Rankscale pricing

A marketing lead types “rankscale pricing” into an AI assistant before a renewal call with a client. The answer points to Rankscale’s pricing page, where the monthly bill and the number of tracked answers depend on how the monitoring is configured.

What does your Rankscale plan actually include?

Rankscale’s public pricing page shows four paid tiers with a monthly price: Pro at $99, Pro+ at $229, Growth at $385 and Enterprise at $780 a month billed monthly, about 15% less billed yearly, each with its own credit allocation. A yearly-only Essentials plan is listed without a visible price, and a custom plan is available on request. The credits pay for queries to AI engines, rather than acting as a simple allowance of prompts. Those prices were checked on 2 Oct 2026; our UK session saw them in euros, and the page’s own structured data lists the same figures in dollars.

Rankscale’s page says each tier can track up to the stated number of answers from AI engines. It also says the number of answers depends on which engines you select for each search term. Treat those figures as ceilings under the page’s stated conditions, then model your own engine mix and run frequency.

Rankscale says each query to an AI engine typically uses 0.25 credits per engine per prompt. A prompt sent to several engines therefore uses more of the monthly allocation than the same prompt sent to one engine. That gives you a workable calculation, provided your worksheet uses the engines you actually intend to monitor.

Every tier lists the same 17+ AI engines to choose from; the credits decide how many you can afford to run.

How many engines can you use with your Rankscale plan?

Rankscale lists ChatGPT, Gemini, Perplexity, Claude, DeepSeek, Mistral, Grok and Copilot, followed by “and more”. Its comparison table shows 17+ AI engines on every tier. So the tier does not limit which engines you can choose; your credits limit how many you can run, and how often.

This matters when you compare Rankscale AI pricing with another monitoring product. A long supported-engine list does not tell you how many engines you can run for each question or how often the allowance will last. CiteGraph states its engine count plainly: Starter and Growth each include 4 engines and ChatGPT Only asks ChatGPT alone, according to the CiteGraph pricing page. That lets you size the workload without guessing.

The distinction is useful for procurement. Rankscale gives you a credit rule and a selectable engine list, while CiteGraph gives you a fixed engine count on every listed plan. You still need to decide which questions and runs matter, but one part of the calculation is visible.

What does your money actually buy in credits?

The published Rankscale options increase both monthly price and credit allocation. Its page says each engine query typically costs 0.25 credits per prompt, so the answer ceiling follows the credit pool when that assumption applies. Your estimate should include the number of questions, selected engines and runs during the month.

Suppose you monitor buyer questions across several engines and repeat the checks. Each additional engine creates another query for the same prompt. Each additional run uses more of the monthly pool. Multiply questions by engines and runs, then compare the result with the available credits.

Breadth and repeatability use the same allowance. More terms increase breadth. More runs give you a better view of whether an answer has changed, but they consume credits again. Rankscale’s public page explains the currency without recommending a particular workload for each tier.

CiteGraph’s plans provide a useful reference point for the comparison. Starter costs $29 a month and includes 10 questions, 3 runs per question on 4 engines, 6 tracked rivals and 30 written pages a month. Growth costs $69 and includes 10 questions on 4 engines, 10 tracked rivals and 60 written pages. ChatGPT Only costs $19 and includes 20 questions on 1 project, asked on ChatGPT only, all from the published plan details. Weekly scans ask each question 3 times on every plan; a scan you start on Growth asks it 5 times.

How can you test Rankscale against your workload?

Start with the questions buyers already ask. Write down the terms where a recommendation or citation could affect a sale, mark the engines that matter to your audience, and decide how often each question needs to run. This keeps the pricing page from choosing an imaginary workload for you.

Use this short procedure:

1. Write down the buyer questions you want to monitor and remove duplicates.
2. Assign the engines that matter to each question, rather than selecting every available engine by default.
3. Estimate how often you will run each question during a month.
4. Multiply questions by engines and runs, then compare the result with the tier’s published credit pool.
5. Record which pages appear in the answers, as well as whether your brand is named.

The last step matters because visibility and citation measure different things. A product can be mentioned without its site being used as a source, and a useful page can be cited without the brand becoming the recommended choice. Credits cannot settle that distinction.

You can use the free AI visibility checker for a quick view of answers and citations. The free AI readiness check needs no account, runs fifteen checks and shows the fix for each. Those checks will not convert Rankscale credits into a universal comparison, but they can help you identify the work your team actually needs to measure.

For the comparison, use your worksheet total against the table. If the workload fits only when you assume one engine per question, rerun it with the engine mix you plan to use. If repeated runs push the estimate beyond the lower tier, decide whether the extra capacity is worth the additional monthly cost.

What should you do this week before choosing a tier?

Build the worksheet from real buyer questions, include the engines you expect to use, and compare the result with the published credit pools. Every Rankscale tier lists the same 17+ engines, so the part of your estimate to confirm is how many credits your chosen engine mix uses. We measure what the public page states; we do not know what it leaves unstated.

1. Build the question, engine and run-frequency worksheet.
2. Run the same small sample across your chosen engines, then record answers and cited pages.
3. Compare the workload with Rankscale’s tiers and CiteGraph’s published plan structure, then choose the lowest option that covers ordinary use.