the engines read to fill those seats, and whether any of them name you.

In a small category the seats still move. In a crowded one they are held, and the way in runs through other people’s pages or through a narrower question whose seats are open.

Working with Empact Partners on it starts with an audit of your category’s answers and a roadmap, owned by a named senior consultant who runs the measurement on your own buyers’ questions and the work across positioning and the pages the engines read, planned in quarters.

If your category’s answers have already chosen their names and yours is not among them, book a call with us, and we’ll see whether we could work together.

Sources

  1. Empact Partners, AI answer run: 113 G2 software categories from niche to crowded, 110 of them printing a listing count, three unbranded buying questions each, ChatGPT with web search asked twice and Google AI Mode asked once, US, 1,016 answers collected 28 October 2026, read against each category’s listing count from our G2 census of the same day.
  2. Empact Partners, census of G2’s software categories: the listing count, the review total and the first page of products on each category page, for a random draw of 813 of the 1,895 software categories in G2’s taxonomy, 729 of which print a count, read 28 October 2026.
  3. TrustRadius, Beyond the Hype: The AI Bubble that Isn’t Bursting (Yet), 2026 B2B Buying Disconnect report, 15 July 2026: 1,862 technology buyers surveyed in January 2026.
  4. G2, New G2 Research: Half of B2B Software Buyers Now Start Their Research With AI Chatbots, PR Newswire, 15 April 2026, on The Answer Economy report: 1,076 B2B decision makers surveyed in March 2026.
  5. Empact Partners, census of GetApp’s category directory: the product count printed beside each of its 994 categories, read 28 October 2026.
  6. G2, Best Software Products for 2026, February 2026.
  7. G2, Global Software Companies for 2026, February 2026.
  8. Capterra, Capterra’s Proprietary Data & Research Methodologies, updated into 2026.
  9. G2, G2 to Acquire Capterra, Software Advice, and GetApp from Gartner, PR Newswire, 29 January 2026.
  10. G2, How G2 Is Bringing Accountability to AI Software Claims in 2026, Emily Malis Greathouse, 27 August 2026.
  11. G2 Learn Hub, The Great Software Re-Rating: Top Categories Reshaped by AI in 2026, Sidharth Yadav, 1 October 2026, updated 22 October 2026.
  12. G2, Inside the 2,000% Growth of the AEO Software Category on G2, 30 January 2026.
  13. CB Insights, The AI agent market map, 10 November 2025.
  14. chiefmartec, 2026 Marketing Technology Landscape Supergraphic: Peak Martech Achieved! (Maybe), Scott Brinker and Frans Riemersma, May 2026.
  15. Matt Turck, FirstMark, Full Steam Ahead: The 2024 MAD (Machine Learning, AI & Data) Landscape, 31 March 2024.
  16. Matt Turck, FirstMark, Bubble & Build: The 2025 MAD (Machine Learning, AI & Data) Landscape, 28 October 2025.
  17. DHRMap, HR Tech Company Directory, read 28 October 2026.
  18. Momentum Cyber, Cybersecurity Almanac, 2025 Year-End Report, January 2026.
  19. IT-Harvest, About IT-Harvest, read 28 October 2026.
  20. The University of Texas at Dallas, Center for Professional Sales, Sales Technology Landscape, Q1 2026 release.
  21. G2, 2024 Buyer Behavior Report: Proving Value in the Age of AI, 2024: 1,940 B2B decision makers surveyed in March 2024.
  22. 6sense, 2025 B2B Buyer Experience Report: How AI Is (and Isn’t) Disrupting Buying Journeys, November 2025.
  23. Capterra, Habit 3 of the 5 Habits of Successful Software Adopters: Shortlist Decisively to Maintain Decision-making Momentum, 19 January 2026, from the 2026 Software Buying Trends survey of 3,385 respondents, August 2025.
  24. Zylo, 2026 SaaS Management Index, January 2026.
  25. G2, 2026 Buyer Behavior Report: The Evaluation Maze, 2026: 1,038 B2B decision makers surveyed in June 2026.
  26. Qvery, AI Search Statistics, Stage by Stage: From a Buyer’s Question to a Customer, Vlad Shvets, 29 June 2026, updated 16 October 2026.
  27. Qvery, AI Visibility vs. Share of Voice vs. Average Rank: What Each Number Lets You Decide, Vlad Shvets, 29 March 2026, updated 15 October 2026.
  28. Qvery, Double Jeopardy in AI Search: Smaller Companies Lose Twice, and the Losses Multiply, Vlad Shvets, 17 March 2026, updated 15 October 2026.
  29. Qvery, Breaking Into a SaaS Category’s AI Shortlist Starts With Counting Its Open Seats, Vlad Shvets, 22 September 2026, updated 20 October 2026.
  30. Qvery, How to Get ChatGPT to Recommend Your Brand at the Top of Its Shortlist, Vlad Shvets, 17 March 2026, updated 16 October 2026.
  31. Qvery, How to Generate LLM Tracking Queries From Your Sales Calls and Emails, Vlad Shvets, 1 September 2026, updated 18 October 2026.
  32. Qvery, New SaaS Products in AI Recommendations: The Best-Tool List Is Settled, Narrow Questions Are Not, Vlad Shvets, 2 August 2026, updated 19 October 2026.
  33. Qvery, The Pages AI Answers Cite for CRM and Voice-Agent Buyers, and Who Owns Each, Vlad Shvets, 1 September 2026, updated 15 October 2026.
  34. Qvery, How To Run A Citation Gap Analysis That Ends In A Work Queue, Vlad Shvets, 4 September 2026, updated 15 October 2026.
  35. Qvery, Domain Authority Is a Weak Guide to the SaaS Brands ChatGPT Names. The Lists It Cites Are Better., Vlad Shvets, 22 September 2026, updated 20 October 2026.

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