Peec AI is a strong candidate when your team needs published brand or agency plans and a documented Data Studio connector. Profound merits evaluation when prompt-driven analysis, CSV or JSON exports, or documented Agent and MCP options matter. Neither distinction makes one platform universally better. The practical choice depends on the reporting artifact, metric definitions, plan access and review process your team can support.
This comparison focuses on operational fit rather than feature-count claims. It is based on official vendor documentation reviewed October 13, 2026. Pricing, model access and plan entitlements can change, so confirm current details with the vendors before purchase.
The analysis also separates documented product behavior from proposed implementation guidance. A connector, export or workflow example can support a reporting design, but it does not by itself prove raw event access, CRM write-back, approval controls or race-safe data processing.
Profound vs. Peec AI: the decision in brief
Start with the output your team must produce. Select a candidate based on whether it can provide the required fields, prompt population and access for that output, rather than comparing feature labels alone.
- Evaluate Peec first if its published brand or agency packaging fits your tracking need and its documented Data Studio connector provides the dimensions and metrics required for the report. The connector requires access to a Peec project and a project-scoped API key.
- Evaluate Profound first if you need its prompt-driven Answer Engine Insights analysis, documented CSV or JSON exports, or a documented Agent pattern that summarizes visibility data and sends it to Slack.
- Verify either platform before committing. Check the exact answer engine or model, prompt capacity, tracking period, fields and permissions available on the intended plan. General product pages do not establish every plan entitlement.
Peec publishes separate brand pricing and agency pricing pages. Profound’s current pricing page describes Trial and Enterprise packaging. Treat these as current vendor statements at the research date, not permanent guarantees.
Compare the measurement before the feature list
A prompt is a configured question. An execution or response is an observed run of that question. A citation is a source referenced within an answer. An aggregate summarizes a defined population over a stated period. These are different grains. A prompt-level KPI is not an execution record, and a citation is not the same as a brand mention.
Profound describes Answer Engine Insights as prompt-driven analysis of collected responses, including brand presence, citations and sentiment. Its documented Visibility Score is the number of responses containing the brand divided by the number of responses containing at least one brand. Profound separately documents Visibility, Share of Voice, Average Position, Citation Share and Citation Coverage. See its Answer Engine Insights overview and metric interpretation guide.
Peec defines visibility as chats in which a brand was mentioned at least once, and share of voice as the brand’s proportion of total mentions. Its Data Studio documentation lists citation, retrieval, retrieval percentage, visibility, sentiment, position, usage and share-of-voice metrics. The connector guide documents fields and setup, but does not fully specify one universal event-level data grain.
Citation coverage and citation share are not interchangeable. Profound describes coverage as how widely a domain is cited across responses, while share is the proportion of citations attributed to a domain. A visibility score, share-of-voice percentage and citation measure therefore answer different questions.
Compare metrics only after aligning the denominator, date range, prompt population and platform or model channel. If the definitions or grain differ, report the figures separately.
What current vendor documentation supports
Peec AI: published plans and a documented reporting connector
Peec’s brand pricing page lists Starter, Pro and Advanced tiers. The page currently describes Starter as including 50 prompts, three selected models, daily tracking and one project. It also displays controls for additional models. Confirm current model availability, price and eligibility in the live plan information or account configuration.
Peec packages agencies separately around credits, client projects and reporting. Its agency page describes Essential, Growth, Scale and Comprehensive packages, along with credit-based tracking, client projects, shareable dashboards, Data Studio dashboards, custom CSV exports and automated client reporting. Peec defines an agency credit as one prompt tracked on one AI model for one day. A credit is not the same as a unique prompt, client, project or report.
The Data Studio connector requires Peec project access and a project-scoped API key. It documents dimensions such as brand, country code, date, model, model channel, prompt, source domain, source URL, tags, topics and project. It also lists metrics including citation, retrieval, retrieval percentage, visibility, sentiment, position, usage and share of voice. This supports a connector-based reporting path. It does not establish a general-purpose API, raw event-level export, CRM write-back or a fully specified event schema.
Profound: prompt analysis, exports and workflow options
Profound describes Answer Engine Insights as configured prompts sent to answer engines, with resulting responses analyzed for brand presence, citations, sentiment and related attributes. Its documentation supports CSV and JSON exports for prompts and topics. Documented prompt export fields include Prompt, Topic, Tags, Visibility, Average Position, Citation Share, Citation Ranks and Executions.
The selected Answer Engine Insights tab matters. Profound documents answer exports from the Visibility, Sentiment, FactCheck and Prompts tabs, while the Citations tab exports citations. The selected tab and filters determine what the export represents, so an analyst should preserve that context with the source file.
Profound’s current public pricing page lists a free Trial plan with limited AI Marketer credits, 50 prompts run daily for seven days, and visibility across ChatGPT, Gemini and Google AI Overviews. It describes Enterprise as custom-priced and says Enterprise can include up to nine answer engines, dedicated support, SSO/SAML and SOC 2 compliance. These are plan-specific statements, not universal entitlements. The pricing page also advertises instant setup, although enterprise permissions, governance and workflow design may still require planning.
Profound distinguishes native integrations, which provide nodes for Agents, from MCP connectors used by AI Marketer. Its general integration documentation illustrates a visibility-data node followed by a Prompt LLM node and a Slack node. The general guide does not establish every service’s actions, fields, permissions, approval gates, retries, idempotency or CRM write-back. Check service-specific documentation before relying on a particular operation.
Three documented paths from AEO data to a usable report
These paths support different operating models. Assign a reporting owner to check the selected period, filters and metric meaning before results are shared.
| Path | Input and sequence | Validation and destination |
|---|---|---|
| Peec connector | Use project access and a project-scoped API key to connect Peec’s Data Studio connector, then build a report from documented dimensions and metrics. | Check project scope, date filters, timezone, model channel and metric grain. Publish the validated Data Studio report to approved stakeholders. |
| Profound export | Select prompts or topics, date range and relevant Answer Engine Insights view, then export the supported CSV or JSON data. | Retain the original export and selected filters. Trace normalized fields to source columns and use the reviewed analysis in a downstream report or data store. |
| Profound Agent example | Use the documented visibility-data node, Prompt LLM node and Slack integration node to retrieve, summarize and send a report. | Check period and filters before summarization. Review the interpretation and send it to the configured Slack channel only under the team’s own review procedure. |
Each path has a different failure mode. A Peec chart may appear to show a daily improvement when model channels have been combined or a date filter is wrong. A Profound export row may be mistaken for one execution or one citation. An Agent summary may be blank or use an unintended period. The remedy is path-specific: inspect connector dimensions, preserve export context, or withhold the Slack message until the input and filters are checked.
Design downstream AEO data without mixing observations and aggregates
If AEO data will be combined with other reporting, define separate records for observed answers, their citations and period-level metrics. This is a proposed warehouse design, not a schema published by Peec or Profound.
- Answer observation: one row per observed answer execution, if the source provides that grain. Retain vendor, project, prompt identifier or normalized prompt hash, platform, model channel, region or language when available, observation time, source reference and original export row or identifier when available.
- Citation: one child row per citation within an answer observation. Retain its parent observation reference, cited URL, normalized domain and position where available. Do not collapse multiple citations into one Boolean if citation position or share matters.
- Reported aggregate: one row per explicitly defined reporting period, prompt population, platform or model channel and brand where applicable. Store the metric definition, date boundaries and prompt-set version. A portfolio share-of-voice value belongs here, not on a single answer execution.
- CRM event: a separate record for a reviewed business action, such as an approved recommendation or contact update. Do not treat a visibility aggregate as a CRM contact or deal event.
Do not invent a vendor execution ID when none is present. Preserve the source export row, retrieval timestamp and available identifying fields. If concurrent imports can process the same source record, use a database-enforced unique constraint or transactional upsert. A lookup followed by an insert is not race-safe.
A proposed observation key should include enough context to distinguish multiple runs, such as vendor, project, prompt, platform, model channel, region, persona and execution timestamp or source identifier where available. If the vendor does not expose a stable execution identifier, include an answer hash and retrieval timestamp only as part of an explicitly documented deduplication strategy. The correct key depends on the fields the export actually exposes.
For citations, a proposed child-record key can include observation ID, normalized cited URL and citation ordinal. Multiple citations to the same URL must remain distinguishable when their positions or occurrences matter. For aggregates, the key must include the declared period and aggregation scope. Never reuse an execution key for an aggregate row.
A prompt-set change can break a trend line. Keep a prompt-set version and effective date. When prompts are added, removed or materially rewritten, annotate the report and compare only overlapping populations when measuring change. Profound’s prompt management documentation describes prompt changes and their reporting context.
A share-of-voice aggregate describes a defined population over a period. It is not a property of one answer execution and should not be written directly to a CRM contact or deal. Store its period, denominator, aggregation scope and prompt-set version with the aggregate.
For example, the following is an illustrative aggregate record. It is not a vendor field list or reported result:
{
"record_type": "period_aggregate",
"vendor": "illustrative",
"period_start": "2026-09-01",
"period_end": "2026-09-30",
"aggregation_scope": "project_prompt_set_platform_model_channel",
"prompt_set_version": "v3",
"metric_name": "share_of_voice",
"metric_definition": "source-defined; retain exact denominator",
"source_export_id": "retain-if-available"
}Before writing an approved recommendation into a CRM or CMS, define the system of record, permission scope, source period, prompt or aggregate reference, metric definition, processing timestamp and human review status. If provenance is incomplete, route the record to review rather than writing it automatically. CRM systems consulting is relevant when an organization needs to design that separate system-of-record and write-back path.
Evaluate both platforms with the same acceptance test
Use a representative prompt set, regions, competitors and reporting period where both candidate plans allow. The goal is not to make scores look identical. It is to find out whether each product can support the decision your team needs to make.
- The required answer engines or models, prompt count and tracking frequency are available on the intended plan.
- The reporting owner can state each metric’s definition, denominator, date range and prompt population.
- A sample report or export contains the fields and level of detail needed for the intended analysis.
- Project access, API key or service permissions have been reviewed and approved for the actual workflow.
- A named analyst can explain an observed change without conflating visibility, share of voice and citation metrics.
Ask a non-analyst to answer a specific question from the sample output, such as which tracked prompts changed visibility or which cited sources need review. If the reader cannot identify the period, model channel or metric meaning, fix the report and labels before rollout.
For integrations, verify the actual service-specific action, permissions and data fields. A directory listing does not prove a particular read or write operation. If you extend a documented workflow into a governed agent process, see AI agent workflow design for design considerations beyond the vendor’s illustrative pattern.
Which platform should you shortlist?
Shortlist Peec when its published brand or agency packaging fits the tracking requirement and its documented Data Studio connector supplies the fields for your reporting path. Agency buyers should calculate capacity in prompt-model-days and confirm current package limits.
Shortlist Profound when its prompt-driven analysis, CSV or JSON exports, or documented distinction between Agent integrations and MCP connectors matches the work. Confirm access by plan, especially when assessing Enterprise features such as SSO/SAML, SOC 2 compliance or broader engine coverage.
Then make the decision using your own prompts and target report. The better fit is the platform whose metric definitions, available data path, plan limits and accountable reporting owner support the decision your team actually needs to make. This article demonstrates reporting architecture and readiness, not a guaranteed direct API connection or business outcome.