The data problem
- Data Foundation & Signal Readiness
Your CRM has data.
Just not data you can trust.
The Database Hygiene module makes your HubSpot trustworthy — cleaning the foundation, standardizing the signals, and ensuring the architecture you build on top of it actually works.
We'll audit your HubSpot and show you exactly what needs to be cleaned before you build.
Signal-ready revenue infrastructure
Broken lifecycle stages, noisy activity data, and orphaned records don't just look bad — they produce false signals that make every downstream system unreliable.
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The foundation the SOS runs on
The Monarch SOS is only as good as the data underneath it. This module ensures the architecture is built on a clean, structured, trustworthy foundation.
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Standalone or bundled
Available as a standalone engagement for teams that need data foundation work before anything else — or included in Full SOS implementation.
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If your HubSpot data isn't trustworthy,
False signals
"Our lifecycle stages don't reflect where contacts actually are in the buying process."
Broken lifecycle stages mean funnel metrics are unreliable, automation misfires, and attribution tells you a story that isn't true.
Dirty data
"We have thousands of duplicate contacts, blank fields, and records nobody owns."
Orphaned records, inconsistent formatting, and missing ownership make every sales motion less accurate and every report less trustworthy.
Assumptions instead of signals
"Our activity data doesn't tell us who's actually engaged — just who had a call logged."
When sales activity isn't standardized, engagement metrics become noise. You can't tell what's working, what's real, or who's actually ready to buy.
The transformation
From assumed signals
to reliable signals.
This isn't a one-time cleanup. It's a permanent infrastructure upgrade — governance rules, automation, and enrichment that keep the data clean going forward.
Today — assumed signals
- Lifecycle stages don't reflect real buying intent
- Sales activity ≠ actual engagement
- Inconsistent company & contact data across records
- Orphaned records and unclear ownership
- Reporting and attribution aren't trusted by anyone
- Teams operate on assumptions instead of signals
- AI tools produce noise because the data underneath is broken
After — reliable signals
- Governed lifecycle stages tied to real sales readiness
- Meaningful activity signals that show actual progress
- Standardized, enriched company & contact records
- Clear ownership on every sales-ready record
- Reporting, automation, and attribution you can trust
- Every downstream system running on clean data
- AI agents producing leverage — not noise
What's included
Six components.
One trustworthy data foundation.
Every component is designed to work together — not as a checklist of one-time fixes, but as a governed, automated system that keeps your HubSpot data reliable over time.
01
Lifecycle Stage Management
Audit and govern your lifecycle stage system — filling gaps, defining progression rules, implementing regression protection, and aligning stages to real sales readiness thresholds.
The most common source of funnel metric errors. Fixed here first.
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02
Sales Activity Signal Standardization
Define what meaningful sales engagement actually looks like — standardizing call outcomes, meeting types, email engagement, and task completion so activity metrics reflect real progress.
Without this, "activity" is just noise. With it, you can tell who's actually moving.
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03
Contact & Company Data Normalization
Standardize firmographic fields — employee count, revenue buckets, industry — across all company records, and backfill existing contacts with enrichment where possible.
ICP scoring and segmentation only works if the underlying fields are consistently populated.
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04
Hygiene, Formatting & Deduplication
Property value formatting, name normalization, and duplicate handling - automation over manual cleanup.
Requires Data Hub Professional for full deduplication automation capabilities.
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05
Ownership Integrity System
Fix orphaned companies, implement ownership enforcement workflows, and configure SLA-based alerts when ownership is missing on sales-ready records.
Every sales-ready record needs a clear owner. This makes that non-negotiable.
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06
Data Enrichment & Record Standardization
Enrich records against a golden record standard, operationalize that standard within HubSpot layouts, and validate record staleness.
Record staleness validation requires a Clay subscription.
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WHY THIS MATTERS FOR THE SOS
The architecture is only as good
as the data underneath it.
Every pillar in the Monarch SOS depends on clean, structured, trustworthy data. The Database Hygiene module is what makes all of it possible.
HOW CLEAN DATA POWERS EACH PILLAR
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PROSPECTING
ICP scoring requires clean firmographics. Signal capture requires standardized activity. Without it, the Prospecting Pillar prioritizes on noise.
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SALES PROCESS
Stage discipline requires accurate lifecycle data. Buyer evidence models require clean field structure. Without it, the pillar enforces nothing.
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EXPANSION
Health models require reliable engagement signals. Account governance requires clear ownership. Without it, the pillar monitors noise.
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Not sure how clean your HubSpot data is?
We'll audit your database and show you exactly what's broken — before you commit to anything.
WHAT'S NOT COVERED
This package has a clear scope.
Here's what it doesn't include.
We believe in being explicit about scope. These items are out of scope — most are covered by the full SOS implementation.
CRM architecture or rebuilds
Full re-implementations, object model redesigns, pipeline overhauls, and tool migrations. That's SOS implementation work.
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Sales process redesign or enablement
We align data to sales reality. Redesigning stages, defining playbooks, or training reps is SOS work - not hygiene work.
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Bespoke reporting & dashboards
We ensure data supports reporting. Building custom executive dashboards or board-level metrics are scoped separately.
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Custom attribution model design
This package enables accurate attribution - designing multi-touch models or custom dashboards is scoped separately.
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Manual data cleanup at scale
This package prioritizes automation. Large-scale manual record updates and ad hoc list cleanup are not included.
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Ongoing monitoring & governance
Unless part of an SOS Subscription, continuous data quality monitoring and monthly audits are not included.
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HOW TO GET IT
Available standalone or
included in Full SOS.
Whether you need data foundation work before anything else — or you're moving forward with the full SOS — this module fits either path.
DATABASE HYGIENE
For teams that need clean data before they can build anything else.
Starts at $15K • Investment discussed on discovery call
ADD TO ANY PILLAR
- All six components included
- Lifecycle stage governance
- Activity signal standardization
- Contact & company normalization
- Deduplication & formatting automation
- Ownership integrity system
- Data enrichment & golden record standard
FULL SOS
The complete revenue operating system. Database Hygiene included from day one.
Investment discussed on call
- Database Hygiene module included
- All three SOS pillars deployed
- Al Operational Agents configured
- Revenue Data Architecture
- Inspection & Governance layer
- 90-day deployment team onboarding
RECOMMENDED ADD-ON
Database Hygiene Module
Most Monarch customers find their HubSpot data is messier than they thought. This module cleans and structures it before the architecture goes in — so the system runs on accurate data from day one.
Standalone or Add-on.
Included in Full SOS.
Every piece of architecture you build on top of dirty data inherits the problem. You can't enforce a buyer evidence model if your lifecycle stages don't reflect reality. You can't score ICP fit if your firmographic fields are blank.
Most HubSpot implementations fail not because the architecture is wrong — but because the data underneath was never cleaned up. The Database Hygiene module fixes the foundation before anything gets built on top of it.
Find out what's actually
broken in your HubSpot data.
We'll audit your database, show you exactly what's broken and why it matters, and walk you through what it takes to fix it — before you commit to anything.
No pitch. No pressure. A clear picture of your data foundation and what it needs.
