Home Care Acquisition Signal Agent
The campaign lead enriches leads through Clay at per-data-point cost, with no way to know in advance which signal is worth checking. The team either over-spends on enrichment or misses owners at the exact moment of intent. The team has no economical way to spot when an owner becomes ready to sell across a 24K TAM. Best deals close when owners are nearing retirement or facing a life change, but those signals are scattered across Google Maps, agency websites, LinkedIn, ad platforms, and state portals. No one can manually search 24K agencies for these signals.
Every morning, a prioritized Google Sheet drops with Hot leads (call now), Warm leads (Instantly campaign), and Long-term touches (six-month cadence). Each lead includes the signal explanation already written. The campaign lead shifts from data acquisition to creative outreach. The advisory team reaches owners at the moment of intent, not weeks later. The full TAM cycles every three months, so no opportunity is missed due to budget constraints.
Stop enriching 24,000 agencies one data point at a time.
M&A advisors for home care agencies face a brutal choice: spend heavily on per-data-point enrichment through Clay and miss owners at the moment of intent, or skip enrichment and lose deal flow entirely.
You pay for every data point checked on every agency, with no way to know in advance which signal will matter.
Owner retirement proximity, GM hiring, review velocity, ad changes, and website updates live across Google Maps, LinkedIn, state portals, and agency websites. No single source shows them all.
Deals close when owners are nearing retirement or facing a life change. Manual monitoring across 24K agencies means you miss the window.
Replace Clay with a rolling TAM monitor that surfaces the right sellers at the right moment.
Process all 24K agencies every three months on a rolling schedule, not a subset based on budget constraints.
Each lead surfaces with the reason already written: 'Owner appears 70+ based on LinkedIn graduation year and agency hired GM in last 90 days.'
Hot leads get lumpy mail and calls. Warm leads feed Instantly campaigns. Long-term leads get six-month touches. No triage needed.
No lead surfaces more than once every two months unless a new high-strength signal appears, protecting your sender reputation and prospect relationships.
the agent processes your full 24K agency TAM on a rolling 3-month cycle, checking every agency for owner retirement proximity, GM hiring, review velocity spikes, ad activity changes, website updates, LinkedIn signals, and nearby closed deals. Every morning, a prioritized Google Sheet drops with Hot leads (call now), Warm leads (Instantly campaign), and Long-term touches (six-month cadence). The campaign lead shifts from data acquisition to creative outreach. You reach owners at the moment of intent, not weeks later.
How the agent monitors your TAM and prioritizes leads.
The agent runs on a rolling cycle, processing roughly 2,000 agencies per week so the full TAM refreshes every three months. Each agency is checked against eight signal types. Leads are classified into three tiers based on signal strength and combination. Daily Google Sheet drops capture whatever crossed thresholds that day.
Start with your existing agency list (from Clay or your CRM). Filter to your ICP: Medicaid-primary agencies in your priority states, plus Medicare agencies in select states. Exclude private-pay-only operators.
For each agency: pull owner age from LinkedIn (graduation year proxy), check if they posted a GM job, monitor Google Maps review count and velocity, scan Google Ads Transparency Center for ad volume changes, check their website for new pages or service offerings, look for LinkedIn activity or M&A engagement signals, and flag if a nearby agency just closed.
Hot: owner 70+ AND hiring a GM, or multiple strong signals. Warm: single signal like owner 65+ or review velocity spike. Long-term: no current signals but worth touching every six months. Rules are tunable as you learn which signals predict actual deals.
Suppress re-surfacing within two months unless a new high-strength signal appears. Every morning, a fresh Google Sheet tab drops with that day's new and re-prioritized leads, formatted exactly like your gym-leads example.
Same data available as JSON so the campaign lead can pull directly into Instantly or route to other tools without manual export.
Existing TAM list +
~24K home care, home health, and hospice agencies (from Clay export or your CRM)
State priority list and ICP criteria +
Which states are in scope (ranked), Medicaid vs Medicare definitions, agency size thresholds, exclusions
Google Maps business listings +
Review count, velocity, phone, address via Serper search
Agency websites +
New pages, service offerings, owner announcements, GM hire posts
LinkedIn profiles +
Owner name, age estimate (graduation year proxy), activity, M&A engagement, job postings
Google Ads Transparency Center +
Ad volume changes per agency
State licensing portals +
Medicaid/Medicare classification where available
HubSpot closed-deal history +
Recently closed deals to drive 'nearby closed deal' internal signal
Filter TAM to ICP +
Apply state priority list and Medicaid/Medicare classification rules to create the active monitoring set
Check owner age signal +
Scrape LinkedIn for owner graduation year; estimate age; flag if 65+ or 70+
Check GM hiring signal +
Monitor agency website and LinkedIn for job postings or announcements of new general manager or operations manager
Check review velocity signal +
Pull Google Maps review count and compare to last cycle; flag if velocity spike (20%+ growth in 90 days)
Check ad activity signal +
Scrape Google Ads Transparency Center; flag if ad volume changed significantly (e.g., 4 ads to 50 ads)
Check website changes signal +
Compare current website to last cycle snapshot; flag new pages, service offerings, or owner announcements
Check LinkedIn activity signal +
Monitor owner LinkedIn profile for M&A engagement, retirement-adjacent posts, or increased activity
Check internal closed-deal signal +
Pull recent closed deals from HubSpot; flag agencies within geographic proximity (same metro or state)
Classify into tiers +
Apply configurable rules: Hot (multiple signals or one strong signal), Warm (single signal or growth indicator), Long-term (no current signals but touched every six months)
Deduplicate and suppress +
Track surface history per agency; suppress re-surfacing within two months unless new high-strength signal appears
Generate reason line +
Write one-line signal summary for each lead (e.g., 'Owner 70+, hired GM in last 90 days')
Format for daily sheet +
Populate Google Sheet columns: Created, Company, Domain, Reason, Address, Segment, Current Stack, Phone, Social Links, Email, Owner/People, Key Signals (multi-line breakdown), Country, Priority Tier, Notes, Salesperson
Daily Google Sheet drop +
New and re-prioritized leads in gym-leads format, with daily date tabs at the bottom for history. Columns: Created, Company, Domain, Reason, Address, Segment, Current Stack, Phone, Social Links, Email, Owner/People, Key Signals, Country, Priority Tier, Notes, Salesperson.
Hot tier leads +
Agencies with multiple strong signals or one very strong signal (e.g., owner 70+ AND hired GM). Ready for calls and lumpy mail.
Warm tier leads +
Agencies with single signal or growth indicator. Ready for Instantly campaigns.
Long-term tier leads +
Agencies with no current signals but worth touching every six months. Ready for educational content drips.
Signal explanation per lead +
Multi-line Key Signals breakdown showing which signals triggered the classification and why (e.g., 'Owner appears 70+ based on LinkedIn graduation year. Agency posted GM job 45 days ago. Review count grew 18% in last 90 days.').
API endpoint (JSON) +
Same data as the Sheet, available as JSON with Bearer-token auth for the campaign lead to pull into Instantly or other downstream tools.
Dedup state +
Internal tracking of which leads have surfaced and when, so no lead appears more than once every two months unless a new signal appears.
Is this for you?
- + M&A advisory firms in home care - the sell-side advisory model: run a structured sell-side process, create buyer competition, close in 60-120 days. You need to spot owners at the moment of intent across a large TAM.
- + Teams running outbound at TAM scale - You have 24K+ agencies to monitor but limited budget for per-data-point enrichment. Rolling TAM cycles replace expensive per-agency checks.
- + Operators with creative outreach talent - Your comparative advantage is campaign engineering and relationship building (like the campaign lead in Instantly). You need data so you can focus there, not on acquisition.
- + Firms with tunable ICP and signal rules - You're willing to iterate on which signals predict actual closed deals. The agent's tier rules are configurable so you can refine as you learn.
- - Single-agency operators or small teams - If you manage fewer than 500 agencies, manual research or simpler tools (like Clay for spot checks) may be more cost-effective than a rolling TAM monitor.
- - Firms focused on buy-side advisory only - This agent is built for sell-side sourcing (finding agencies to acquire). Buy-side teams need different signals (seller quality, operational fit, integration risk).
- - Teams without a CRM or data infrastructure - The agent integrates with HubSpot, Google Sheets, and downstream tools like Instantly. If you're not using these systems, integration overhead increases.
- - Operators who need real-time monitoring - The agent cycles the full TAM every three months on a rolling schedule. If you need to catch signals within 24 hours of occurrence, this is not the right tool.
Scoped build plus usage-based runs.
the agent is a custom build that includes the prototype (synthetic data, demo dashboard, format validation), production integration (live TAM, signal monitoring, daily Sheet drops, API endpoint), and ongoing maintenance. Pricing covers the build scope plus monthly usage-based costs for API calls to Serper, ZenRows, HubSpot, Google Sheets, and OpenRouter. The 3-month TAM cycle (roughly 2K agencies per week) has predictable monthly costs once the signal set and ICP filter are locked in.
- Build scope includes prototype with synthetic data, production integration with live TAM and signal sources, daily Google Sheet drops, API endpoint for downstream tools, and configurable tier rules.
- Usage costs depend on TAM size, signal set complexity, and cycle frequency. A 24K TAM cycled every three months (2K/week) has predictable monthly costs for web scraping, search API, and LLM classification.
- Tier rules are tunable without engineering changes. As the advisory team learns which signals predict actual closed deals, you can adjust weights and thresholds in the database.
- Optional: HubSpot enrichment push (mirroring leads into your CRM in addition to the Sheet) can be added post-launch if the campaign lead's workflow changes.
- Optional: internal credit/usage dashboard showing cycle state, signals detected, and cost per cycle is included in the prototype; full-featured credit tracking can be expanded if needed.
How does this replace Clay's per-data-point enrichment model?
Instead of paying Clay for each data point checked on each agency, the agent processes your full 24K TAM on a rolling 3-month cycle. Every agency is checked against eight signal types (owner age, GM hiring, review velocity, ad activity, website changes, LinkedIn activity, internal closed deals, and state licensing data) once per quarter. You pay a predictable monthly cost for the cycle, not per-point-per-agency. This eliminates the guessing game of which signals are worth checking in advance.
What signals does the agent monitor to identify sale-ready agencies?
The agent checks eight signals on a rolling cycle: owner age (retirement proximity via LinkedIn graduation year), whether the agency posted a GM or operations manager job, Google Maps review count and velocity (size and growth proxy), Google Ads Transparency Center ad volume changes, website updates (new pages or service offerings), LinkedIn activity (M&A engagement or retirement-adjacent posts), state licensing classification (Medicaid vs Medicare), and whether a nearby agency recently closed with the advisory team. Each signal is weighted; multiple signals or one strong signal (e.g., owner 70+ AND hiring a GM) triggers a Hot classification.
How often does the agent cycle through the full TAM, and when do I see new leads?
The agent processes roughly 2,000 agencies per week on a rolling schedule, so your full 24K TAM refreshes every three months. Every morning, a new Google Sheet tab drops with that day's leads that crossed a threshold since the last check. Hot leads (call now), Warm leads (Instantly campaign), and Long-term touches (six-month cadence) appear with the signal explanation already written. No lead surfaces more than once every two months unless a new high-strength signal appears, protecting your sender reputation.
What does the daily Google Sheet look like, and can I use it directly in Instantly?
The daily Sheet follows the gym-leads format: Created date, Company, Domain, Reason (one-line signal summary), Address, Segment, Current Stack, Phone, Social Links, Email, Owner/People, Key Signals (multi-line breakdown explaining why the lead made the list), Country, Priority Tier, Notes, and Salesperson. Daily date tabs at the bottom preserve history. The same data is also available via API as JSON, so the campaign lead can pull it directly into Instantly or other tools without manual export.
How does the agent know which agencies are in my ICP, and can I change the filter?
You provide a state priority list and ICP criteria document (Medicaid vs Medicare definitions, agency size thresholds, exclusions). The agent filters your 24K TAM to match: Medicaid-primary agencies in your priority states, plus Medicare agencies in select states, excluding private-pay-only operators. The filter is configurable, so you can expand or tighten it without engineering changes as your strategy evolves.
What happens if an agency owner doesn't have a LinkedIn profile or their website hasn't changed recently?
The agent is designed to work even when data is incomplete. LinkedIn coverage is roughly 50% of owners, and many profiles are inactive. If an owner has no LinkedIn profile, the agent skips the age-estimate signal for that agency but continues checking the other seven signals (GM hiring, review velocity, ad activity, website changes, state licensing, internal closed deals, and nearby-deal proximity). The Reason line is honest about what was found: 'Owner age unavailable; agency hired GM in last 90 days' beats false precision.
Can I adjust the Hot, Warm, and Long-term tier rules as I learn which signals actually predict deals?
Yes. The tier rules are configurable without engineering changes. Hot starts as 'owner 70+ AND hiring a GM, or multiple strong signals.' Warm is 'single signal like owner 65+ or review velocity spike.' Long-term is 'no current signals but touched every six months.' As the advisory team closes deals and learns which signal combinations actually predict sales, you can adjust the weights and thresholds in the database. The agent will re-classify leads based on the new rules on the next cycle.
What if a nearby agency just closed? How does that signal work?
The agent pulls your recently closed deals from HubSpot and flags agencies within geographic proximity (same metro or state) as 'nearby closed deal' signals. This drives the internal signal logic: if you just sold Bob's in Cleveland, the agent surfaces other agencies in Ohio or the Cleveland metro as potential warm introductions. This signal can promote leads regardless of the normal two-month dedup window because it represents a new moment of intent for the advisory team's outreach.
Useful comparison for teams deciding how to structure signal weighting and tier classification across different data sources when aggregating multi-source lead data.
Useful reference for teams implementing per-cycle cost discipline and error budgets across high-volume scraping workflows with deduplication.
Ready to replace Clay and reach owners at the moment of intent.
The prototype is ready to review. You'll see a working Google Sheet populated with synthetic home care agencies, daily drops in the gym-leads format, Hot/Warm/Long-term tiers with signal explanations, and a demo dashboard showing how the TAM cycle works. No live integrations needed yet. After you approve the format and tier logic, we'll integrate your real TAM, state priority list, ICP criteria, and HubSpot closed deals to go live.