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Mapping

Mapping connects incoming event metadata to standardized fields kenbun uses for scoring, segmentation, and reporting. Without mappings, kenbun can only score leads on what they do (behavioral events). With mappings, kenbun can also score leads on who they are — their role, seniority, the company they work for, and where that company sits in your ICP.

Why Mapping Matters​

Events arriving in kenbun typically carry metadata — extra details like a lead's job title, their company size, or the industry they're in. Mapping tells kenbun which metadata fields correspond to which profile or account properties so the scoring engine can evaluate leads on attributes as well as actions.

Example. An event arrives with metadata { "job_title": "VP of Sales", "company_size": "201-500" }. That data is only useful if kenbun knows job_title should populate the profile property contact_job_title and company_size should populate the account property employee_count. Mapping makes that connection.

Without mapping you cannot:

  • Run profile scoring rules (e.g. "+15 points if seniority is VP or above")
  • Run account scoring rules (e.g. "+25 points if industry is SaaS")
  • Segment leads by firmographic or demographic attributes
  • Display profile or account context in the UI and notifications

Two Flavors of Mapping​

kenbun supports two mapping types, each scoped to a different layer of your data model:

Mapping TypeWhat It PopulatesPowers
Profile MappingLead-level profile properties (job title, seniority, role, function)Profile Scoring, lead segments, lead detail UI
Account MappingAccount-level properties (industry, employee count, revenue, region)Account Scoring, account segments, ABM workflows

The two are independent — you can run one, both, or neither — but most teams configure both to get the full picture of fit at the person and company level.

Shared Concepts​

The following ideas apply to both Profile and Account Mapping. Each spoke covers them in detail; this section is the quick reference.

Source Field vs. Target Property​

Every mapping pairs a source field (the key in your event metadata payload) with a target property (the standardized name kenbun stores it under).

  • The source field is whatever your tracking code, integration, or import sends — jobTitle, job_title, JobTitle, title, role, etc.
  • The target property is a stable name kenbun uses internally and in scoring rules — contact_job_title, industry, employee_count, etc.

Source and target can be the same string. They differ when you're standardizing variations from multiple sources onto one canonical name.

Update Behavior​

Each mapping has an update behavior that controls what happens when an event arrives with a value that conflicts with what's already on the lead or account:

  • Always Latest — overwrite with the most recent value. Use this for fields that change over time (job title, company size).
  • Only If Empty — set the property only when it's blank. Use this for fields where the first value is most reliable (original lead source, signup date).

Backfilling​

If you set up mappings after data has already flowed in, you can retroactively apply them to existing leads or accounts. The backfill respects your update behavior — leads that already have a value with Only If Empty are skipped. Backfills are safe to run multiple times.

Mapping Audit History​

Every change to a mapping is recorded with the team member, timestamp, and field-level diff. Click History on either mapping page to review or revert.

The Mapping and Scoring Workflow​

Mapping is one step in a larger scoring workflow:

  1. Send events with metadata — include profile and account data in your event payloads (via API, web beacon, or integrations).
  2. Create mappings — tell kenbun which metadata fields correspond to which properties.
  3. Create scoring rules — under Configure > Scoring, build rules that award points based on mapped property values.
  4. Scores update automatically — as new events arrive, kenbun maps metadata to properties and re-evaluates scoring rules in real time.

Best Practices​

Map Early​

Set up mappings before importing large volumes of data. Properties are populated as events arrive, avoiding the need for large backfill operations.

Use Consistent Metadata Keys​

Coordinate with your development team so event metadata uses consistent field names across all sources (API, web beacon, CRM integrations). Inconsistent naming (job_title from one source, jobTitle from another) requires separate mappings.

Start with High-Impact Fields​

Focus on the fields that will move the needle most:

  1. Job title and seniority — identifies decision-makers
  2. Industry — enables vertical-specific scoring
  3. Company size or revenue — distinguishes enterprise from SMB