User-Based Targeting

I learned a hard lesson watching a six-figure SaaS deal almost die in the second quarter. The company had crushed the sales process—closed a $150K annual contract with a fortune 500 company. Perfect use case. Perfect fit. Then the contract stalled during implementation.

The problem: They sold to the VP of Marketing. But they were building for the campaign manager. The VP said yes because it solved a problem she understood. The campaign manager said no because they never explained the product in her language, to her use case, at her seniority level. One person bought. The other people used it. And they weren't speaking to the users.

That gap between buying influence and usage influence is where user-based targeting lives.

Definition

User-Based Targeting is a go-to-market and marketing strategy that identifies, segments, and messages based on individual users within accounts rather than treating accounts as single decision-making units. It recognizes that buying a SaaS product and using it are controlled by different people—often with conflicting incentives, different pain points, and different success metrics.

User-based targeting differs from Account-Based Marketing (ABM) in a crucial way: ABM targets an entire account with a coordinated campaign. User-based targeting recognizes that within that account, different personas require different value propositions, different support, and different success criteria.

The Account vs. User Problem

Most enterprise sales teams optimize for closing one deal with one person. They identify a champion—someone with a budget and a problem. They sell to that person. Sale closes. Implementation begins. Then reality hits:

• The champion (often a director or VP) cares about ROI and compliance. But they don't touch the tool daily.
• The operators (managers and individual contributors) touch the tool daily. But nobody showed them the value prop or explained how it helps their work.
• The admin (someone you didn't talk to at all) now has to maintain it, troubleshoot it, and answer user questions.
• The data or engineering person (who you never met) discovers the integration you promised doesn't work the way they expected.

You sold to one person's problem. You implemented into four people's workflows. No wonder adoption is painful.

How User-Based Targeting Works

Effective user-based targeting operates at three layers:

1. User-Level Segmentation (Within the Account)

Map the decision-making unit (DMU) inside target accounts. Identify not just who has budget, but who touches the tool, who influences adoption, and who measures success.

In a typical mid-market SaaS sale:

• The champion/buyer (Director+ level): Cares about ROI, board reporting, vendor risk
• The operator (Manager level): Cares about saving time, integrating into existing tools, usability
• The admin (Specialist level): Cares about deployments, security, maintenance burden
• The technical user (Engineer/Analyst): Cares about API design, data structure, integration capability

Each person needs different education.

2. Messaging Stratification

One value prop doesn't fit all layers. Value Proposition Design at the user level means communicating benefits differently based on who receives them.

For a marketing intelligence platform:

• To the VP of Marketing: "Reduce content go-to-market cycle by 6 weeks and improve campaign ROAS by 23%"
• To the campaign manager: "Get competitive research data without leaving your campaign planning tool—same place, better insights"
• To the data team: "API-native architecture that integrates with Snowflake and Segment—no data warehouse transfer needed"
• To the legal/compliance person: "SOC 2 Type II certified, GDPR compliant, encryption at rest and in transit"

Same product. Four different benefit statements.

3. Channel and Content Alignment

User-based targeting requires meeting users where they are and in formats they consume.

• The VP reads executive summaries and ROI case studies. Reach them through LinkedIn and high-level sales conversations.
• The campaign manager reads blog posts and watches tool tutorials. Reach them through organic search and YouTube.
• The data engineer reads technical documentation. Reach them through GitHub, API docs, and engineering communities.
• The admin reads security assessments. Reach them through SOC 2 reports and security whitepapers.

You're no longer running one campaign. You're running four parallel campaigns to the same account. Each feeds the others.

Real Example: Slack's Enterprise Land Strategy

Slack's user-based targeting is textbook. When they sell into an enterprise:

1. They hook the IT buyer with security certifications, SSO, and admin controls.
2. They excite the VP of Communication with analytics dashboards and compliance features.
3. They delight the end user with a beautiful, intuitive interface that requires zero training.
4. They keep the DevOps team happy by documenting API design and offering pre-built integrations.

Each person feels like Slack was built for them specifically. That's user-based targeting. Slack didn't build a different product for each persona. They built one product and marketed it to multiple personas with different value props.

User-Based Targeting vs. Account-Based Marketing

These terms are often confused. They're related but distinct:

The best companies do both: ABM to land the account at scale, UBT to ensure adoption and expansion across user types.

Implementing User-Based Targeting

Step 1: Map Your Internal User Personas

Don't rely on what your sales team thinks. Audit your customer base. For your largest 20 accounts, who actually uses the product? What's their title, department, and daily job? What problem are they solving with your tool?

This is different from Buyer Personas (who buys) and User Personas (who uses). Map both separately.

Step 2: Create Persona-Specific Journeys

For each user persona within your DMU, design a distinct journey:

• What do they need to learn? (Value proposition)
• When do they need to learn it? (During sales, onboarding, or success phase)
• Where do they consume content? (LinkedIn, docs, product UI, email)
• Who should deliver the message? (Sales, CS, support, product)

Example for a user-based targeting campaign to a mid-market account:

Step 3: Multi-Channel Orchestration

You're no longer sending one email to the account contact. You're sending:

• Email sequences to the VP (executive value)
• In-app product tours to the manager
• Implementation checklists to the admin
• Technical documentation to the engineer

Orchestrate across these channels so they reinforce each other without overwhelming any single user.

Step 4: Measure Adoption by Persona

Track which user personas reach which milestones:

• Did the campaign manager complete the first campaign setup?
• Did the data engineer connect the API integration?
• Did the admin set up user permissions and SSO?
• Did the VP review the performance dashboard?

If one persona isn't progressing, that's a flag. Intervention should be persona-specific, not account-wide.

User-Based Targeting and Expansion Revenue

User-based targeting is one of the most powerful levers for Expansion Revenue because it identifies who inside the account can become a new champion for a different product or feature.

The campaign manager who fell in love with your core product? Perfect person to champion your automation module. The data engineer who built the API integration? Perfect person to champion your custom integrations offering.

User-based targeting early in the lifecycle prepares the ground for expansion conversations later. You've already mapped influence and built trust with multiple personas. Now you're extending value to more of them.

User-Based Targeting in PLG Companies

Product-led growth (PLG) companies don't have traditional sales teams, so user-based targeting looks different but is equally critical.

Rather than a sales team mapping the DMU, Product Usage Analytics reveal it. You see which user types—based on behavior, features used, and company size—reach different activation milestones. Then your in-app education, email nurture, and free trial experience are tailored based on detected user persona.

Figma does this: a solo designer has a different onboarding experience than a team lead, which is different from an admin trying to set up workspace permissions. They detect role based on usage patterns and adapt accordingly.

FAQs

Q: How do I identify user personas if I don't have sales conversations?

A: Use your product data. Behavioral Analytics reveal real user types—who touches what features, in what order, and how often. Cross-reference with customer data (title, department from signup forms) to build empirical personas. This beats guessing.

Q: Doesn't user-based targeting require way more marketing content?

A: It does require more content, but it's more efficient content. Instead of one generic landing page, you build four landing pages. But together, they convert better than the generic one because each is hyper-relevant to its audience.

Q: How do I prioritize which personas to target first?

A: Prioritize by impact: (1) Who determines adoption success? (2) Who influences expansion decisions? (3) Who causes churn if unsatisfied? Focus on the personas with the highest leverage first.

Q: Can I do user-based targeting without dedicated salespeople assigned to accounts?

A: Yes—it's actually more critical if you don't have dedicated reps. You need to automate the persona-specific education through email, product, and content marketing. Your product becomes your primary sales tool.

Q: How do user personas differ from buyer personas?

A: Buyer personas (decision-makers) focus on who has budget authority and can say yes. User personas focus on who touches the tool daily and determines success. They're often different people. Know both.

Q: Does user-based targeting work for low-touch or self-serve motion?

A: Absolutely. Self-serve motion actually benefits more because you can't rely on a sales rep explaining value to different personas. The product experience and email sequences must do it automatically.

Q: How do I measure success of user-based targeting?

A: Primary metrics: adoption rate per persona (% of each user type actually using the product), activation speed by persona (how quickly they reach first value), and expansion rate by persona (which personas upgrade or add licenses). If all personas aren't tracking similarly, you've found your problem.

Q: What if my product only has one user type?

A: Most products have more than you think. Even "individual user" products have power users vs. casual users, early adopters vs. late majority. Segment by usage depth, not just by title.

Sources & References

See also: Account-Based Marketing, Buyer Personas, User Personas, Value Proposition Design, Behavioral Analytics, Expansion Revenue, Product-Led Growth, Expansion-Led Growth, Adoption Metrics, Customer Success Strategy

Written by Conan Pesci | April 6, 2026