Scrunch AI vs Otterly.AI for Testing Real Buyer Prompts Across AI Engines

How do they compare?

From each vendor's pricing and product pages:

What makes a buyer prompt "real"?

A real buyer prompt is a question someone asks before they have chosen a supplier, in their own words. Good sources:

• Sales and support teams: the questions prospects ask on calls and in chats.
• Site search and support tickets: what visitors look for on your site.
• Search Console: long, question-shaped queries, which often mirror how people ask assistants.
• Reviews: the needs and objections customers mention.
• Community questions in forums and question-and-answer sites in your field.

Keep most prompts unbranded, such as "best accounting software for a five-person firm", with a few branded ones to see how you are described. Avoid prompts invented only from your own marketing language, which tend to flatter visibility because they echo your pages. How to mine Search Console for this is covered in how to use Search Console long-tail queries to find AI prompts.

How does each help you find prompts?

Otterly offers an AI Prompt Research tool that maps hundreds of prompts by intent and funnel stage, and an AI keyword research feature that converts ordinary keywords into prompts, with estimated intent volume. That suits teams starting from an SEO keyword list.

Scrunch generates prompts from your brand context and recommends a simple rule of thumb: pick your topic clusters, then write 12 to 15 questions for each, mixing branded and unbranded. Its AI Search Trends view estimates volume and momentum for topics using panel data, and Scrunch is clear that no vendor has native volume data from AI platforms, so the figures are directional. That suits teams that want to prioritise topics before writing prompts.

How should you test prompts in either tool?

1. Group prompts into topics, each with 12 to 15 variations.
2. Include different phrasings of the same need, since small wording changes can change which brands appear.
3. Add personas where buyers differ, for example a finance director versus an office manager. Scrunch supports this directly; in Otterly, write persona-specific prompts.
4. Run each prompt many times. Answers vary between runs; daily runs in Otterly or roughly ten a month in Scrunch give a rate rather than a single result.
5. Freeze the set for a quarter, so trends reflect the engines, not your edits.
6. Read the answers, not just the scores, for a sample of prompts each month.

How to choose questions for a specific sector is covered in which buyer questions a software development agency should test.

How should you read the results?

Look for three patterns across each topic. First, prompts where you are missing on every engine, which usually point to a content or reputation gap. Second, prompts where you appear on one engine but not others, which point to differences in the sources each engine uses; Google's AI Overviews lean on search results, while ChatGPT and Perplexity cite more third-party pages. Third, prompts where you appear but low in the list or described poorly, where the fix is often in how others describe you. For each pattern, open the cited sources. They show whether the answer depends on your own pages, on review and comparison sites, or on competitors' content, and so which team should act.

What does each cost per answer?

Otterly's Lite plan runs 15 prompts daily on four engines, about 1,800 answers a month for $29, or roughly 1.6 cents each. Standard runs 100 prompts daily, about 12,000 answers for $189, also about 1.6 cents. Scrunch Core's 5,000 responses for $250 work out at 5 cents each, but include personas, trends and site tools. If your goal is simply to test many prompts often, Otterly is cheaper by a wide margin. If you want structured topic research and optimisation in the same tool, Scrunch's price buys more than answers.

Where does each fall short?

• Otterly: Gemini, AI Mode and Claude cost extra; persona testing needs manual prompt writing.
• Scrunch: fewer runs per prompt at entry; one persona and one country on Core; more engines need Enterprise.
• Both: volume estimates are modelled, not measured; treat them as a guide to which topics matter.

Our comparison draws on each vendor's published pages; we have not run the two tools against each other.

Which should you choose?

• Otterly for small and mid-sized teams that want daily data on a broad prompt set at low cost, and that start from keyword research.
• Scrunch for teams that want to test several buyer types, prioritise topics by trend and act on pages in the same platform.

Otterly is also compared with other trackers in ZipTie vs Otterly and Otterly vs Semrush, and Scrunch in Promptwatch vs Scrunch.

What might this look like in practice?

Consider an illustrative HR software company, Brannockly, selling to small businesses. It collected 60 questions from sales calls and support chats, grouped into four topics. In Otterly Standard, daily runs showed Brannockly named in answers about shift scheduling but rarely about payroll. It then trialled Scrunch with two personas, a restaurant owner and an HR manager, and found assistants recommended it to restaurant owners far more often. Brannockly kept Otterly for daily tracking and used the persona insight to write separate guides for HR managers.

What do people ask about Scrunch and Otterly?

Which is cheaper?

Otterly, from $29 a month; Scrunch Core is $250.

Do both track the same AI engines?

At entry, yes: ChatGPT, Perplexity, AI Overviews and Copilot. Each adds more on higher plans or add-ons.

How many prompts should I track?

A useful starting point is 12 to 15 questions for each of your main topics.

Can either show how often people ask a prompt?

Both offer estimates; no vendor has native volume data from AI platforms.