HubSpot Account Tiering & Scoring

The workflow

Play 23

HubSpot Account Tiering & Scoring

1Learn from the deals you already closed

Closed won and closed lost, last 12 to 24 months

Closed wonWhat good looks like

ACVSales cycleExpansion

Start with the highest revenue customers. Look for patterns in industry, size and geography.

Closed lostWhat to rule out

Poor-fit industrySize mismatch

The disqualification reasons that keep coming back.

2Define segments and scoring logic

SegmentsOne per account

Company sizeIndustryBusiness model

Scoring inputWhat it checks

Firmographics→Size, industry, location

Technographics→Tech stack

Signals→Recent activity at the account

3Build the Clay model and tier

Core fields

CompanyDomainLinkedIn URL

Enrichment fields

EmployeesRevenueIndustryTech stack

Logic fields

SegmentTierLast enriched

Clay formulas assign the tier

Tier 1Strong fit

Tier 2Good fit

Tier 3Low fit

4Sync tiers into HubSpot

New HubSpot properties

Account tierSegmentKey firmographics

Company and contact data mapped field by field, so the sync never creates duplicates.

Data

Clay

Emails

Findymail

Verify

BounceBan

Write

HubSpot

5Keep tiers live with workflows

Tier workflowsProperty trigger

Company workflows with re-enrollment on, so the tier changes when the data does.

FallbackMissing tier

Accounts without a tier are flagged, not left to slip through.

FreshnessQuarterly

Re-enrich any account last enriched over 90 days ago, and re-check its contacts for job changes.

Job

LinkedIn

Monthly data review, quarterly strategy update

Every account tiered in HubSpot

The stackHubSpotClayFindymailBounceBanLinkedIn

Oriel · GTM plays library

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The diagram as text

1. 1

   Learn from the deals you already closed

   Closed won and closed lost, last 12 to 24 months: Tool: HubSpot.

   Closed won (what good looks like): ACV, Sales cycle and Expansion. Start with the highest revenue customers. Look for patterns in industry, size and geography..

   Closed lost (what to rule out): Poor-fit industry and Size mismatch. The disqualification reasons that keep coming back..

2. 2

   Define segments and scoring logic

   Segments (one per account): Company size, Industry and Business model.

   Scoring input → What it checks

   • Firmographics → Size, industry, location
   • Technographics → Tech stack
   • Signals → Recent activity at the account
3. 3

   Build the Clay model and tier

   Core fields: Company, Domain and LinkedIn URL.

   Enrichment fields: Employees, Revenue, Industry and Tech stack. Tool: Clay.

   Logic fields: Segment, Tier and Last enriched.

   Clay formulas assign the tier: Tool: Clay.

   Tier 1: Strong fit

   Tier 2: Good fit

   Tier 3: Low fit

4. 4

   Sync tiers into HubSpot

   New HubSpot properties: Account tier, Segment and Key firmographics. Company and contact data mapped field by field, so the sync never creates duplicates. Data: Clay. Emails: Findymail. Verify: BounceBan. Write: HubSpot. Tool: HubSpot.

5. 5

   Keep tiers live with workflows

   Tier workflows (property trigger): Company workflows with re-enrollment on, so the tier changes when the data does. Tool: HubSpot.

   Fallback (missing tier): Accounts without a tier are flagged, not left to slip through. Tool: HubSpot.

   Freshness (quarterly): Re-enrich any account last enriched over 90 days ago, and re-check its contacts for job changes. Job: LinkedIn.

   Monthly data review, quarterly strategy update

   Outcome: Every account tiered in HubSpot. Tools: HubSpot.

Feedback loop: Conversion rate, deal size and cycle length by tier feed back into the model, starting again from the closed won and closed lost review.

The stack: HubSpot, Clay, Findymail, BounceBan and LinkedIn.

Open the diagram full size (1180 px wide)

The play in seven steps

1. 01

   Step 1: Analyse your closed deals

   Your own wins and losses are better evidence of fit than any ICP written in a workshop.

   • Export closed won and closed lost deals from the last 12 to 24 months.
   • For wins:
     • Start with the highest revenue customers
     • Compare ACV, sales cycle and expansion revenue
     • Look for patterns in industry, size and geography
   • For losses:
     • Find the disqualification reasons that repeat, such as poor-fit industries and size mismatch
2. 02

   Step 2: Define segments and scoring

   Without segments, a perfect mid-market account and a perfect enterprise account get the same score and the same play.

   • Segment by company size, industry and business model. Each account belongs to one segment.
   • Score on firmographics, technographics and recent signals.
   • Use three tiers: Tier 1 strong fit, Tier 2 good fit, Tier 3 low fit.
3. 03

   Step 3: Build the data model in Clay

   A clean model now saves a messy CRM migration later.

   • Core fields: company name, domain and LinkedIn URL.
   • Enrichment fields: employee count, revenue, industry, location and tech stack.
   • Logic fields: segment, tier and the date the account was last enriched.
4. 04

   Step 4: Enrich and assign tiers

   Tiers built on half-empty records put good accounts in the wrong bucket.

   • Run enrichment in Clay to fill missing firmographic and technographic data.
   • Apply the scoring logic with Clay formulas to set the final tier.
   • Spot-check 20 accounts per tier by hand before syncing. If a rep would disagree with the tier, fix the formula.
5. 05

   Step 5: Sync to HubSpot

   A tier that lives only in a spreadsheet changes nothing about how reps spend their week.

   • Create properties for account tier, segment and key firmographics.
   • Map company and contact fields one by one so the sync never creates duplicates.
   • Find contact emails with Findymail and verify them with BounceBan before they are written.
6. 06

   Step 6: Automate with HubSpot workflows

   A static tier is wrong within months. Workflows keep it moving with the data.

   • Build company workflows on property triggers, with re-enrollment on.
   • Flag any account with a missing tier.
   • Re-enrich accounts every quarter and re-check their contacts for job changes on LinkedIn. Enrichment data goes stale.
7. 07

   Step 7: Monitor and improve

   The model is a guess until conversion data proves it right.

   • Track conversion rate, deal size and sales cycle by tier.
   • Watch tier distribution. If more than a third of accounts are Tier 1, the bar is too low.
   • Review data quality monthly and the scoring strategy quarterly.

Tools used

The five tools this play names. Each links to the other plays that use it.

HubSpotClayFindymailBounceBanLinkedIn

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Signals on your target accountsDated or dropped

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Detect

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TypeDateSummarySource URLWeight

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Each signal adds its weight, then decays on its own curve. A new signal lifts the score again.

Config

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HotNow

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Why it is hot, written only from copy-safe signals, plus a task for the owner.

Brief

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Task

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Alert

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1Audit, read-only

Snapshot and fill rates0 records written

TitleLinkedInCountryEmail validityPhone validitySegment

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Export

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Dirty setFix

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Contact not linked to its account→Link to the account

Job changer→New contact, old one marked gone

Bounced email or dead number→Replace and verify

Missing fields→Fill blanks only

Lead with no account→Match on domain

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Gate1

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A name match only counts when the domain matches too.

× Different people

Gate2

Not a shared key

A switchboard number or a common firm name is never the key.

× Shared line

Gate3

Not a role inbox

A person's name stamped on info@ is a field to fix, not a merge.

× Fix the field

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The change set

Saved as a list view or report the owner can open.

Backup export

Every record in the change set, before anything moves.

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Owner approves the exact listYes unlocks the write

Write unlocked

Every change is logged with its old value, so any field can be restored.

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Enrichment waterfall

Only the misses move on. Fill blanks, never overwrite a value someone set on purpose.

Profile

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Email

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Verify

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Phone

Twiliolookup, dead numbers cleared

Job changers

Current-employer scan, customers first. The same company under another domain is not a move.

Scan

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Create

New contact, history kept

6Keep it on

Same rules, every new record

New inboundRep-added recordsJob-change signalsWeekly sweep

Report

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A CRM that stays clean, with every change undoable

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