Start with Scrunch when the main AEO problem sits at the website edge: page audits, AI bot traffic, enterprise controls, or bot-facing delivery. Start with Peec AI when the priority is visibility and citation analysis, agency project workflows, MCP-assisted reporting, or crawler-log analysis. This is a fit-based buying guide, not a performance ranking. A web team investigating whether bots can access a complex site should evaluate Scrunch first. An agency comparing cited sources across client projects should begin with Peec AI. Neither choice proves that a page will earn more citations or revenue.
Product pages and pricing interfaces change. Scrunch’s current public pricing page differs from older Starter-plan comparisons, and Peec AI’s displayed models and plan information are dynamic. Confirm the exact plan, model access, export path, security evidence, and commercial terms in the vendor’s current interface before buying.
The practical decision is not simply which product has more features. It is which platform gives your team usable evidence at the control point where it can act, and whether the selected plan exposes enough data to support that work.
Scrunch vs. Peec AI: the short answer
Use two questions for an initial evaluation:
- Where is the operating control point? Choose Scrunch as the first candidate when the work is page-level diagnosis, bot access, site-side delivery, or enterprise governance. Choose Peec AI when the work is measuring answers and citations, organizing agency projects, querying data through MCP, or examining crawler logs.
- Can the selected plan supply the evidence and access you need? Confirm model variants, prompt and response limits, markets, seats, audits, log access, project allocation, MCP entitlement, and data export in the current account or pricing interface.
These are fit criteria, not claims that one platform produces better visibility. A team needing both measurement and detailed site auditing should test both on the same prompt set and target pages.
Buy the platform that gives the responsible team evidence it can validate and an action it can own. Do not buy a metric without deciding who will investigate it.
Compare the operating fit, not a stale feature matrix
Scrunch’s current public pricing page lists Core at $250 per month with 125 unique prompts, 5,000 responses per month, five site audits, one brand workspace, five user licenses, and four platforms. The page lists Enterprise as custom, with AXP, API access, SSO, expanded platform coverage, and nine displayed AI platforms. These are public plan details, not a substitute for account-specific terms or a contract.
Peec AI’s pricing interface is dynamic. Its currently displayed models differ from older fixed engine lists, so verify each required model and variant against the specific brand or agency plan. Peec’s agency pricing page describes allocation as one prompt multiplied by one model multiplied by one day, and lists a 900-credit minimum allocation per project. Allocated credits are not automatically the same as a cash-spend balance.
| Control point | Documented fit | Likely owner | Verify before buying |
|---|---|---|---|
| Website diagnostics and delivery | Scrunch lists site audits and Enterprise AXP; its FAQ describes bot-traffic monitoring. | Web operations, CDN, or technical SEO | Audit allowance, AXP scope, supported data source, and plan access |
| Visibility and project analysis | Peec documents visibility and citation analysis, agency allocation, and MCP-assisted querying. | AEO analyst, agency lead, or reporting owner | Models, prompt limits, project allocation, MCP entitlement, and exports |
| Crawler investigation | Both document log-related analysis. Scrunch describes agent traffic and Peec describes agent analytics. | Web operations and analytics | Accepted log source, fields, format, retention, and plan availability |
| Governance | Scrunch’s FAQ describes a completed SOC 2 Type II audit and Admin, Editor, Viewer, and Guest roles. | Security and procurement | Current report and scope, role entitlements, SSO, and contract terms |
Scrunch’s security FAQ is a vendor statement about its audit. Request the current report and scope. SOC 2 is an audit, not a government certification. Its roles FAQ documents Guest in addition to Admin, Editor, and Viewer. Confirm which controls apply to the plan under consideration.
Put the purchase decision in a dated comparison sheet containing the selected plan, prompt and response limits, markets, model variants, seats, audit allowance, project allocation, export access, and security evidence. Ask the vendor to confirm entitlements that are not visible in the live interface.
Choose based on the work your team must operate
Scrunch is a candidate when teams need page-level audits, site-side technical diagnosis, bot-traffic visibility, enterprise access controls, or AXP. Scrunch currently lists AXP as an Enterprise capability. Treat it as a delivery option to test, not a promise of better citations, rankings, or revenue. Its bot-traffic FAQ describes monitoring through CDN and hosting integrations. Web operations still needs to confirm setup requirements and own changes at the edge.
Peec AI is a candidate when the team needs visibility and citation analysis, agency project allocation, MCP-assisted querying, or analysis of uploaded or connected crawler logs. Peec’s MCP page documents querying visibility, competitors, sources, and trends. Confirm that the relevant plan supports the intended account and client workflow. MCP access does not by itself establish a CRM write-back or publishing workflow.
| Operating trigger | Capability to test | Owner | Decision gate |
|---|---|---|---|
| A specific page may be hard for bots to access or interpret | Scrunch site audit and, if relevant, Enterprise AXP | Web operations | Can the team reproduce the issue and safely test a proposed change? |
| An agency needs repeatable client visibility reporting | Peec projects, credit allocation, citation analysis, and MCP access | Agency reporting lead | Does the plan cover the client, models, prompt volume, and report destination? |
| Logs show repeated crawler errors or unexpected requests | Scrunch agent traffic or Peec agent analytics | Web operations and analytics | Can the product parse the actual log source and preserve request-level evidence? |
The operating cost differs too. Site-edge work needs CDN or web-operations ownership. Measurement work needs prompt stewardship, clear reporting definitions, and people responsible for content or outreach actions. A team that lacks either owner should resolve that before adding a platform.
Keep four AEO signals separate
Reports become misleading when unlike records are blended. Define each record by its grain, meaning what one row represents:
- Prompt-run observation: one execution of one prompt against one engine or model variant at one time. It can record whether the brand appeared and other response-level observations.
- Citation occurrence: one URL citation within one prompt run. A single response can contain zero, one, or several citations.
- Bot request: one raw or vendor-normalized request for a URL in a crawler or server log.
- Human AI referral: one analytics session from an AI platform, with any associated landing page or conversion event.
A crawler request, a citation, a prompt-run observation, and a human referral are different records. A request does not prove that a page appeared in an answer, a citation does not establish a visit, and a referral does not establish that a citation caused a conversion. Compare them only in a separately scoped analysis.
Store Share of Voice and other aggregates separately from the underlying observations. For each aggregate, retain the prompt-set version, engine and model scope, date range, timezone, denominator, and calculation version. A changed prompt set or model mix changes the measured population, so mark that change rather than presenting it as a clean trend.
Scrunch describes query, responses, and agent traffic API categories: visibility metrics, response-level answers and citations, and bot traffic. Its public API overview is not a full implementation reference. Confirm actual fields, authentication, pagination, rate limits, historical access, and billing before building scheduled extraction.
Turn a finding into an owned action safely
The following is a proposed, vendor-neutral workflow, not a vendor-provided integration template. The input is a reviewed prompt run or log event. The analytics store is the evidence system of record, while a human-owned editorial or web-operations queue is the action destination. Use a vendor export or API only after confirming it is available to the selected account and testing its actual payload.
A small illustrative recommendation record might look like this. It is a local design contract, not a Scrunch or Peec API schema:
{
"recommendation_id": "rec_illustrative_014",
"tenant_id": "tenant_01",
"brand_id": "brand_01",
"source_product": "confirmed_vendor_export",
"source_run_id": "run_illustrative_102",
"prompt_version": 2,
"engine": "account-confirmed-model",
"observed_at": "2026-10-10T09:00:00Z",
"source_url": "https://example.com/topic",
"recommendation_type": "content_review",
"evidence_hash": "illustrative-hash",
"confidence": null,
"approval_status": "pending_human_review",
"approved_by": null,
"destination_record_id": null,
"applied_at": null
}Keep vendor-originated observations separate from locally derived priority, narrative, and confidence. A vendor presence field and an internally calculated priority score are not interchangeable evidence.
Do not deduplicate by searching for a task and then inserting as the only safeguard. Two workers can pass the search at the same time. Enforce a database unique key such as tenant or brand plus recommendation type, normalized target URL, prompt-set version, and active period, then use a transactional upsert where supported. If two citations support one content gap, preserve both citation records but create one reviewed task for the target page.
The reviewed vendor materials do not establish a standard native CRM write-back connector for either product. MCP, APIs, and exports are not interchangeable with an approved CRM write. If your team is designing ownership and data flows across systems, see CRM systems consulting. For automation, validate the real source and destination interfaces before evaluating Zapier automation services; do not assume an available connector or ready-made workflow.
Check security, integrations, and procurement boundaries
For Scrunch, request the current SOC 2 Type II report and scope, subprocessor terms, plan-specific access controls, and retention or deletion terms required by your security review. For Peec AI, review its current security and privacy materials directly. Do not infer a certification status or an unpublished control from product or pricing pages.
For either vendor’s API, MCP, export, or log ingestion, ask for the actual data contract: authentication, schemas, pagination, rate limits, retries, retention, deletion, and billing treatment. Public product overviews describe capabilities but do not establish a production-ready integration specification.
- Confirm plan-specific model access, prompt and response limits, markets, seats, and audit or project allowances.
- Test a sample export or API response and verify that prompt-run, citation, bot-request, referral, and aggregate records remain distinguishable.
- Obtain current security evidence, report scope, data-retention terms, and deletion process.
- Test missing fields and duplicate handling. Require database-enforced uniqueness for concurrent task creation.
- Name the content owner and web-operations exception owner before the pilot begins.
Run a bounded pilot with fixed prompt versions, a small set of target pages, and agreed engine and geography scope. Judge it by evidence completeness, analyst effort, time to assign an issue, and completed actions. Do not use an assumed citation or revenue lift as the acceptance criterion.
When HubSpot AEO is the more relevant alternative
HubSpot AEO is worth a separate look when CRM context and marketing work inside HubSpot are the operating priority. HubSpot documents monitoring across ChatGPT, Perplexity, and Gemini, with visibility, share of voice, sentiment, citations, and recommendations on its AEO product page. At research time, HubSpot advertised standalone access at $50 per month for 25 prompts and a 28-day trial. Confirm current pricing, trial terms, and Marketing Hub entitlements before purchase.
The AI Search Grader is a free, one-time diagnostic, not an ongoing monitoring history. HubSpot’s setup guide describes access through Marketing Hub Pro or Enterprise as well as standalone use. Check the current edition matrix and engine scope. This option is not automatically a substitute for deep page auditing, bot-facing delivery, or agency-specific project needs.
A practical final selection test
Before signing, define the prompt set and markets, verify models and limits, test citation-level evidence access, confirm audit or log access, and assign both a prompt-governance owner and a content or operations owner. For a side-by-side evaluation, keep prompt versions, engines, geography, date range, and target pages constant.
Set a dated baseline and agree on a measurement window. Success should mean that the team can obtain usable evidence, produce reports with less avoidable effort, assign issues to the right owner, and complete approved interventions. Recheck the selected plan and model coverage at purchase because vendor interfaces and terms can change.
In short: evaluate Scrunch first for website-edge control and Peec AI first for visibility, citation, project, or MCP-led analysis. Choose only after the required data, plan access, ownership, and validation process pass a real pilot.