How to Monitor If Your SaaS Is Being Recommended by AI (Free & Paid Tools 2026)

To monitor if your SaaS is being recommended by AI, run a fixed set of 10–15 buyer-language prompts across ChatGPT, Perplexity, Claude, and Gemini once a month and log brand mentions, position in the response, competitors named, and cited URLs in a spreadsheet. That free manual workflow is enough to know whether AI engines are recommending you right now. Once you have a baseline, paid tools like Otterly.ai ($29/month), Profound ($99/month), and AthenaHQ ($295+/month) automate the same checks across more platforms with daily cadence and competitive benchmarking.

TL;DR: AI-referred traffic converts roughly 4x higher than organic search, but most SaaS founders have no idea whether AI engines are mentioning them. This post gives you a free manual monitoring workflow you can start today, an honest breakdown of every paid AI monitoring tool by budget tier, and a direct path from "what monitoring reveals" to "what to fix next." No enterprise budget required.

You shipped the GEO work. You unblocked GPTBot. You added SoftwareApplication schema. You submitted to a few directories. Now what? Most founders skip the measurement layer entirely, then six months later wonder why none of it moved the needle. This post is the measurement layer. By the end you will have a free workflow you can run in 30 minutes and a clear sense of whether to graduate to a paid tool — and which one.

Why Monitoring AI Mentions Is a Different Problem Than Traditional Rank Tracking

Monitoring AI mentions is not the same problem as keyword rank tracking, and the tools you used for Google will not work here. Google rank tracking shows you positions 1–10 on a deterministic SERP. AI monitoring tracks something fuzzier: whether your brand is mentioned at all in a generated answer, where in the response it appears, what language describes it, and which competitors got named instead. There is no "position 7" to fall to — there is only mentioned or not mentioned, with shades of framing in between.

The other shift: AI traffic behaves differently once it lands. Multiple studies in 2025 found AI-referred visitors converting at roughly 4x the rate of organic search traffic, because the user has already been pre-qualified by the AI's recommendation. That makes invisibility expensive in a way Google ranking #11 never was. A category leader with no AI presence is leaving a high-intent channel entirely on the table.

If you have not yet diagnosed why you might be invisible, start with the 5-layer AI visibility diagnosis. This post assumes you have either fixed the obvious gaps or you want to measure your starting point before fixing them.

The Two Things You Are Actually Trying to Measure

There are exactly two metrics worth tracking, and most tools obscure them with dashboards full of vanity numbers.

Citation frequency is the percentage of relevant queries where your brand appears in the AI's response at all. If you run 20 prompts and your brand shows up in 6 of them, your citation frequency is 30%. This is your visibility floor.

Citation framing is how the AI describes you when it does mention you — first choice or also-ran, "the standard for X" or "another option to consider," named in the headline or buried in a caveat. Two products with identical citation frequency can have wildly different commercial outcomes based on framing alone.

Both metrics differ by platform. ChatGPT and Perplexity share only about 11% of their cited domains (per Averi.ai's 680M-citation analysis), which means you can be the default on one platform and entirely invisible on the other. You have to measure them separately. Treating "AI search" as a single channel is the most common monitoring mistake founders make, and it is the reason competitor posts on this topic produce misleading dashboards.

The Free Method — Manual Prompt Testing (No Tool Required)

The free method is a 30–45 minute monthly workflow that costs nothing and produces better data than most $99/month tools — because you can read context the dashboards strip out. Run it for two months before you spend a dollar on automation.

Build Your Prompt Set (15 Minutes)

Write 10–15 prompts in three categories. You will reuse this set every month, so make them count.

1. Discovery queries (4–5 prompts). "Best [category] tools for [audience]." Examples: "best invoicing tools for freelance designers," "best AI customer support tools for B2B SaaS," "what are the top project management tools for remote teams." Use the words your buyers actually type, not your internal product taxonomy.
2. Alternatives queries (3–4 prompts). "[Top competitor] alternatives" and "alternatives to [incumbent] that are cheaper." These are dominated by incumbents, but the AI's answer reveals exactly which products are in the consideration set for your category.
3. Comparison queries (3–4 prompts). "[Your brand] vs [competitor]" and "[Competitor A] vs [Competitor B]." Comparison queries surface the exact comparison pages and review sources AI engines trust most for your category.

Save the list in a file and never edit it casually. Consistency over months is what makes the data useful.

Run the Test Across Four Platforms

Run each prompt on four platforms in this order: ChatGPT (with web search mode on), Perplexity (standard search, not deep research), Claude (with web access enabled), and Google Gemini. The whole pass takes roughly 25–30 minutes for a 12-prompt set.

For each prompt-platform combination, log four things:

• Is your brand mentioned? Yes or no. The single most important data point.
• Position in the response. First named, middle of a list, last bullet, or only in a parenthetical aside.
• Exact language used to describe you. Copy-paste the verbatim phrase. This is the column most founders skip and later regret — framing changes are early signals of citation pool drift.
• Cited URLs. Perplexity displays them inline. In ChatGPT and Claude, ask a follow-up: "What sources did you use for that answer?" Log the top three.

The Monitoring Spreadsheet (Copy This Structure)

Open a Google Sheet and create one row per prompt-platform run. Columns:

| Date | Prompt | Platform | Mentioned (Y/N) | Position | Competitors Named | Description Language | Cited URLs |

Run 5–10 priority prompts monthly on the same date each month. Run the full 15-prompt set quarterly across all four platforms. After three months you will have enough rows to spot patterns: which platform is improving, which is stagnant, which competitor keeps appearing in the same slots you should be filling.

Flag any month where:

• Your position dropped two or more slots from the prior month
• A new competitor appeared on three or more prompts who was absent last month
• A previously cited URL was replaced by a new source you are not on

Each flag is a signal to investigate, not a panic trigger. Most months you will see slow drift in one direction or another. Monitor for two cycles before reacting.

Free Tools That Supplement Manual Testing

A handful of free tools complement the spreadsheet without replacing it:

• HubSpot AEO Grader — One-off snapshot of your visibility across ChatGPT, Perplexity, and Gemini. Good for an initial baseline. Not ongoing tracking.
• Answer Socrates LLM Brand Tracker — Free brand mention checker across ChatGPT, Perplexity, Gemini, and Claude. Useful for spot-checks between monthly runs.
• LLMrefs free tier — Weekly High/Medium/Low visibility score for one primary brand keyword. Trend signal, not detail.
• Am I On AI / ZipTie — Quick lookup tools to confirm basic AI mention presence. One-off rather than longitudinal.

Use these as supplements. None of them give you the description-language column, which is where the real intelligence lives.

Paid AI Monitoring Tools — Compared by Budget

Paid tools earn their cost when manual monitoring becomes the bottleneck — usually around month three of consistent tracking, when you want daily cadence, more platforms, and competitor benchmarking without spending a Saturday on it. Here is the honest breakdown by budget. Pricing is current as of early 2026 and changes regularly; verify before you commit.

Under $50/Month — Otterly.ai and Mangools AI Search Watcher

This is the realistic entry point for bootstrapped founders.

Otterly.ai — $29/month. Monitors brand mentions across ChatGPT, Perplexity, Google AI Overviews, and a few others. Provides a Brand Visibility Index, prompt suggestions, and competitor tracking. Free trial available, 20,000+ users, recognized on G2 and Gartner. Best for: founders who want automated daily checks without committing to enterprise pricing. Honest limitation: smaller platform coverage than higher-tier tools, and competitive benchmarking is lighter than what Peec AI or Profound provide at the higher tiers.

Mangools AI Search Watcher. Entry-level AI monitoring bundled with the broader Mangools SEO toolkit. Runs multiple prompts per checkup for accuracy. Best for: founders already paying for Mangools for traditional SEO who want AI visibility added to a tool they already log into. Skip if you do not already use Mangools — the standalone alternatives are stronger.

Nightwatch — from $32/month. Combines AI visibility with traditional rank tracking, 14-day free trial. Good if you want one tool covering both classic SEO and AI mentions.

$99–$150/Month — Profound and Peec AI

This tier makes sense once you are seeing real revenue from AI traffic and want competitive benchmarking and broader platform coverage.

Profound — from $99/month (Starter). Tracks ChatGPT only at the entry tier; scales to 10+ AI models including DeepSeek and Meta AI on higher plans. Strong analytics, 700+ customers, used by roughly 10% of the Fortune 500, $155M raised. Best for: growth-stage SaaS with a marketing budget. Honest caveat: the Starter plan is genuinely thin — most of the features the marketing site emphasizes (multi-model coverage, competitor analysis) require the higher-tier plans, which run several hundred per month. Read the feature matrix carefully before committing.

Peec AI — from $120/month. Tracks ChatGPT, Perplexity, Claude, Gemini, Meta Llama, and DeepSeek out of the box. Strong on competitive benchmarking and brand ranking comparisons. Free demo tier available. Best for: founders in competitive categories who want detailed share-of-voice analytics across all major models without paying enterprise prices.

LLMrefs. Analytics across ChatGPT, Google AI Overviews, Perplexity, Gemini, Claude, and Grok. 10,000+ marketers on the platform. Worth a look as a Profound alternative if you want broader model coverage at the entry price point.

$295+/Month — AthenaHQ and Visiblie

This tier is for teams that need attribution, not just tracking. If you are a solo founder, skip this section unless you have an unusual reason to be here.

AthenaHQ — $295–$499/month. Founded by ex-Google Search and DeepMind engineers, $2.7M from Y Combinator. The clearest value proposition in the category: revenue attribution via GA4 and Shopify integration. You can see which AI mentions converted to revenue, not just which queries surfaced your brand. Features include competitor impersonation testing and dynamic blindspot detection. Best for: marketing teams that need to attribute AI-driven revenue to a budget line item. Overkill for solo founders.

Visiblie. Tracks up to 8 AI models from one dashboard, including DeepSeek, Grok, Meta AI, and Mistral on the Enterprise plan. Best for: teams running global campaigns where coverage of non-Western models matters.

Scrunch AI / SE Ranking AI Tracker. Enterprise-grade alternatives, more relevant for in-house marketing teams than indie founders.

Quick Reference — What Each Tool Actually Tracks

Tool	ChatGPT	Perplexity	Claude	Gemini	Grok / DeepSeek / Meta
Manual workflow	Web search mode	Standard	Web access	Standard	Skip
Otterly ($29)	Yes	Yes	Limited	Yes (AIO)	No
Profound Starter ($99)	Yes	No	No	No	No
Profound higher tiers	Yes	Yes	Yes	Yes	Yes
Peec AI ($120)	Yes	Yes	Yes	Yes	Yes
LLMrefs	Yes	Yes	Yes	Yes (AIO)	Grok
AthenaHQ ($295+)	Yes	Yes	Yes	Yes	Yes
Visiblie Enterprise	Yes	Yes	Yes	Yes	All four

The detail competitor posts skip: most tools that advertise "ChatGPT tracking" track ChatGPT's web search mode, not the base-model retrieval pool. If a tool does not specify, assume web search mode only. Base-model coverage genuinely requires API access and synthetic prompt evaluation, which only the higher-tier paid tools handle properly.

How to Read What You Find — And What to Do Next

Monitoring data is only useful if it triggers a fix. Map every pattern in your spreadsheet to one of these four action paths.

If you are mentioned but always third or lower: This is a citation framing problem. The AI sees you as an option but not the option. Revisit vocabulary alignment (Layer 5 of the 5-layer AI visibility diagnosis) and seed consistent positioning language across every directory listing, G2 review prompt, and comparison post that mentions you. AI engines pull verbatim phrases from sources they trust — repetition of the same one-line positioning across 10+ sources gradually displaces the "another option" framing.

If you are not mentioned at all: This is an entity footprint problem. Your product is not in enough trusted sources for the AI to cite you with confidence. Return to the 5-layer diagnosis and confirm Layers 1–3 are clean (crawl access, JS rendering, structured data), then prioritize Layer 4 work. The fastest single fix for a thin entity footprint is a verified listing on a curated, schema-marked directory. TheSaaSDir, a curated directory of SaaS and AI products with dofollow backlinks, is free to submit, editorially reviewed, explicitly crawlable by GPTBot and PerplexityBot, and includes SoftwareApplication schema on every listing. It is a Layer 4 fix you can ship in 20 minutes.

If you are mentioned on Perplexity but not ChatGPT (or vice versa): This is the platform split problem, and it is more common than founders realize. The two platforms share only ~11% of cited domains. Run them as separate campaigns with platform-specific tactics — the citation share of voice strategy post lays out the ChatGPT-specific moves (Bing verification, schema-marked directories, review velocity) and the Perplexity-specific moves (Reddit participation, quarterly content refreshes, BLUF-structured comparison posts).

If a competitor displaced you this month: This is a citation gap problem with a specific cause. Pull the new cited URLs from this month's runs and compare them to last month's. The competitor added a source — a new comparison post, a new directory listing, a new active Reddit thread, or a new "best of" roundup placement. Audit what they added and decide whether to match the placement on the same source pages, displace it with a stronger version, or ignore it as noise. The fastest counter is matching the move on the same pages, not building entirely new infrastructure.

If your monitoring reveals you are still pre-foundation — robots.txt issues, no schema, no directory listings — go back and run the step-by-step GEO playbook before investing in monitoring tools. Tracking invisibility you have not started fixing is a waste of a subscription.

How Often Should You Monitor? (Cadence by Stage)

Monitoring cadence should match your stage and budget, not the marketing copy of whichever tool you just signed up for.

• Early stage (pre-product-market fit): Monthly manual run with 5–10 prompts. Free only. The goal is establishing a baseline and learning what the AI says about your category — most early-stage founders are not yet positioned to invest in displacement work, so high-cadence monitoring is premature. A good signal you are ready to move to the next tier: you can name three specific buyer-language queries where AI engines should mention you and a competitor consistently shows up in the slot you want, and your manual spreadsheet has at least three months of consecutive data showing the same competitor cited in the same position. Concrete example: a freelance-invoicing SaaS founder who has tracked "best invoicing tools for designers" for 90 days and watched FreshBooks anchor the top slot on ChatGPT every single run is ready to graduate from "baseline" to "displacement work."
• Growth stage (active GEO work underway, real revenue from AI traffic): Monthly manual + one paid tool at the $29–$50/month tier (Otterly.ai is the best fit here). The paid tool catches changes between manual runs and frees the manual session for the description-language column, which is where the strategic insight lives. A good signal you are ready to move to the next tier: your AI-referred traffic shows up as a distinct line in GA4 (typically 5%+ of new signups attributable to ChatGPT, Perplexity, or Claude referrer strings) and you are now competing with two or three named rivals on the same prompts every month. Concrete example: you can pull a GA4 report showing 40+ signups in the past 30 days where the referrer string contains chat.openai.com or perplexity.ai, and your Otterly dashboard shows you and two named competitors trading the #2 and #3 slots week to week.
• Scaling stage (competitive category, attribution matters): Paid tool at the $99–$150/month tier (Peec AI or Profound) plus quarterly full audits of 20–30 prompts. Consider AthenaHQ only if you have a team that needs to attribute AI-driven revenue to a budget line — solo founders almost never benefit from $295+/month tools. A good signal you are ready for the AthenaHQ tier: your CFO or board is asking for AI-channel revenue attribution by source, and you have a marketing team member whose performance review depends on AI visibility numbers. Concrete example: a Series A SaaS where the head of growth has been asked to report quarterly on "AI-sourced ARR" with the same rigor as paid-search ARR, and the existing $120/month tool cannot tie a Perplexity citation to a closed-won deal in HubSpot or Salesforce.

The mistake to avoid: skipping the manual run entirely once you have a paid tool. Paid tools will not show you the verbatim description language that signals positioning lock, and that is the single most important leading indicator of citation pool drift.

Frequently Asked Questions

How do I know if ChatGPT is recommending my SaaS?

Open ChatGPT in web search mode and run your top three buyer category queries — for example, "best [your category] tools for [your audience]." If your brand appears in the response, ChatGPT is recommending you for those queries. For systematic tracking, build a fixed 10–15 prompt set covering discovery, alternatives, and comparison queries, run it monthly across ChatGPT (web search and base mode), and log brand mentions, position in the response, and competitors named in a spreadsheet. After two to three monthly runs you will have enough signal to know whether your visibility is improving, stagnant, or declining. Tools like Otterly.ai automate the same checks at $29/month.

What tools track AI mentions for free?

Several free tools track AI mentions, but none replace ongoing manual tracking. The HubSpot AEO Grader gives a one-off snapshot across ChatGPT, Perplexity, and Gemini. Answer Socrates LLM Brand Tracker checks brand mentions across ChatGPT, Perplexity, Gemini, and Claude. The LLMrefs free tier provides a weekly High/Medium/Low visibility score for one primary keyword. Am I On AI and ZipTie offer quick presence lookups. The most reliable free method is still manual prompt testing in the free tiers of ChatGPT, Perplexity, and Claude — 30 minutes a month with a 10–15 prompt spreadsheet produces better strategic insight than any free dashboard, because you can read framing and cited URLs directly.

How do I monitor my brand across ChatGPT, Perplexity, and Claude?

You need separate prompt runs for each platform — they pull from different citation pools with only ~11% domain overlap, and a brand that dominates one can be invisible on another. Manually, run the same fixed prompt set in each platform monthly and log the results in separate columns of one spreadsheet. For automation, paid tools like Otterly.ai ($29/month, lighter coverage), Peec AI ($120/month, full multi-model), and AthenaHQ ($295+/month, with attribution) track all three from one dashboard on daily or weekly cadence. The non-negotiable rule: do not aggregate the platforms into a single visibility score. Track them separately and run platform-specific tactics for each.

What is an LLM visibility tracker?

An LLM visibility tracker is a tool that automatically runs a defined set of prompts across AI platforms — ChatGPT, Perplexity, Claude, Gemini, and others — on a schedule, logs whether your brand appears in each response, and tracks changes over time. It is the category equivalent of a traditional keyword rank tracker, except instead of measuring SERP position, it measures citation frequency, position in generated answers, and competitor share of voice. Examples include Otterly.ai, Profound, Peec AI, AthenaHQ, and LLMrefs. The category is sometimes also called an AI search monitoring tool, ChatGPT rank tracker, or generative engine optimization tracker — same idea, different marketing names.

How often should I check if AI is mentioning my product?

Monthly manual checks (30–45 minutes) are the minimum viable cadence for any SaaS that takes AI visibility seriously. Early-stage founders without an AI traffic line item can run 5–10 priority prompts monthly and a full 15-prompt audit quarterly. Growth-stage founders should add an automated paid tool (Otterly.ai at $29/month is a fair entry point) for daily or weekly cadence between manual runs. Scaling teams in competitive categories typically run paid tools daily and supplement with full manual audits quarterly. Checking more often than monthly without a tool is usually wasted effort — citation pools do not shift fast enough to justify weekly manual runs.

Does it matter that ChatGPT and Perplexity have different citation pools?

Yes — this is the single most important fact about AI monitoring. The two platforms share only roughly 11% of their cited domains (per Averi.ai's 680M-citation analysis), which means a brand that dominates Perplexity can be entirely invisible on ChatGPT and vice versa. They reward different inputs: ChatGPT favors entity authority compounding through Bing's index, structured directory listings, and review volume, while Perplexity favors content freshness, traditional search ranking, and Reddit activity (Reddit alone accounts for ~46.7% of Perplexity's top citations versus ~11.3% for ChatGPT). Track them separately, set separate share-of-voice goals for each, and run platform-specific tactics. Treating "AI search" as one channel is the most common monitoring mistake.

Start Tracking This Week

The goal of monitoring is not a dashboard. It is a closed loop: measure, identify the specific gap, fix the gap, measure again. Most founders skip the measurement layer entirely and spend 12 months on GEO tactics with no idea what is working. Thirty minutes a month with a spreadsheet beats every paid tool you do not actually use.

Start with the free manual workflow this week. Build your 15-prompt set, run it across the four major platforms, and save the spreadsheet. If your monitoring reveals a thin entity footprint — the most common result for early-stage products — the fastest single fix is a verified listing on a curated, schema-marked directory. Submit your product free on TheSaaSDir — editorially reviewed, dofollow-backed, AI-crawler-friendly, and live in days.