Persona mapping framework

Persona Mapping - Framework

How to identify, segment, and target personas within ABM accounts. Mapping personas to their jobs-to-be-done (JTBDs), pain points, and messaging.

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The Persona Mapping Principle

ABM targets accounts, but people buy - not companies. Persona mapping answers:

1. Who at the target account should see your ads?
2. What do they care about? (JTBDs, pain points)
3. How should messaging differ by persona?
4. When should BDRs reach out to which persona?

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Identifying Personas

Step 1: Analyze Your Closed-Won Deals

Look at your CRM data for closed-won deals:

Question	What You're Looking For	Source
Who was the primary contact on won deals?	Most common titles/roles	CRM deal contacts
Who initiated the buying process?	Champion persona	CRM first touch data
Who signed the contract?	Economic buyer persona	CRM deal owner notes
Who else was involved in evaluation?	Buying committee members	CRM activity log, call notes
What was their typical seniority?	IC vs Manager vs VP vs C-suite	CRM contact properties

Step 2: Map the Buying Committee

Most B2B deals involve 6-10 stakeholders. Map the roles:

Role	Definition	Example Titles	Engagement Priority
Champion	Internal advocate who drives the deal	Product Manager, Head of Ops, Director of Growth	Primary - warm them first
Economic Buyer	Controls budget, signs the contract	VP/C-suite, Finance	Engage after champion is warm
Technical Evaluator	Assesses product capabilities	Engineering Lead, Solutions Architect, IT	Engage during demo/trial stage
End User	Will use the product daily	Analyst, Designer, Specialist, IC	Engage with product-focused content
Blocker/Gatekeeper	Can slow or kill the deal	Legal, Procurement, IT Security	Address concerns proactively

Step 3: Define Persona Attributes

For each persona, document:

Attribute	What to Capture	Example
Title patterns	Common job titles	"Product Manager", "Head of Product", "VP Product"
Seniority	IC / Manager / Director / VP / C-suite	Manager - Director
Function	Department/team	Product, Engineering, Marketing
JTBD	Job to be done - what they're trying to accomplish	"Improve user onboarding to reduce churn"
Pain points	What's frustrating them today	"Can't see where users drop off", "Manual onboarding flows"
Success metrics	How their performance is measured	Activation rate, time-to-value, NPS
Content preferences	What content resonates	Case studies, data/benchmarks, peer recommendations
Buying role	Champion / Economic Buyer / Evaluator / User / Blocker	Champion

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Persona Enrichment with Clay

Custom Properties to Enrich

When building contact lists in Clay, enrich beyond standard fields:

Property	How to Enrich	Why
Persona (custom)	Map from title using Clay AI/rules	Enables persona-specific campaigns
Seniority (custom)	Map from title (IC/Manager/Director/VP/C-Suite)	Different messaging by seniority
Function	Extract from LinkedIn profile	Department-specific JTBDs
LinkedIn URL	Apollo / Clay	For LinkedIn outreach + audience matching
Verified email	Email waterfall in Clay	For outreach sequences

Persona Assignment Rules

Create rules in Clay to auto-assign personas:

IF title contains "Product Manager" OR "PM" OR "Head of Product" OR "VP Product" OR "CPO":
  → Persona = "Product"

IF title contains "UX" OR "UI" OR "Designer" OR "Design Lead":
  → Persona = "UX/Design"

IF title contains "Marketing" OR "Growth" OR "PMM" OR "Demand Gen":
  → Persona = "Marketing"

IF title contains "CTO" OR "VP Engineering" OR "Engineering Manager":
  → Persona = "Engineering"

IF title contains "CEO" OR "COO" OR "Founder" OR "General Manager":
  → Persona = "Executive"

IF title contains "Customer Success" OR "CX" OR "Support":
  → Persona = "Customer Success"

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Persona-Based Messaging

Messaging Matrix

Persona	Primary JTBD	Pain Point	Messaging Angle	Ad Content Example
Product	Improve user activation/retention	Can't see user behavior, manual processes	"See exactly where users drop off"	Product analytics screenshots, feature walkthrough
UX/Design	Create better user experiences	No data on user flows, guesswork	"Design based on real user behavior"	Session replay demo, heatmap visuals
Marketing	Drive pipeline, prove ROI	Can't attribute conversions, poor lead quality	"Know which campaigns actually drive revenue"	ROI dashboards, attribution data
Engineering	Ship faster, reduce tech debt	Too many tools, complex integrations	"One platform, simple integration"	API docs, integration showcase
Executive	Hit revenue/growth targets	Slow growth, high churn, team misalignment	"Companies like yours grew X% with us"	Case study with numbers, ROI calculator
Customer Success	Reduce churn, improve NPS	Can't identify at-risk users proactively	"Spot churn risk before it's too late"	Health score dashboards, alert demos

Messaging by ABM Stage

Stage	Product Persona	Executive Persona	UX Persona
Awareness	Industry trend / thought leadership about user analytics	"CEOs at top SaaS companies are investing in..."	Design community content, UX best practices
Interested	Feature comparison vs competitors	ROI data, business impact numbers	Session replay deep-dive, workflow demos
Considering	Product demo, free trial, technical walkthrough	Case study from peer company, executive briefing	Design-focused case study, UX workflow example

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LinkedIn Targeting by Persona

Two Approaches

Approach 1: Contact List Upload (More Precise, More Expensive)

1. Find specific contacts at target accounts in Clay/Apollo
2. Enrich with email
3. Upload to HubSpot as marketing contacts
4. Sync to LinkedIn via HubSpot Ad Audiences
5. Create separate campaigns per persona list

Pros: Very precise targeting Cons: Expensive (Clay credits + HubSpot marketing contacts cost), complex to manage

Approach 2: Company List + LinkedIn Native Filters (Recommended)

1. Upload company list to LinkedIn (via HubSpot company list sync)
2. Use LinkedIn Campaign Manager's native filters to target personas:
   • Job Function: Product Management, Design, Marketing, etc.
   • Seniority: Director, VP, C-Suite
   • Job Title keywords: specific titles

Pros: Cheaper, simpler, leverages LinkedIn's data Cons: Less precise (LinkedIn's job function mapping isn't perfect)

LinkedIn Persona Filters

Persona	LinkedIn Job Function	LinkedIn Seniority	Title Keywords
Product	Product Management	Manager, Director, VP	Product Manager, Head of Product, CPO
UX/Design	Design, Arts and Design	Manager, Senior, Director	UX Designer, Design Lead, Head of Design
Marketing	Marketing	Manager, Director, VP	Growth, PMM, Demand Gen, Head of Marketing
Engineering	Engineering, IT	Manager, Director, VP, CTO	Engineering Manager, CTO, VP Engineering
Executive	General Management	VP, CXO	CEO, COO, Founder, GM
Customer Success	Support	Manager, Director	CS Manager, Head of CS, VP Customer Success

Minimum Audience Rules

• Minimum matched audience: 300 LinkedIn members per campaign
• Smaller audiences = higher CPMs (more expensive)
• At later ABM stages (Interested, Considering): persona lists may be too small to run separately
• Solution: Combine personas at later stages, differentiate via ad content instead of targeting

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Persona Prioritization

Which Personas to Target First

Priority	Persona Type	Why	Budget Allocation
1st	Champions	They drive the deal internally	40-50% of budget
2nd	Economic Buyers	They approve the purchase	20-30% of budget
3rd	End Users	They validate product fit	15-20% of budget
4th	Technical Evaluators	They assess during demo/trial	5-10% of budget

When Budget is Limited

With $10K/month (one campaign group effectively):

1. Don't split by persona. Target all personas in one campaign group.
2. Differentiate through content. Create ads that speak to different JTBDs within the same campaign.
3. Use LinkedIn filters to exclude irrelevant roles (e.g., exclude HR, Finance, Legal from initial campaigns).
4. Prioritize by JTBD/intent instead of persona.

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Campaign Naming Convention (for Intent Tracking)

Structure

[Campaign Name] - [Persona] - [Ad Type] - [JTBD/Intent] - [ABM Stage]

Examples:

• Q1-Analytics - PM - Image - User-Activation - Awareness
• Q1-Analytics - UX - Video - Session-Replay - Interested
• Q1-Analytics - All - TLA - Industry-Trends - Awareness

Why Naming Matters

When ZenABM/Fibbler pushes engagement data to HubSpot, the campaign name is how you extract:

• Which persona engaged (for outreach targeting)
• Which intent/JTBD they cared about (for message personalization)
• Which ABM stage content resonated (for campaign optimization)

Notion Database for Asset Management

Track all ad assets in a Notion database with properties:

• Persona
• Ad Type (Image, Video, TLA, Carousel, Text)
• Asset Description / JTBD
• ABM Stage (Awareness, Interested, Considering)
• ABM Campaign Name
• Status (Brief Done, Design In Progress, Ready, Launched)
• Owner
• Designer Assigned
• Performance Notes

Use formula fields to auto-generate campaign names from properties, ensuring clean naming that flows through to intent detection.

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Project Management: Asset Creation Workflow

Process

1. ABM Manager defines campaign brief
   → Persona, intent, stage, messaging angle

2. Content owner writes ad copy brief
   → Headline, intro text, CTA, visual direction

3. Brief → Notion database (assigned to designer)

4. Designer creates visual assets
   → Follow LinkedIn's current image, headline, and intro-text specs for each ad format

5. ABM Manager reviews + approves

6. Assets uploaded to LinkedIn Campaign Manager
   → Correct campaign group, campaign, naming convention

7. Track in Notion: launched date, performance notes

Volume Expectations

Campaign Scale	Ads Needed	Note
First campaign	~100 ads across personas	Typical first ABM campaign
Mature program	500+ ads over time	After 16 months
Per campaign cycle	17-20 ads per intent group	Based on budget math

Critical: Volume of ads must follow the budget math - each ad needs enough daily spend to generate 3-4 clicks, so don't create more ads than your budget can effectively serve.

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Measuring Persona Effectiveness

Metrics by Persona

Metric	What It Tells You
CTR by persona	Which personas engage most with ads
CPC by persona	Cost efficiency per persona
Interested-stage conversion by persona	Which personas move through the funnel
Meeting book rate by persona	Which personas are most receptive to outreach
Pipeline generated by persona	Which personas drive the most revenue

What to Do with the Data

Finding	Action
Product personas have 2x the CTR of Engineering	Shift more budget to Product persona campaigns
Executive personas rarely click but deals with exec engagement close faster	Keep exec campaigns for influence, don't optimize for clicks
One persona never progresses past Aware	Revisit messaging or drop from targeting
BDRs get higher reply rates from Champions than Economic Buyers	Focus BDR outreach on Champions first

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By Ivan Falco - Frontal