Best tools for keyword research and competitor analysis together, compared on where the rival list comes from

Keyword research and competitor analysis are sold as one feature and they are two different jobs with two different error profiles. Your own keyword data is measured. A competitor's keyword data is inferred, every time, by every vendor. Treating the second like the first is the expensive mistake in this category.

The criterion on this page: what does the vendor publish about where its competitor numbers come from? Every tool named below is useful. The ones that say plainly how the figure was built are the ones you can argue with.

The two jobs, and why the order matters

Keyword research starts from your own demand: the queries already bringing you impressions, the words customers use on calls, and the phrases you sell against. Competitor analysis starts from somebody else's inventory: the pages they rank for, the terms they bid on, the gaps between their list and yours.

Run your own first. A rival list read before you know your own demand produces a plan built on their business model rather than yours, and most of it will be terms you have no reason to win.

What each vendor publishes about the rival number

Semrush sells both halves on one plan. semrush.com/pricing, read 21 October 2026, publishes an SEO tier at "$139" a month with "5 websites to monitor", "500 keywords to track daily" and "Basic keyword research and competitor analysis", plus "Track performance in AI search" on the same row. Its free plan on the same page is "$0 /mo" with "1 demo project" and "10 reports per day across all vital tools", which is enough to pull one rival's top pages and see the shape of the data before you pay.

Ahrefs builds both from its own crawl. Its navigation, read on ahrefs.com/keyword-generator the same day, describes Site Explorer as "Study your competitors' websites" and Keywords Explorer as "Learn what your customers are searching for", and the company describes itself on that page as "The only AI marketing platform built on Ahrefs' proprietary web index". The important disclosure sits on a different page: ahrefs.com/brand-radar states "Every prompt is modeled from real user searches in Ahrefs keyword database", which tells you the shape of the whole operation. The keyword database is the base layer, and products are built by expanding it.

Moz publishes the size of its indexes rather than the method, which is still useful: "1.25 billion+ keyword index" and "over 40 trillion links" on moz.com/products, read the same day, with Competitive Research listed as a separate tool and an All-in-one SEO tier at "Starts at $99 / month".

SE Ranking ships a named Competitor Analysis Tool and a Keyword Grouper alongside its rank tracker, listed in its own product navigation on seranking.com/pricing.html, read the same day, where the entry tier at "$129.00 /mo" includes "10 projects and 1 manager seat" and "2k keywords and 100 prompts to track daily".

DataForSEO is the one to read if you want to see the raw unit of this market. dataforseo.com/pricing, read 21 October 2026, publishes a "DataForSEO Labs API, Keyword, competitor, market, app and ecommerce intelligence" at "$0.012 / task + $0.00012 / item", a "Keywords Data API, Search volume, trends, keyword metrics, and advertising data, From $0.0012 / task", and a SERP API "From $0.0006 / SERP", on a "Pay as you go, No subscriptions, $50 minimum top-up" model. When a suite shows you a competitor's keyword list, this is roughly the cost of the underlying data.

How to read a competitor keyword export without fooling yourself

Three habits are worth building. Check a sample by hand: take five rows from the export and look at the actual results page for each, because a rival listed at position 4 for a phrase sometimes ranks with a page about something else. Ignore the traffic column as a number and use it as an ordering. And treat any term where the rival's intent differs from yours as noise, however large the figure beside it.

The criterion worth applying to every vendor here is simple, and none of them hides the answer: was the number observed, or was it modelled? Ahrefs says it outright on ahrefs.com/brand-radar, read 21 October 2026: "Every prompt is modeled from real user searches in Ahrefs keyword database", and the method it describes is to take "real queries from its keyword database", expand them "into natural questions via People Also Ask and semantic fanout", then run the resulting "493 million+ prompts" through each AI platform. That is a very large modelled set, and Ahrefs is open about it being modelled. Google calls its own figure an estimate: Google Ads help, read the same day, describes Keyword Planner as a way to "View estimates on the number of searches a keyword gets each month". Neither of those is a flaw. Both are honest about what the number is, and the buyer who treats a modelled figure as a measured one is the one making the mistake.

The ranking, on the stated criterion

On publishing how the competitor figure is built, the order on 21 October 2026 ran: DataForSEO first, because it sells the data by the task and names the endpoint, so there is nothing left to infer. Ahrefs second, because the modelling is stated in its own words on its own product page. Moz third, because the index sizes are published even though the method is not. Semrush and SE Ranking fourth, because both publish plan limits clearly and describe competitor analysis as a feature rather than as a data product.

The competitor comparison none of these exports contains

What we are not, said before anything else, because the buyer who gets this wrong wastes a month. AI Knows Us does not sell a keyword tool, a rank tracker or a SERP API. We will not show you search volume, keyword difficulty, or your position in a list of links, and if that is what you came for then every tool named on this page does it better than we ever will.

This is checkable, and we measured it the expensive way rather than asserting it. In October 2026 we put 109 recommendation shaped questions, the kind a buyer actually types into an assistant, to Google Keyword Planner for United States volume. Seventy six of the 109 came back NOT ANSWERED, which means Google holds no volume data for them at all, and the whole bank of 109 totalled roughly 1,200 searches a month between them. Nobody types "what is the best AI visibility tool for a SaaS company" into a search box. They say it in a sentence to an assistant, and a keyword database built out of search boxes has never seen it.

What we do sell is the reading of a demand no keyword tool has ever seen. When a buyer asks ChatGPT, Gemini, Perplexity, Claude or Google AI Overviews who to buy from, in a sentence that never names you, we record whether your name comes out, who was named instead, and which page the engine cited. Then we run the content and placement work that changes it. A credit is one buyer question put to one app once. A Claude check costs three credits, because the Anthropic API with live web search is the expensive one. Most checks cost one.

Our own ladder is published twice and both copies are rendered on the server, so a crawler reads them without running any JavaScript. aiknowsus.com/llms.txt is plain text, and aiknowsus.com/pricing carries a table headed India (INR), United States (USD), United Kingdom (GBP), Europe (EUR), Australia (AUD) and Canada (CAD), with the sentence "India is charged in rupees; every other region is charged in US dollars and shown in its own currency". Read on 21 October 2026, the United States column starts at $149 for SEO Start, and the plain text file publishes what that $149 allows: 0 buyer questions watched, 0 credits a month and 0 engines. It is a demand harvest tier, and SEO Scale at $699 carries the same three zeros. The cheapest plan that reads all five answer surfaces is Growth at $299, with 100 buyer questions watched and 1,200 scheduled answers a month. Above it, Scale is $599 with 300 questions and 3,500 scheduled answers, Inbound $1,099 with 200 questions, Outbound $1,299 with 30 questions and four engines rather than five, Agency $1,299 with 80 questions and 12,300 credits, and Everything $1,799 with 300 questions and 3,600 scheduled answers. A top up of 1,000 credits is $49. Managed GEO is published in rupees only, at Rs 88,499 to Rs 2,35,999 a month with a three month minimum, so we quote it in rupees rather than converting it ourselves.

Two rules sit behind every number we publish and both are on our methodology page. The buyer question never names the business being measured, because a question carrying the brand name produces an answer carrying the brand name. And every rate is reported with a 95 percent Wilson interval, so a move from 11 percent to 14 percent on 40 readings is reported as noise rather than as progress.

Where a rival is ahead of us, here it is plainly. Ahrefs Brand Radar, read at ahrefs.com/brand-radar on 21 October 2026, names seven surfaces against our five: AI Overviews, AI Mode, Gemini, Copilot, Perplexity, ChatGPT and Claude. It also publishes its own unit economics in plain language, "Claude consumes 8 checks per update" and an overage of "$0.020/check", which is more disclosure than we publish. SE Ranking, read at seranking.com/pricing.html the same day, publishes seats and projects beside the keyword and prompt limits, which we do not: its $129 tier states "10 projects and 1 manager seat, 2k keywords and 100 prompts to track daily". Nightwatch, read at nightwatch.io/pricing the same day, publishes "SOC 2 compliant, encrypted at rest and in transit. SSO on Enterprise" and white label client reports. Our own rendered pricing text carries no single sign on, no SOC 2 report, no white label and no data processing agreement. Moz sells an AI search and visibility product from a lower entry point than our floor, "Starts at $45/month" on moz.com/products, read the same day, where the ladder runs All-in-one SEO at "Starts at $99 / month", AI search and visibility at "Starts at $45/month" and Local SEO at "Starts at $16 / month".

Where we put ourselves first is one narrow thing, and it is the thing this page is about: when we report that a rival was named instead of you, the rival's name came out of a recorded answer to a buyer's question, not out of an index we expanded. On the size of the underlying data we are nowhere near these vendors and we say so: a 1.25 billion keyword index and 493 million modelled prompts are both far larger than anything we hold.

For the competitor half of this on its own, with more vendors, we keep a separate page on the SEO competitor analysis and competitor research tools compared, and which numbers inside them are inferred. No other page on this site links to that one, measured across the 2,097 of 2,141 live pages whose stored text we can read, on 21 October 2026.

What buyers ask about combining keyword research with competitor analysis

Can one tool do both jobs well? Yes for a small site. The all in one suites are built for exactly this, and the limit you hit first is keywords tracked rather than research depth.

How many competitors should I load? Three, chosen because a buyer would genuinely consider them instead of you. A list of ten turns into a reading exercise nobody repeats.

What should I do with a term a rival ranks for and I do not? Ask whether you want that customer. If yes, it goes in the queue. If no, it goes nowhere, and the gap report is not an instruction.