AI Engines Still Can’t Detect Reddit Astroturfing: 2026 Report

Key Takeaways:

• Astroturfed Reddit threads reach real users: Confirmed manipulated threads were cited in live ChatGPT and AI Overview summaries, framed as organic recommendations.

• Manipulation does not displace legitimate brands: In all confirmed cases where an astroturfed competitor was named, brands with genuine authority appeared in the same answer.

• Unmoderated personal-profile (r/u_) pages are cited at roughly twice the rate of genuine discussions, despite a third of retrievals per thread.

• ChatGPT and AI Overviews are high-risk surfaces; Perplexity is currently and, most probably, temporarily resistant.

Executive Summary: As part of Reddit citation research, ZeroClick Labs analyzed 119 of the highest-retrieved threads across 21 brands. We confirmed 22 instances of astroturfing, ranging from spun-template comment clusters to openly sold seeding services. Manipulated content reaches live AI answers, cited by name on ChatGPT and AI Overviews, while Perplexity currently remains resistant. Although it might not displace authentic brands, astroturfing manufactures a consensus that answer engines keep restating as facts.

Methodology

Time period: 30 days (June 1-30, 2026)

Sample: 21 active Peec AI client brands

Source: Peec AI (chat-level retrieval and citation data; complete June volume)

Full-text read: 119 of the 714 retrieved threads (16.7%) read in full; weighted toward the highest-retrieval and highest-suspicion material.

Engines analyzed: ChatGPT, AI Overviews, Perplexity (primary); Gemini, AI Mode (included for completeness)

Taxonomy: 8 industry categories – SaaS, Home Services, Education & EdTech, Digital Marketing, Renewable Energy, Automotive, Medical, Property Management.

Metrics:

• Retrieved % – share of chats surfacing 1 or more reddit.com URL.
• Retrieval rate – average Reddit URLs pulled per chat.
• Blended citation rate (“blended rate”) – citations ÷ retrievals (can exceed 1.0 when a page is cited more than once)

Prompt volume: 459 tracked prompts running daily across the month.

Anonymization: All client brands and named competitors anonymized throughout.

A note on the findings: Because roughly a sixth of threads were read in full, every manipulation example is a confirmed instance, not a prevalence rate.

Most of Reddit discussions are real.

Worth upfronting, because a report on manipulation tends to pull toward an opposite conclusion. That being said, as part of our study of Reddit usage in AI responses, we read 119 of the most frequently cited threads in full, and we can say:

Manipulation is also real.

It is also more sophisticated and more openly practiced and sold than we expected.

And AI engines cite it – by name, as consensus.

For that exact reason, understanding the dynamic of astroturfing is a major part of AI SEO,  not just to counter it, but to get ahead of it.

Why did Reddit become a high-value manipulation target?

Reddit owes its status as a prime astroturfing target to several factors, the key ones being a large user base (130+ million Daily Active Unique (DAUq) users), high search visibility (traditional and AI), and authenticity (human-written content equals high trust).

This is the core of it, but not all of it. In recent years, and especially during the first half of 2026, a set of commercial factors converged which intensified Reddit’s potential for manipulation. 

It must be noted that Reddit did NOT become a prime astroturfing target because of AI search; it held that status long before generative engines became mainstream, or even existed. What AI did is make it easier, cheaper, and more profitable than ever to manipulate it at scale.

Compounding search visibility

During mid-2025, Reddit became one of the highest-cited sources in AI-generated answers, with virtually every frontier LLM using it to synthesize their answers to some degree. In addition, Google and OpenAI both have multi-million-dollar data licensing agreements with Reddit, which they use to train their AI models. Those benefits go both ways, and it shows.

Google Search consistently positions Reddit threads front-and-center at SERPs for high-value commercial keywords, and its AI engines (Gemini, AIOs, AI Mode) heavily retrieve it. Although they cite it sparingly, the answers are still shaped by the information coming from the platform.

Similarly, OpenAI’s engine heavily relies on Reddit for its answers, and it doesn’t refrain from showing it. While ChatGPT retrieves Reddit at almost half the rate of AIOs (15.1% vs. 27.8%), it cites it roughly 10 times more frequently (1.75 vs 0.17 blended).

As a result, Reddit is uniquely positioned for double exposure, enjoying sky-high traditional and AI visibility alike, which is exactly what makes it an ideal surface for advertisement – and astroturfing.

Compounding trust

For years, Reddit has widely been considered the ultimate source of “truth” for humans and LLMs alike. Even long before AI, users have been appending “reddit” to Google queries to find genuine, human answers, and that sentiment persists, only intensifying in the AI era.

However, as of late 2024 / early 2025, AI-generated content officially surpassed human-written content, culminating in the widespread collapse of trust in the open web. In that ever-growing field of slop, Reddit perseveres as a bastion of authenticity. 

This trust is precisely why marketers, legitimate or otherwise, target Reddit: it is one of the last places users believe it will provide them with authentic, unbiased, human answers. And this belief is what makes manipulation tactics so effective.

What makes Reddit valuable to readers is what also makes it valuable to manipulators.

A service market has formed around the opportunity

Black-hat GEO/SEO vendors are now selling Reddit “seeding” as a service, going so far as to advertise it in the open, and the key reason for this is that AI tools made maintaining these “services” dirt-cheap.

Pre-AI, astroturfing was extremely expensive and bottlenecked by human labor: manipulators had to run entire armies of human laborers who had to manually write distinct posts to avoid Reddit’s spam detection filters. AI has sunk those costs to near zero.

Now, these bad actors can near instantly generate millions of unique personas, deploy them via hijacked aged accounts, and manage them almost effortlessly – and do it all on a fraction of the budget.

Worse, these AI bots are highly sophisticated, mimicking human slang, staggering their posting schedules, adapting seamlessly to a subreddit’s specific culture, and cross-upvoting their own content to boost visibility. The result: spam that no longer looks like spam, and bots that no longer look like bots.

What is astroturfing?

Astroturfing is a deceitful practice of planting promotional content to manufacture the appearance of grassroots consensus. Within the Reddit context, this entails planting posts, comments, or entire threads designed to look human: spontaneous, independent, organic. 

The objective is to create artificial consensus around a brand/product/service that looks and feels real, so that a reader mistakenly interprets a paid or coordinated push for a genuine view of the community.

Only, in 2026, the target reader is no longer a human scrolling the thread, but increasingly the model parsing it.

What are the confirmed astroturfing patterns?

As part of our Reddit citation research, we performed a full-text content analysis of 119 top-ranked Reddit threads across 21 projects, specifically for signs of manipulation. We found and confirmed 22 instances of astroturfing (18 manipulation + 4 community-flagged), recurring across six distinct patterns:

• Cross-thread templated campaigns
• Spam-filter evasion
• Hijacked aged accounts
• Campaigns instrumented for AI
• AI-generated posts (w/ admission)
• Self-advertised astroturfing-as-a-service.

Table #	Sub-section	# of campaigns / projects / industries
1.1	Cross-thread template reuse	5 campaigns, 6 of 21 projects, 3 industries
1.2	Filter evasion and moderation bypass	3 campaigns, 3 projects, all Home Services
1.3	Hijacked and compromised accounts	1 campaign, 2 projects, Home Services
1.4	Campaigns instrumented for AI	33 of 714 threads (4.6%), 16 of 21 projects
1.5	AI-generated content	4 instances, 4 projects, 3 industries
1.6	Rigged listicles, paid placement, astroturfing-as-a-service	5 instances, 3 projects, 2 industries

Cross-thread template reuse & coordinated testimonial clusters

The pattern: An almost- or fully-identical testimonial (same narrative arc, same oddly specific phrasing) reposted across multiple separate threads.

We found 5 distinct cross-thread campaigns spanning 6 of 21 projects, across 3 industries: 4 in Home Service, 1 in SaaS, and 1 in Property Management. Template reuse was rarely the only mechanic: many featured signs of other manipulation practices (covered in their own sections below), including moderation evasion, hijacked accounts, single-purpose ad accounts, and keyword stuffing/permutation spam. The examples here isolate template reuse and testimonial clusters only.

Table 1.1: Cross-thread template reuse & coordinated testimonial clusters
Industry (top-line label)	Niche (Category)	Pattern	Example
Home Services	Cleaning services	Near-identical testimonial posted across two separate r/StLouis threads	“Finding someone reliable” ↔ “finding someone consistent”; “same people show up, they know where everything goes” ↔ “same crew each time”; “went through two franchise services… eventually switched to [brand]” ↔ “tried a few before settling on [brand]”
Home Services	Cleaning services	At least 15 short, similarly worded, glowing testimonials clustered across four threads;At least 9 in a single thread (see screenshot 1.1.2);One also carries a referral link that survived auto-moderation (see 1.2)	See screenshot 1.1.2
Home Services	Garage doors / door installation	One templated lead-gen comment seeded into a garage-door thread(see row below)	“dude i had this exact problem like a month ago… finally used [brand]… wish i knew about it sooner…” See screenshot 1.1.3-4
Home Services	Water damage restoration	Same template, two variants one comment apart (see row above); completely unrelated project, indicating one campaign seeding a single phrase across multiple home-service verticals; Posted from a compromised account (see 1.3)	“dude, i get it. sounds like a nightmare. i had a similar thing with a busted water heater a while back… felt totally rushed… finally found something that works with [brand]… wish i knew about this sooner, honestly.”“Dude, yeah i get it… happened to me with a leaky roof a while back… felt like they just patched it up quick… i started using [brand]…”See screenshot 1.1.3-4
SaaS	Field-service / cleaning-business software	Two different named products appear with word-for-word identical bulleted ad copy across two r/smallbusiness threads	See screenshot 1.1.5
Property Management	Short-term rental management	Programmatic SEO applied directly to Reddit;Same company, same address and phone, posted 7 times from one account with the same core pitch recombined into keyword permutations (from a personal-profile ad account – see 1.4)	“short-term rental property management Los Angeles”“vacation rental management Los Angeles”“Airbnb property management Los Angeles”

Spam-filter evasion & moderation bypass

The pattern: invisible characters embedded into a word to break the string an anti-spam filter is matching on; links survive moderation rules that would have otherwise removed them. The only purpose of these techniques is to get promotional content past automated moderation.

Evasion techniques surfaced in 3 campaigns across 3 of 21 projects, all within Home Services, spanning three unrelated niches. The most telling detail here is repetition: an invisible zero-width character appears in two campaigns run by different operators in unrelated categories, pointing to a reused technique (as opposed to a single bad actor).

Table 1.2: Spam-filter evasion & moderation bypass
Industry (top-line label)	Niche (Category)	Pattern	Example
Home Services	Window treatments / decorating	Unicode character (U+034F) stitched into the middle of the word “recommendations,” in both of the campaign’s NYC-subreddit posts – invisible to a reader, enough to break a text-matching filter	recomme\u034fndations(See ss 1.2.1)
Home Services	Water damage restoration	Same zero-width obfuscation, different Unicode character (U+2064) applied to a link for a “free AI-powered mold remediation cost calculator”different operator, different vertical, identical technique	fr\u2064ee
Home Services	Cleaning services	Referral-program link persists in a subreddit whose auto-moderator explicitly bans referral codes, while unrelated self-promotion in the same threads was visibly removed in real time	n/a

Hijacked & compromised aged accounts

The pattern: a real, aged account with genuine posting history and positive karma, hijacked and used to post promotional comments. These types of accounts circumvent Reddit’s post limitations for new accounts, which is precisely what makes them valuable.

This pattern appears only once in the dataset, but it is worth its own section purely for the fact it is almost always invisible – a hijacked account is indistinguishable from a legitimate one, because that’s exactly what it is (or, rather, was). We caught this one just because the real owner regained control and publicly disavowed the promo comment.

Table 1.3: Hijacked and compromised aged accounts
Industry (top-line label)	Niche (Category)	Pattern	Example
Home Services	Water damage restoration;Same campaign also seen in garage doors (see 1.1)	Lead-gen comment posted from an established account; the account’s genuine owner posts a disavowal directly underneath it	“I briefly lost control of this account and the below comment was NOT by me. I have no idea what this topic is…” (see screenshot 1.3.1)

Campaigns instrumented for AI retrieval & tracking

The pattern: Single-purpose ad accounts & press-release reposting

Reddit generates a personal profile subreddit (r/u_username) for every account. These accounts carry no community moderation and no subreddit rules, meaning they function as free, unmoderated hosting for content formatted to look like a Reddit thread. The problem is that they are indexed and retrieved as such.

Table 1.4: Campaigns instrumented for AI retrieval and tracking
Industry (top-line label)	Niche (Category)	Pattern	Example
Home Services	Home remodeling (competitor content)	Heavily formatted guide linking to the operator’s own site with an AI-attribution tracking parameter, indicating that the operator is measuring how much traffic ChatGPT sends them from this exact post	?utm_source=chatgpt.com appended to a hyperlink(see screenshot 1.4.1)
Renewable Energy	Solar (competitor content)	Full, unedited ~700-word third-person corporate press release about a competitor’s product launch, reposted verbatim to a personal-profile subreddit	Excerpt: This exhibition will last to June 16, and [brand] will make a debut in this event with a full range of [products], adapting to different application scenarios with innovative technologies and green intelligent manufacturing…
Property Management	Short-term rental management	Seven near-identical pitches from a single account, same address and phone throughout (keyword-permutation detail in 1.1)	See screenshot 1.4.3
SaaS	Web accessibility	“Top 15” agency listicle: entry #1 receives a bolded promotional paragraph and a call-to-action; entries #2-15 receive one generic sentence each; the post closes by re-linking entry #1. Highest citation rate (3.75) of any thread in the 714-row dataset	See screenshot 1.4.4

Personal-profile subreddits spearhead manipulation

This is the most quantifiable astroturfing pattern in our dataset and the most counterintuitive finding of our study: 33 of 714 tracked threads (4.6%) across all verticals come from personal profile subreddits, and appear in 16 of 21 projects. 

Despite carrying roughly a third (~35%) of the retrieval volume on average, these threads boast a blended rate of 1.98 vs 0.93 of ordinary subreddits. Although that rate rests on a thin base (240 citations from 121 retrievals vs 7,033 baseline), the directional conclusion is stark nonetheless:

AI engines cited unmoderated, single-purpose promo pages at twice the rate of genuine community discussions.

Table 1.4.1: Prevalence of personal-profile subreddits in astroturfing examples
Industry (top-line label)	Niche (Category)	Pattern	Example
Portfolio-wide (16 of 21 projects)	All tracked verticals	33 threads hosted on r/u_ personal-profile subreddits, ranging from bare name/address/phone listings to discount-code ads to polished buyer’s-guide posts	4.6% of tracked threads;Blended citation rate 1.98 vs 0.93 for ordinary subreddits(base: 240 citations / 121 retrievals)

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AI-generated content

The pattern: posts and comments drafted by an LLM and presented as first-hand experience. Posts and comments in these threads have all the tells of content formatted for AI extraction, rather than human reading.

We’ve confirmed four instances across 4 of 21 projects and 3 industries: Digital Marketing, SaaS, and Home Services (2 projects). Two (Digital Marketing & SaaS) were confirmed by the author’s own admission and a community catch, respectively. The two in Home Services were confirmed by structural signature.

A more interesting finding in this section is that two original comments were removed by the moderator months or a full year ago – yet the engines still retrieve and cite them. This behavior is well-documented and typically stems from one or more of the following mechanisms:

• Outdated search indexes: Answer engines keep their own copy of web pages, which often lag far behind live updates and moderation on the actual site.
• Training data persistence: If AI “learned” from the comment while it was still live, that knowledge remains baked into its memory long after the source post is gone.
• Web archives & mirrors: Automated scrapers frequently create duplicate snapshots of live content before moderators remove it, and LLMs can easily find and access them.

Regardless of the exact mechanism, the implications remain the same: deleted content can continue to influence generative answers for extended periods of time.

Table 1.5: AI-generated content
Industry (top-line label)	Niche (Category)	Pattern	Example
Digital Marketing	AI search / GEO	Accused of AI authorship by commenters who spotted the structure and tone, the OP confirms it outright – three times	Accusation: “OP used AI to write a post on basically how to get AI to see your posts…” OP: “Yes I used ai to convert my findings into well structured format…” Accusation: “Bro forgot to remove the long em dashes after he had AI write this. ” OP: “I didn’t remove as ai structured it in a format- I was expecting.” Accusation: [Comment deleted] OP: “I used ai to convert my finding into a structure post, whats the issue?”
SaaS	Cleaning-business software	A comment in the highest-retrieval thread in the entire dataset (775 retrievals) is called out and independently confirmed by a second user INTERESTING: OG comment removed by moderator, yet AIs still retrieve it.	[OG comment removed by moderator] User 1: “Dude is just copy pastimg AI slop” User 2: “Absolutely lol. I think I looked into it right away and knew.”
Home Services	Water damage restoration	An entire Q&A thread with no personal narrative: the OP poses four numbered questions built around an invented market statistic, and multiple “answer” comments restate the same four numbered questions verbatim before answering with oddly specific, example-flavored dollar figures INTERESTING: OG post removed by Reddit filters, yet AIs still retrieve it.	Invented “$12 billion market” statistic; answers quoting $4,800 / $11,200 / $14,000
Home Services	Home remodeling (competitor content)	Virtually every signature of AI-generated contentthe same post carries the AI-attribution tracking parameter (see Table 1.4) Result replicated in August 2026 (see screenshot 1.5.5)	Cliche hooks, excessive bullet/numbered lists, hashtag block, keyword permutations, em-dashes, and a “final thoughts” close restating the introduction

Astroturfing-as-a-Service

The pattern: Posts forming a commercial market that openly advertise astroturfing services, including supplying self-promotional content (rigged listicles), selling the placements, and building the tools.

In this subset, we’ve confirmed two rigged listicles, one in-thread ad, one genuine operator admission, and one described bot, spanning 3 of 21 projects across SaaS and Digital Marketing. This is where our “Reddit seeding service advertised in the open” claim gets confirmed, repeatedly.

A perfect and blatant example (see screenshot 1.6.4): One thread contains an admission of a duplicate-content campaign instrumented for LLM manipulation by the OP, AND an in-development astroturfing tool promotion by a commenter – who then pitches it to the OP. The thread ends with OP saying: “Sounds Interesting. Let’s connect!”, marking what we can only assume is the beginning of a beautiful astroturfing collaboration.

Table 1.6: Astroturfing-as-a-Service
Industry (top-line label)	Niche (Category)	Pattern	Example
Digital Marketing	AI SEO / GEO agencies	A commenter names an agency as running a series of fake Reddit listicles specifically to manipulate LLM citations, pointing to a second, nearly identical thread as further evidence; a commenter in that second thread independently makes the same accusation	Thread 1: “Seems to me like [brand] is creating a series of fake Reddit posts with listicles of them at the very top of the list to influence LLMs (like this one and this one [commenter-provided links]… Smart idea, it definitely works.” Thread 2: “Worth saying out loud: someone above already flagged this post as a probable seeded listicle, and looking at the comment section, most of the substantive replies are agencies (with varying levels of disclosure) talking their own book. Which is itself a useful lesson, this thread is the tactic working in real time.”
Digital Marketing	AI SEO / GEO agencies	Direct in-thread advertisement for a named commercial service guaranteeing Reddit thread rankings on Google’s first page on a fixed timeline	“I am personally working with [brand], they specialise in creating reddit threads and indexing them to google’s first page (all within 60 days or you don’t pay them).”
Digital Marketing	SaaS / SEO	Commenter describes a tool they built that scans target subreddits for brand-relevant keyword mentions and auto-generates AI replies designed to read as human, offering to share it	Replies designed to “compliment + promote” a brand [see screenshot 1.6.4]

Where’s the line between astroturfing and legitimate community marketing?

The distinction lies in honesty (disclosure) and voice (authenticity). A brand genuinely participating on Reddit (which many do) will include some form of disclosure. Here are several examples from our dataset, verbatim:

• “This is a bit of a sales pitch for what i’ve been building. I can appreciate if moderators would prefer to remove this post, I understand.”
• “(I am an installer in NYC and would glad to discuss further)”
• “ I’m a general contractor here in Portland…” (followed by contact info)

Examples like these abound on Reddit, ranging from radical honesty (“I’ll be upfront: this is a bit of a self-promotion post…”) to playful honesty (“Shameless plug: Check out our company website…”). Either way, the effect is the same: a reader knows exactly what they’re seeing. That’s authentic disclosure marketing, and users appreciate and reward it.

Ten near-identical high-praise comments from different accounts or one account’s copy/paste posts across several subreddits is engineering an appearance of independent consensus. Either way, the reader thinks they know what they’re seeing. That’s astroturfing – and users resent it. AIs don’t care – and cite them anyway.

Does astroturfed content ever reach real users?

During the first week of July 2026, we traced flagged threads into live AI answers, focusing on those that contained a confirmed instance of manipulation. We’ve confirmed that the astroturfed content is reaching users consistently, whether directly or indirectly.

In the clearest direct cases, the astroturfed competitor was cited by name in the live answers, and described as “popular in discussions,” “frequently mentioned,” or “frequently recommended.” 

The clear conclusion is that the synthesizing engine pulled a handful of coordinated posts, interpreted them as evidence of organic popularity, and presented them in the live answer as authentic consensus.

Table 2: Examples of direct-citation astroturfed content in live answers
Competitor industry / niche	Astroturfing pattern	Description in live AI answer
Property Management / Short-term rental management	Seven-post keyword-permutation spam cluster promoting the same company(Table 1.1 & 1.4)	Described as “popular in LA market discussions”
Home Services / Cleaning services (Toronto)	Coordinated cluster of promotional comments across multiple Reddit threads(Table 1.1)	Cited as one of the companies “Toronto Reddit discussions also frequently mention… as dependable options”(see screenshot 2.2; result replicated in August 2026)
Home Services / Window treatments (Manhattan)	Unicode-obfuscated promotional posts across multiple NYC subreddits(Table 1.2)	Described as “frequently recommended for motorized window treatments in NYC discussions”

In subtler, indirect cases, the astroturfed post never surfaced the exact brand name, but it did shape the frame of the live answer. The prime examples are the competitor’s UTM-tagged cost-guide post (described in Table 1.4), and a plugged tool beating the OG astroturfed one (described in Table 1.6).

This post was ChatGPT’s most consistently cited source for that project, and by a wide margin: 2-3 citations on nearly every retrieval across weeks, versus zero for most organic threads in the same set. Despite not returning the actual brand name, the influence was obvious in the pricing-tier structure of the live answer.

Similarly, AI Overviews’ single most cited source was also a manipulated thread. In this instance, a particular third-party tool was repeatedly plugged throughout the comments, and that tool ended up recommended in AIOs’ live answer instead of the one the OG thread was promoting.

A critical caveat regarding the “instead” part: no brand was pushed out of the answer. The plugged tool filled a gap rather than overtaking anyone’s organic ranking position, plausibly because neither the OG nor the tracked brand were established enough in the space to hold that spot.

Key observations: 3 patterns that hold

Across the tracked answers, three patterns persisted consistently:

1. Both the OG post and the comment section are active manipulation vectors.
2. Astroturfing rarely knocked legitimate brands out of the answers – they appeared alongside them in all 3 cases; in one, the legitimate brands ranked higher than the astroturfed one.
3. In 4 of 5 cases, a thread containing confirmed astroturfing content was among or the most consistently cited source in live answers.

Which AI engine is most likely to surface astroturfed content?

Engines that rely on Reddit the most are the ones most likely to surface manipulated content. In our dataset, and for reasons mentioned in the beginning, these are ChatGPT and AI Overviews. Throughout June and July, both engines cited flagged threads on a near-daily basis, frequently with one to three citations per response.

The likelihood of astroturfed content appearing in AI answers is directly tied to a specific engine’s baseline behavior toward Reddit:

• ChatGPT retrieves selectively but cites heavily (1.75 blended), often more than once per answer, and tends to frame the output as a confident “the community recommends” claim.
• AIOs retrieve heavily but cite selectively (0.17 blended), attributing what little citations make it into the visible answer narrowly and to a specific community.

The caveat here is that ChatGPT and AIOs are the furthest thing from niche surfaces – they are the two platforms with the largest audience bases in AI search today, counting a billion and two billion monthly users, respectively. Meaning: When manipulation lands on ChatGPT and AIOs, it lands at scale.

Why is Perplexity currently resistant to astroturfing?

Presently, Perplexity’s reliance on Reddit is at an all-time low: it both retrieves and cites it orders of magnitude less than ChatGPT (6.6x fewer retrievals; 155.6x fewer citations) and AIOs (9.1x fewer retrievals; 20.7x fewer citations).

Since Perplexity disclosed no change to its retrieval and citation systems, we hypothesize that this dramatic behavioral shift resulted from a combination of two factors: Reddit’s active litigation against Perplexity over alleged unauthorized data scraping and Google’s recently updated anti-spam policies, which may have thinned the volume of threads reaching its pipeline.

Either way, the magnitude of the shift points toward a deliberate step back, which is why “presently” is the operating word here: a source that collapsed this rapidly can bounce back just as quickly. Therefore, Perplexity should presently be treated as a de-prioritized visibility surface, with astroturfing resistance as only a temporary bonus.

Which industries are most exposed to astroturfing?

The exposure follows the same logic as general Reddit visibility: brands whose query space maps onto active, loud conversations are most at risk of manipulation.

Digital Marketing & SEO/GEO

Unsurprisingly, this is the category that displayed the highest degree of self-awareness and the most openly practiced manipulation. Operators in these subreddits run, sell, discuss, confess to, and get exposed for doing the exact things this analysis describes – and they do so without hiding, often inside the very same threads the AI engines proceed to cite.

Home Services

This is the most bimodal category in our dataset. Some brands’ top threads were genuinely clean – just real people seeking advice (or arguing) about services and providers. Others, however, carry instances of confirmed, repeated campaigns. 

Cleaning and maid services, in particular, were heavily worked, followed by water damage and remodeling niches. However, design-build and general-contractor discussions in the same cohort were untouched, mapping back onto the finding in our foundational analysis:

The niche (sub-category) predicts exposure better than the top-line industry label.

SaaS

The SaaS category produced one of the most interesting findings of our research: behaviors that sit on two diametral extremes, coexisting in the same space – unrelenting vigilance and brazen manipulation.

The Accessibility niche housed the most self-policing expert community in the dataset (r/accessibility), enforcing disclosure harder than anywhere else. Yet, the same niche also produced the single highest citation rate (3.75) rigged thread we found.

An astroturfed “Top 15” agency listicle, cited 45 times on 12 retrievals, was housed on an unmoderated personal-profile subreddit, right where expert community’s vigilance couldn’t reach. Two conclusions follow from these findings:

• Knowledgeable operators do work expert spaces.
• Self-policing does not confer immunity.

A well-built piece of manipulative content targeting an authoritative niche can still top the citation chart, precisely because said niche is trusted and especially if it’s staged just outside the moderation range.

Education & Renewable Energy

Although these are two completely unrelated categories, they both inverted the pattern in the same, instructive way: the threads AI pulled were dense and organic, but the tracked brand was almost completely absent from them.

What little astroturfing surfaced here mostly appeared as competitor press-release reposts, rather than in genuine buyer discussions, indicating that manipulation wasn’t aimed at winning a thread, but rather at planting signals for AI to pick up later. In other words, the game being played here is corpus-seeding, rather than thread-seeding.

How to build astroturfing resistance?

Brands looking to boost their manipulation resistance should focus their attention where risks concentrate: highest-exposure surfaces, their own anchor threads, broader competitive conversation, and prioritizing authentic reputation over retaliation. 

Treat ChatGPT & AI Overviews as the highest-risk surfaces

ChatGPT’s and AIOs’ 3 billion monthly users combined mean high exposure – to genuine audience and bad actors alike.

1. For ChatGPT: Monitor the visible output on your key queries and treat the specific cited threads as visibility assets – to be watched and managed.
2. For AIOs: In addition to visible citations, track which threads are being retrieved, as it can help you catch and address factors that shape the answer.

Manage your Reddit visibility as a portfolio

For the median brand in our broader dataset, just five anchor threads carried well over half of Reddit retrievals.

3. Identify which specific threads carry your footprint.
4. Monitor those threads for accuracy, planted content, and reputation-risk threads.

Observe the wider competitive conversation

Most manipulation that happens in a brand’s general space is run by competitors or unrelated operators.

5. Scope a monitoring set to a broader brand space to catch campaigns most likely to (re)shape a category answer.

Prioritize building genuine, organic authority

In two out of three observed cases where an astroturfed competitor was named in live answers, the legitimate client brand appeared in the same answer – in some cases, ranked ahead of the competitor.

6. Earn genuine recommendations in 2 or 3 communities that actually drive your retrievals.
7. Contribute real expertise under a transparent identity, while openly disclosing your affiliation.
8. Prompt customers toward honest reviews, without scripting or curating what they say.
9. Build first-party authority with original, proprietary content so engines have a legitimate source to cite in the first place.

De-prioritize retaliation

It’s not just about the ethics of manipulative practices. In 2026, the risk profile has shifted against manipulation: Reddit now applies LLM-based detection to exactly the patterns described in this report, and Google’s anti-spam policy now explicitly names AI-answer manipulation as spam.

10. Think hard before fighting fire with fire – there’s a high chance for that strategy to backfire.

Jordan Parkes, the CEO and founder of ZeroClick Labs, has been building and scaling digital marketing strategies since 2012, leveraging performance-driven SEO and data-based digital marketing solutions to guide the growth of hundreds of companies across the U.S. and Europe.