Promptwatch vs Scrunch for Tracking AI Visibility Evidence Over Quarterly Reviews

How do they compare for quarterly evidence?

From Promptwatch's pricing and Data Studio pages and Scrunch's pricing page and help centre:

Why does sampling frequency matter over a quarter?

Because a quarterly review compares two estimates, and each has noise. At Scrunch Core's rate, one prompt on one engine gives about 30 answers a quarter. If that prompt mentioned you in half of them, the true rate could plausibly sit anywhere between roughly 32% and 68%. A rise to 60% the next quarter would not be distinguishable from chance. With daily runs, about 90 answers a quarter narrow that range to roughly 40% to 60%.

In practice, few quarterly reviews should rest on single prompts. Group prompts by topic or buyer stage and report the group's rate: 20 prompts × 4 engines × 30 answers gives 2,400 answers a quarter even on Scrunch Core, which is plenty. Daily sampling matters more when leadership asks about specific high-value questions, such as "best payroll software for construction firms," one by one.

Why is a quarter too long to compare two snapshots?

Because AI citations turn over quickly. Scrunch's own research with Stacker, covering 3.5 million citation events between September 2025 and March 2026, found that a cited page's share of citations halved in about 4.5 weeks on average: around 3.4 weeks on ChatGPT and 5.8 on Perplexity. Over a 13-week quarter, much of what was cited at the start will have been replaced by the end. A review that compares a screenshot from the first week with one from the last misses everything in between, and can mistake normal turnover for a trend.

Use weekly series instead. Scrunch's Explorer exports a date_week breakdown directly; Promptwatch's 90-day Data Studio pull covers most of a quarter in one chart; the last day or two needs a second pull. Longer-term decay is covered in how long earned media remains useful in AI-generated answers.

How do you build a quarter's evidence pack in Promptwatch?

1. Freeze the prompt set on the first day of the quarter, and note any additions separately.
2. Pull the quarter through the Data Studio connector or the API. Each pull is capped at 90 days and most calendar quarters run 91 or 92, so pull the quarter in two date ranges or export the final days separately.
3. Export responses and citations to CSV at quarter end, on Professional or above, so the raw answers are kept outside the tool.
4. Add crawler history from Agent Analytics, so drops in citations can be checked against AI crawler visits.
5. Keep a sample of full responses for the prompts that moved most, as quotable evidence.

Promptwatch says it collects answers from the AI products' own interfaces rather than APIs, which makes the saved responses closer to what users see. More on its plans is in the Promptwatch review.

How do you build one in Scrunch?

1. Export prompt metadata from Configure, including text, stage, persona, tags, branded status, platforms and creation date, to record the set you measured.
2. Build the Explorer view with prompt, platform, persona and week as breakdowns, and export mentions rate, position, sentiment and citation rate. Each export supports up to eight queries and runs in the background.
3. Export citation domains and URLs for the quarter, to show which sources gained or lost ground.
4. Print the home page to PDF with the quarter's date range, for the slide that opens the review.
5. Join metadata to results on prompt ID if you need cuts that Explorer does not offer.

Scrunch's help centre maps every metric to its API field, such as brand_presence_percentage for mentions rate, which helps when the same numbers feed a BI tool on Enterprise. More on Scrunch's other strengths is in Conductor vs Scrunch.

What method changes should a quarterly review flag?

Tools change mid-quarter too, and those changes can look like results:

• Engines dropping out. Scrunch notes that Grok no longer contributes citations, so any citation series that included Grok has a break in it.
• New models becoming the default in ChatGPT or Gemini.
• Prompt additions, which change totals even if nothing else moved.
• Plan changes, such as more engines or prompts after an upgrade.

List them on one slide, with dates, before showing any trend. Ways to show them on charts are in how an AI visibility dashboard should show uncertainty and model releases.

What does a quarter cost?

• Promptwatch: Essential at $95 a month is $285 a quarter for about 18,000 responses; Professional, which adds the 15-type CSV exports and Agent Analytics, is $735 a quarter for about 54,000.
• Scrunch: Core at $250 a month is $750 a quarter for 15,000 responses, with site audits and page optimisation included; API and Looker Studio need Enterprise.

For evidence volume per dollar, Promptwatch is ahead. Scrunch's price also buys site tools that may replace other software.

Where does each fall short?

• Promptwatch: the fuller exports and crawler data start at Professional; Data Studio pulls are capped at 90 days each, so year-long charts come in chunks.
• Scrunch: fewer answers per prompt on Core; retention period not stated on the pages we read; API and BI connections need Enterprise.

We have not run a quarter on either platform ourselves; this comparison is based on their pricing pages, help centre articles and published research.

What might this look like in practice?

Consider an illustrative B2B travel management company, Aircourt, reviewing its second quarter. On Promptwatch Professional, its Data Studio report showed mention rate for its 40 corporate travel prompts rising from 22% to 31%, with the gain concentrated after a comparison guide was cited from week six. The CSV of responses gave the review three quotable answers. A sister brand on Scrunch Core showed a flat quarter overall, but the weekly export revealed a dip in weeks eight to ten that matched a model change in ChatGPT, not anything on its own site.

What do people ask about Promptwatch and Scrunch for quarterly reporting?

How long does Promptwatch keep data?

Promptwatch says history is kept from the day a project starts, with no expiry on visibility, citation, response or crawler data.

Can Scrunch export weekly data?

Yes. Explorer exports can break results down by week, as well as by prompt, platform, persona and country.

Which gives more answers per prompt?

Promptwatch, which runs each prompt daily on each chosen model. Scrunch Core runs each about ten times a month per engine.

Does either connect to Looker Studio?

Promptwatch has a Data Studio connector. Scrunch lists Looker Studio on its Enterprise plan.