Freshdesk Takes the Lead, but AI Recommendations Are All Over the Place
When we asked ChatGPT, Gemini and Perplexity six different questions about help desk software, Freshdesk appeared in five of the six answers, the closest any product came to a clean sweep. No vendor was named in every response. HaloITSM and Help Scout followed with four mentions apiece, while a long tail of 22 other products surfaced just once or twice across the entire set.
We fed all three assistants the same six prompts, verbatim: “best help desk software,” “best help desk software for small teams,” “what help desk software should I use,” “best free help desk software,” “most affordable help desk software,” and “help desk software recommendations.” Every query returned a readable list, so we had six complete answers from each assistant, 18 total recommendation sets, to pick apart. The single biggest surprise was not which product led, but what fed the results. Reddit threads appeared as a source in all six answers. No other domain came close. PCMag.com and proprofsdesk.com each supplied four answers, while crm.org, quora.com and thecxlead.com contributed to three. Every assistant leaned on the same small pool of discussion forums and review sites to build its suggestions.
That reliance on public conversation created a strangely flat field. Freshdesk’s five mentions make it the most consistent pick, but the gap to HaloITSM and Help Scout at four is thin, and after that the counts drop fast. ProProfs Help Desk and Zoho Desk each landed three mentions. Desk365, Freshservice, HappyFox Service Desk and Zendesk each got two. Then comes the volley of products named exactly once: Atera, Intercom, Jira Service Management, ServiceNow, Spiceworks, TeamSupport, and a dozen others. Even Zendesk, one of the most recognizable brands in the space, appeared under three different names across the answers,plain “Zendesk,” “Zendesk Support Suite,” and “Zendesk for Employee Service” each showed up in a single response, as if the assistants could not agree on what to call it.
What a product’s own domain does matters here in a way that traditional SEO logic predicts but still feels stark. ProProfs Help Desk, named in three answers, had its website listed as a source in four of the six response batches. Desk365.io fed two answers and Desk365 itself got two mentions. In a category where no product was in every answer, having a site that the AI engines crawl as a source might be as valuable as having a presence on PCMag or G2.
The fragmentation puts both the leaders and the unmentioned in an odd spot. Freshdesk shows up often, but not always. A buyer asking “best free help desk software” or “most affordable help desk software” got Zoho Desk, Spiceworks, osTicket and others alongside it, diluting any sense of a single safe choice. For a vendor who never appeared, like dozens of help desk tools not listed once, the signal is plain: if your name isn’t showing up on Reddit or those four or five review sites the assistants repeatedly scraped, you effectively do not exist in this AI recommendation layer. The machines are not synthesizing fresh product knowledge; they are remixing the forums and listicles they trust, and right now that trust is narrow.
The Tally: Five Mentions, One Mention, and a Lot of Empty Space
No help desk product was named in all six answers. Freshdesk, at five of six, came closest, missing only the broad “best help desk software” query. That single absence kept it from a clean sweep, but it still appeared more reliably than any competitor. HaloITSM and Help Scout followed with four mentions each, both present in two-thirds of the responses. ProProfs Help Desk and Zoho Desk landed at three mentions apiece, rounding out a small cluster that dominated the recommendations. These five products accounted for most of the high-frequency mentions, yet they never appeared together in a single answer: the assistants rarely agreed on a shared shortlist.
Below that, the counts drop fast. Desk365, Freshservice, HappyFox Service Desk and Zendesk all surfaced twice. Zendesk’s presence is scattered: the bare name “Zendesk” turned up in two answers, while “Zendesk for Employee Service” and “Zendesk Support Suite” each appeared once, as separate identities. A buyer looking for Zendesk as a single entity would see it named only twice, and its specialist editions only in isolated moments. Freshservice, owned by the same parent as Freshdesk, appeared in just two answers, one of them the “small teams” query where it was listed alongside Freshdesk,the assistants treated them as distinct products rather than a family.
Then the long tail opens. Twenty-two other products were named exactly once across all six questions and all three assistants. Some are large, well-known platforms: ServiceNow, Salesforce Service Cloud, Intercom, and Jira Service Management (plus the all-caps variant JIRA Service Management, which the raw logs count as a separate single mention). Others are niche or SMB-focused tools: Atera, TeamSupport, Vivantio, HESK, osTicket (and its differently capitalized form OsTicket, also one mention), BlueTweak, Faveo, Featurebase, HelpCrunch, Raiseaticket, Spiceworks, Alvao. For each of these, exactly one assistant, in exactly one answer, decided they belonged. A product named once across 18 total assistant-responses is the output of a single source or a specific query phrasing catching the model’s attention. There was no reinforcement, no second look.
The per-question breakdown explains why. “Best free help desk software” surfaced Zoho Desk, Spiceworks, OsTicket, ProProfs Help Desk, Freshdesk, JIRA Service Management, Raiseaticket and HelpCrunch,a list that barely overlaps with the other five questions. Spiceworks, OsTicket, Raiseaticket and HelpCrunch were never named outside that free-software prompt. Similarly, “best help desk software” drew in enterprise-flavored names,ManageEngine ServiceDesk Plus, Vivantio, Zendesk for Employee Service, Salesforce Service Cloud,that disappeared entirely from the other queries. The assistants did not build a cumulative ranking; they rebuilt the category from scratch each time, pulling from different source domains and different Reddit threads. This fragmentation is why so many products live in a single-question silo.
What a reader expects to see,and what barely shows up,is telling. Jira Service Management, a mainstay of Atlassian’s portfolio, got two mentions (one for each capitalization variant), but both came in single answers: the “best free” prompt and the “recommendations” prompt. ServiceNow, an ITSM heavyweight, appeared only in “help desk software recommendations,” leaving it invisible in five out of six queries. Salesforce Service Cloud turned up once, for the generic “best” question, and nowhere else. A buyer scanning for enterprise suites might conclude the assistants ignore them, unless the question is framed with exactly the right wording. That is a feature of these six queries, not a verdict on the products themselves. Absence from our list is not absence from the category; it simply means the assistants did not pull those names from the domains they consulted on those particular prompts.
The structure makes a single mention precarious. TeamSupport or HESK exist in these outputs only if a user asks the one question that unlocks them. Freshdesk’s five mentions make it the nearest thing to a default recommendation among these assistants, but even it fell away once, and no product achieved the consistency of a true standard answer. For a vendor, being named five times signals AI visibility that borders on ubiquity in this measurement. Being named once means you are entirely dependent on the whims of a single source domain or a single phrase. And for the shopper, a help desk software that appears in every answer does not yet exist in these models.
The full list, counted
Every product serper+or:chatgpt,gemini,perplexity named across 6 answers, with how many of those answers named it. The share column is out of the answers we read, not out of the category.
| Product | Named in | Share | Read as |
|---|---|---|---|
| Freshdesk | 5 of 6 | 83% | 5 answers |
| HaloITSM | 4 of 6 | 67% | 4 answers |
| Help Scout | 4 of 6 | 67% | 4 answers |
| ProProfs Help Desk | 3 of 6 | 50% | 3 answers |
| Zoho Desk | 3 of 6 | 50% | 3 answers |
| Desk365 | 2 of 6 | 33% | 2 answers |
| Freshservice | 2 of 6 | 33% | 2 answers |
| HappyFox Service Desk | 2 of 6 | 33% | 2 answers |
| Zendesk | 2 of 6 | 33% | 2 answers |
| Alvao | 1 of 6 | 17% | one answer only |
The Pages Behind the Picks: Reddit as a Constant, Vendor Sites as Wildcards
Reddit.com fed all six answers. No other domain did. The assistants treated it as a floor, not a ceiling, threading user threads into every response regardless of the query. Two sources followed with four appearances: pcmag.com, a product review site, and proprofsdesk.com, the homepage of ProProfs Help Desk. Three domains hit three answers each: crm.org, quora.com, and thecxlead.com. The remaining 15 domains showed up either twice or once, a long tail that reveals how little consensus exists across queries.
The split between editorial, forum, and vendor sources shifted depending on the prompt. For “best help desk software,” the assistants pulled from crm.org, reddit.com, pcmag.com, zendesk.com, quora.com, and g2.com, a tight set of six. The outcome was a list heavy on enterprise ITSM tools like HaloITSM, Freshservice, and ManageEngine ServiceDesk Plus. G2.com, a major review aggregator, appeared only in this single query, then vanished. Its sole use suggests the assistants considered it relevant for the broadest, most generic comparison but not for price-sensitive or team-size-specific questions.
The affordable and free queries swung hard toward vendor pages. For “most affordable help desk software,” the sources were reddit.com, crm.org, quora.com, desk365.io, proprofsdesk.com, and zoho.com. Two of those (desk365.io and zoho.com) are vendor sites for products (Desk365 and Zoho Desk) that appeared in the answer. The “best free help desk software” query used reddit.com, community.spiceworks.com, proprofsdesk.com, desk365.io, zoho.com, and raiseaticket.com. Three of those are vendor pages, and the response named ProProfs Help Desk, Zoho Desk, Desk365, and Raiseaticket. The correlation is tight: a product’s own domain appeared as a source, and that product ended up in the recommendation. Spiceworks Community, an IT-specific forum, fed only this one answer, making it a niche signal for zero-cost tools.
ProProfs Help Desk presents a curious mismatch. Its domain, proprofsdesk.com, fed four answers, yet the product itself was named in only three. In the “best help desk software for small teams” response, proprofsdesk.com was among seven sources, but the answer omitted ProProfs entirely, recommending Desk365, Featurebase, Freshdesk, and five others. The vendor page likely provided generic category context or comparison data rather than a direct product pitch, and the assistants chose differently. A vendor’s own content can thus lift visibility without guaranteeing inclusion.
Twelve domains surfaced in exactly one answer. They include techradar.com, thectoclub.com, thedigitalprojectmanager.com, zapier.com, salesforce.com, featurebase.app, bluetweak.com, realtech.com, and others. None of these single-use domains belonged to Wikipedia, Gartner, Forrester, or any analyst firm. The assistants built recommendations by grabbing specific pages that matched the phrasing of the question. The “help desk software recommendations” query drew from the widest net: pcmag.com, reddit.com, proprofsdesk.com, thectoclub.com, thedigitalprojectmanager.com, zendesk.com, thecxlead.com, and techradar.com, eight sources with almost no overlap with the free or affordable queries. That scatter suggests the assistants treat each prompt as its own retrieval event, not as a shared knowledge base that gets refined across questions.
For a product manager reading this, the lesson is uncomfortable. The domain mix shows that recommendation here is part SEO, part community chatter, and part editorial gatekeeping, but not a measured evaluation. A help desk vendor can influence its presence by making sure its own pages rank for phrases like “most affordable help desk software” and by cultivating discussion on reddit. The absence of G2 and the near-absence of dedicated IT communities outside of reddit mean that deep review data barely registers. The assistants leaned on what was easy to retrieve, not necessarily what was most thorough.
The Source-Product Pipeline: Vendor Domains, Reddit, and the Long Tail
Freshdesk showed up in five of six answers not because the assistants independently determined it was the best help desk software, but because Freshdesk appears across the widest range of source types the assistants pulled from. It was named in response to a value query that relied on crm.org and quora.com, a free-tools query that leaned on reddit.com and zoho.com, and a general recommendations query that fed from pcmag.com, thecxlead.com, and techradar.com. No single domain delivered Freshdesk its five mentions. Instead, it was the one product that managed to appear across editorial roundups, Reddit threads, and vendor sites simultaneously, a coverage breadth that effectively made it recommendation-proof.
HaloITSM and Help Scout, each at four mentions, followed a similar pattern but with tighter margins. HaloITSM surfaced in answers that cited crm.org, reddit.com, pcmag.com, quora.com, and thecxlead.com. Help Scout showed up in responses backed by pcmag.com, reddit.com, thecxlead.com, and zendesk.com, plus a salesforce.com-fed answer. These products are not necessarily more present in the source pool than others, but they happen to sit at the intersection of a few high-frequency domains. The data cannot tell us whether any assistant ever selected them directly from a domain or whether they emerged from a synthesis across sources. We can only observe the co-occurrence.
The tightest connection between a product and a source comes from ProProfs Help Desk, named three times alongside four appearances of proprofsdesk.com as a cited source. The vendor’s own domain fed a free software answer, a small teams answer, an affordability answer, and a recommendations answer, and ProProfs was named in three of those four. The assistants did not reject self-referential content. They incorporated it alongside Reddit and pcmag.com as if it were independent analysis. That is a direct line from a product page to a recommendation. Desk365 shows the same loop in miniature: desk365.io appeared twice, and Desk365 was named twice. Zoho Desk, mentioned three times, coincides with two zoho.com citations, though it also appeared in answers that used reddit.com and crm.org, so the connection there is looser.
The products that surfaced only once tell the other half of the story. Alvao was named in a single answer alongside sources that included bluetweak.com and realtech.com, niche domains that did not appear in any other query. BlueTweak itself was named in that same answer, a product and its own domain entering the set together. Raiseaticket appeared once, and raiseaticket.com showed up once. Atera, TeamSupport, Vivantio, and ServiceNow each got a single mention, often in answers that pulled from a single editorial list or a specialised community thread. These products are not absent because assistants evaluated them and dismissed them. They are absent because the source pool for the queries we asked did not carry them more than once, and no assistant went outside that pool to find them.
What we cannot determine is whether the assistants ever exercised judgment. They might have ranked or filtered the products they found, or they might have simply echoed the most frequently occurring names across the sources they scraped. The raw counts give us no insight into that process. Nor can we see how much each source contributed to a given mention. When an answer listed six products and cited five domains, any product could have come from any domain. We also cannot account for time. A product that was named once might dominate a source that was not in our retrieval window, or that a different assistant build would have surfaced. The data shows which products were swept up by the current configuration of three assistants and a small set of queries, nothing more. Freshdesk’s five mentions reflect coverage, not supremacy. The products at one and two mentions reflect narrow sourcing, not inferiority. The lens is the source list, and the picture it gives is of a recommendation engine that converts domain frequency into product mentions, with only Reddit and a handful of vendor sites anchoring the conversion.
If You Sell One of These Products, You’re Defending a Page, Not a Platform
The mention counts look like standings: Freshdesk at five of six, HaloITSM and Help Scout at four, a cluster at three or two. But that order is not a ranking. It is a snapshot of which source pages the assistants happened to surface across six specific questions, and it can invert with one editorial refresh or one well-timed Reddit thread. What a vendor actually defends is a fleeting intersection of forum chatter, review-site list placement, and how the assistant’s retrieval mechanism weights those domains. The position is less safe than it looks because no product showed up everywhere, and the gaps reveal how easily an assistant drops a name when the prompt changes by a few words.
Freshdesk missed the broadest query in the set, “best help desk software.” That answer drew on crm.org, reddit.com, pcmag.com, zendesk.com, quora.com, and g2.com, none of which surfaced Freshdesk for that specific prompt, even though Reddit fed every answer. The product’s five mentions came from a patchwork of other query contexts: value-focused, small-team, free-tool, and general recommendation prompts. That means Freshdesk is not immune to a single-source failure. If pcmag.com, which appeared in four answers, reorders its help desk roundup and bumps Freshdesk off the page for the “affordable” or “small teams” query, the mention count could drop to three overnight. The same is true for any vendor whose presence in the assistant’s output is tied to one editorial site updating its list.
HaloITSM’s four mentions tell a narrower story. It appeared in answers to “best help desk software,” “best help desk software for small teams,” “what help desk software should I use,” and “help desk software recommendations,” but it was completely absent from the “best free” and “most affordable” prompts. If a buyer asks about free or cheap help desk tools, HaloITSM does not show up. A competitor with a credible free tier that gains traction on Reddit (the one domain that fed all six answers) could push HaloITSM out of the “small teams” or “recommendations” responses too, because those answers drew heavily on Reddit alongside review sites. That would leave HaloITSM visible only in the straight “best” query, which is the one Freshdesk already missed.
Help Scout is in a similar bind. It showed up in four answers but missed both “best help desk software” and “best free help desk software.” Its mentions cluster around affordability and small-team contexts. The assistant treats Help Scout as a contender when the question signals budget or team size, but not when the prompt is unbounded. If a new entrant lands a top spot on crm.org or thecxlead.com for “most affordable,” the ground shifts quickly. ProProfs Help Desk, at three mentions, lives on even thinner ice: its own domain, proprofsdesk.com, was sourced in four answers, yet the product only appeared in three. An assistant crawling its vendor page does not guarantee inclusion. A change in how the assistant ranks self-claimed pricing pages would erase ProProfs from the free and affordable prompts where it currently sits.
For Zoho Desk, Desk365, Freshservice, HappyFox, and Zendesk, the count is two or one. These products are not recommendations yet; they are inclusions on a specific source page that the assistant happened to retrieve for one or two queries. Zendesk illustrates the fragmentation: the assistant treated “Zendesk,” “Zendesk for Employee Service,” and “Zendesk Support Suite” as separate entities, leaving no single Zendesk product with a count above two. A seller in this position is not defending a seat at the table. They are defending a mention in a single Reddit thread or a single review-site subheading that an algorithm may deprioritize next week.
What would cost a vendor its mentions is never a grand product failure. It is a PCMag roundup that drops a paragraph. It is a Quora answer that gets updated or displaced. It is a Reddit thread from two years ago that finally fades out of the retrieval window while a new thread with different winners rises. The assistants all leaned on reddit.com as a constant, so the fastest way to fall off every answer at once is for community consensus to pivot. The second-fastest is for a source like proprofsdesk.com or desk365.io to change its on-page copy in a way that no longer matches the assistant’s question-similarity threshold. That is what a seller is actually defending: the wording on a handful of URLs that the assistants happen to pull into context today.
If You Were Not Named, the Absence Is Specific, Not Mysterious
Thirty help desk products appeared across the six answers. Yours is not one of them. That gap is not a verdict on your software. It is a mechanical absence from a defined set of pages that ChatGPT, Gemini, and Perplexity retrieved when we asked the six questions. Two dozen products got a mention because the assistants pulled them from a source page. You did not get a mention because your name did not appear on the right pages for the right queries. The start of the fix is not a rebrand, not a social campaign, not a pitch to an AI company. It is understanding which pages those were.
The source domains tell you where to be. Reddit.com fed all six answers. If you sell help desk software and a Reddit user has never typed your product name in a thread that the assistants surfaced, you are invisible on the most consistent source. That does not mean spamming subreddits. It means that the assistants used real user discussions as a signal, and those discussions must exist. Pcmag.com fed four of the six answers, appearing for the broad “best help desk software” query, the small-team query, and the recommendations query. A single editorial roundup on pcmag.com shapes multiple assistant responses. If your product is absent from its list, you miss those four answers.
What surprises is how often vendor domains themselves fed the answers. Proprofsdesk.com appeared as a source in four answers, each time when ProProfs Help Desk was named. Zoho.com fed two answers, always alongside a Zoho Desk mention. Desk365.io fed two answers, both for queries where Desk365 was named. This is not a pattern of assistants independently evaluating products. It is a retrieval pattern: when an assistant pulls a vendor’s page as a source for a query, that vendor gets a mention. Your own site may already be capable of feeding an answer if the assistant deems it relevant. But relevance is triggered by the query. In the “most affordable help desk software” answer, sources included zoho.com and desk365.io. Those domains did not appear for the “best help desk software” query. The difference is not the assistant’s preference but the content of the pages matching the query’s intent.
What the work involves for an unmentioned vendor is mapping specific queries to the pages that won them. For “best help desk software,” the sources were crm.org, reddit.com, pcmag.com, zendesk.com, quora.com, and g2.com. To appear there, you need a presence on crm.org’s comparison piece, a mention in the relevant Reddit thread, a listing on that pcmag.com roundup. For “best free help desk software,” the answer drew from reddit.com, community.spiceworks.com, proprofsdesk.com, desk365.io, zoho.com, and raiseaticket.com. Spiceworks community discussions and a vendor’s own free-plan page all played a role. The work is narrow and page-specific, not a general brand awareness push.
What this does not involve is chasing the assistants’ internal ranking logic. There is no prompt engineering to be done on your end to make ChatGPT, Gemini, or Perplexity prefer you. The measurement shows that being named is a function of being on the pages the assistants already retrieve, and the assistants change those sources more slowly than a blog post goes live. Your absence means the pages they used, six times in a row, did not contain your name. You cannot control Reddit threads directly, but you can ensure that when a question like “best help desk software for small teams” surfaces quora.com and salesforce.com as sources, your answer appears on Quora and your partner page appears on a Salesforce marketplace listing. You cannot force pcmag.com to update a roundup tomorrow, but you can know that pcmag.com fed four of six answers and treat that domain as a priority in your analyst relations and PR calendar.
One uncertainty remains: the same question asked again next week could pull a different Reddit thread or a refreshed editorial list. The retrieval is not frozen. But the list of domains that mattered here is not infinite. The long tail is long, but the head is reddit.com (six of six), pcmag.com (four of six), and a set of vendor domains that punch above their weight when they match the query. If your product is nowhere in those places, you will stay unnamed. The mechanism is that simple.
How to Run This for Your Own Category by Hand
You can replicate this measurement for any software category in an afternoon. All you need is access to ChatGPT, Gemini, and Perplexity (all have free tiers), a spreadsheet, and a handful of verbatim questions. The process is simple: ask each assistant the same six questions, extract the product names and source domains from the answers, tally them, and look for gaps. The dullness of the workflow is the reason most teams never do it, and also the reason the results are worth having.
Start by writing six questions that mirror how someone shops. Don’t overthink them. Use straightforward, conversational prompts like “best [category] software”, “best [category] for small teams”, “what [category] should I use”, “best free [category]”, “most affordable [category]”, and “ [category] recommendations”. Copy each one exactly as you’ll paste it. Open three browser tabs, one for each assistant, and feed them the first question. Wait for the answer, then open a new chat for the next question. You want clean sessions, no memory bleed.
From each answer, extract two pieces of data: every product named, and every source domain the assistant cites. Some assistants surface their sources inline, others list them at the end, and a few mix both. Spelling and casing will vary (osTicket vs. OsTicket, JIRA Service Management vs. Jira Service Management), so you’ll need to normalise names as you go, cross-checking against the assistant’s own links to confirm the product. This is where the tedium sets in. You’ll scroll through paragraphs of explanatory text, copy-paste URLs, backtrack to catch a product mentioned in passing but not in the final summary, and repeatedly ask yourself whether “Zendesk Support Suite” and “Zendesk for Employee Service” count as separate products (they do, because the assistant named them separately).
Once you have a messy list of products and domains per question per assistant, consolidate them into two tallies: how many of the six answers each product appeared in, and how many answers each source domain fed. The number of assistants doesn’t multiply the tally in a straightforward way, because a product can appear in two assistants’ answers for the same question but only counts once per question for your overall frequency. You’ll build a matrix: rows for products, columns for the six questions, marks for any assistant mentioning it. Count across rows for the mention tally. Do the same for domains. Expect 20 to 30 unique products and a similar number of source domains. All of this is done manually if you’re on a free tier.
What makes the exercise tedious isn’t complexity but repetition. You’ll paste the same questions, read variations of the same advice, and hunt through similar-looking source lists. You’ll catch a product you missed three questions ago and have to check all prior entries. You’ll discover that an assistant occasionally hallucinates a product name that doesn’t exist, forcing you to verify. A single category can eat two to three hours. That time commitment is the real filter, and it’s why the numbers in a measurement like this feel more like competitive intelligence than marketing fluff. If you do the work, you’ll know exactly where your product stands, and where it vanished.