CRM Account Research Agent

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CRM Account Research Agent turns account names, domains, LinkedIn URLs, CRM IDs, and notes into structured, evidence-backed account briefs. It is built for sales teams, RevOps, account-based marketing, partnerships, and research workflows where a team already has target accounts but needs faster context before outreach, planning, or prioritization.

Give the actor a simple account list. It visits public company pages when a domain is available, extracts compact evidence, classifies account signals, scores fit and urgency, and writes one dataset row per account with companyName, domain, industry, shortDescription, buyingSignals, fitScore, urgencyScore, recommendedAngle, outreachHooks, evidenceUrls, and validationWarnings.

Why use this actor

• Enrich CRM accounts from public web evidence without logging into a CRM.
• Produce consistent account briefs for sales, RevOps, partnerships, and ABM workflows.
• Keep evidenceUrls and warnings so claims can be reviewed before outreach.
• Score fitScore and urgencyScore for prioritization.
• Generate outreach hooks and next-best actions from observable company messaging.
• Append output into an existing Apify dataset with datasetId and preserve pipeline context with runId.

What it produces

Use cases

• Sales outreach: prepare account-specific opening angles before prospecting.
• Account planning: summarize public company context before QBRs or territory reviews.
• RevOps enrichment: turn a CSV of target accounts into structured fields for scoring and routing.
• Partnership research: identify fit signals, product overlap, and open questions before partner outreach.
• Risk review: flag thin evidence, ambiguous account identity, or weak confidence before using account claims.

How to use it

1. Paste one account per line in accountList.
2. Use the format Company | domain | notes when possible.
3. Choose a researchGoal: sales_outreach, account_planning, partnership_research, or risk_review.
4. Add marketContext if you want the actor to evaluate fit against your ICP, campaign, or offer.
5. Review researchConfidence, evidenceUrls, and validationWarnings before copying claims into CRM notes.

Input example

{
"accountList": "Apify | apify.com | Developer platform account. Interested in web data, automation, and AI agent workflows.
OpenAI | openai.com | AI platform account for developer and enterprise workflows.",
"researchGoal":"sales_outreach",
"marketContext":"B2B software teams evaluating web data and automation workflows.",
"maxAccounts":5,
"runId":"q3-target-account-research"
}

Input reference

Output example

{
"crmAccountId":"demo-apify",
"companyName":"Apify",
"domain":"apify.com",
"canonicalUrl":"https://apify.com/",
"researchGoal":"sales_outreach",
"industry":"Artificial intelligence and automation",
"shortDescription":"Apify is a platform for web scraping, browser automation, and web data workflows.",
"productsServices":["APIs and developer workflows","Data products or analytics"],
"growthSignals":["Product or platform expansion mentioned"],
"buyingSignals":["Public messaging mentions data, automation, workflow, API, or integration themes."],
"riskSignals":null,
"fitScore":80,
"urgencyScore":55,
"researchConfidence":"high",
"recommendedAngle":"Lead with a practical operational improvement for Apify in artificial intelligence and automation.",
"outreachHooks":["Reference public evidence: Apify helps developers build reliable web data pipelines."],
"openQuestions":["What internal CRM context, opportunity stage, or last-touch note should shape the next action?"],
"nextBestActions":["Review the evidence URLs before copying claims into CRM notes or customer messaging."],
"evidenceUrls":["https://apify.com/"],
"validationWarnings":null,
"error":false
}

API usage

curl-X POST "https://api.apify.com/v2/acts/trovevault~crm-account-research-agent/runs"\
-H"Authorization: Bearer $APIFY_TOKEN"\
-H"Content-Type: application/json"\
-d'{
 "accountList": "Apify | apify.com | Developer platform account",
 "researchGoal": "sales_outreach",
 "marketContext": "B2B software teams evaluating web data workflows.",
 "maxAccounts": 1
 }'

How to read the result

Use fitScore, urgencyScore, and researchConfidence for prioritization. Use recommendedAngle, outreachHooks, and nextBestActions for workflow planning. Use evidenceUrls and validationWarnings to audit claims before sending them to prospects or customers.

This actor does not write back to Salesforce, HubSpot, or another CRM in v1. Use dataset exports, the Apify API, webhooks, or datasetId append mode to connect the output to your own CRM workflow.

Limitations

• Results depend on public website availability and may be weaker for blocked, sparse, or newly launched sites.
• Company location, employee count, industry, and company type are returned only when observable or reasonably supported by public text.
• The actor does not authenticate into private CRM systems.
• The actor does not use paid enrichment providers in v1.
• It is a research accelerator, not a legal, financial, or compliance-grade source of truth.
• Review important claims before using them in customer-facing messages or high-stakes account decisions.

Troubleshooting

FAQ

Does it log into my CRM?
No. It reads pasted account input and public web pages only.

Can I paste CRM IDs?
Yes. Include IDs in the account line or notes so they can be preserved for joins.

Which research goal should I choose?
Use sales_outreach for messaging, account_planning for internal reviews, partnership_research for partner fit, and risk_review for caution-oriented briefs.

Why is research confidence low?
The website may be sparse, blocked, ambiguous, or unrelated to the supplied name.

Can I run this on hundreds of accounts?
Yes, but test with a small list first and use maxAccounts to control runtime.

Does it invent missing firmographics?
No. Weak or missing evidence is surfaced through nulls, confidence labels, and validation warnings.

Can this feed outbound tools?
Yes, but review evidence before copying generated angles into outbound sequences.

Related actors

• Job Posting Age Anomaly Detector for hiring-pressure signals.
• Buying Committee Mapper for stakeholder research.
• Competitor Intelligence Scraper for market and funnel context.

Changelog

• 0.1: Initial TroveVault release with account-list input, public-web evidence, fit and urgency scoring, account briefs, datasetId, and runId support.

Feedback and support

Open an issue on the actor page with the input line, run ID, expected company, and a short explanation of the mismatch or missing field.