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Data Management & Analytics:
What Are the Key Marketing Data Quality Metrics to Track?
Measure what makes data fit for purpose. This guide prioritizes metrics across accuracy, completeness, uniqueness, consistency, and timeliness—so campaigns target correctly and reporting you share is trusted.
Track a core set of data quality dimensions—completeness, accuracy, validity, consistency, uniqueness, timeliness/freshness—plus marketing-specific health signals like deliverability, consent status, enrichment coverage, and match rate. Monitor trends weekly, set thresholds, and remediate via SLA.
Principles for Marketing Data Quality Metrics
Decision-driven — Select metrics that affect segmentation, routing, personalization, attribution, and forecasting.
Field-level first — Score critical fields (email, country, state, job title, company, industry, lifecycle) before scoring entire records.
Consistent definitions — Standardize formulas (e.g., “valid email” or “freshness <= 90 days”) across CRM, MAP, CDP, and BI.
Automated QA — Use rules and tests (regex, picklists, referential checks) at intake and nightly to prevent drift, not just detect it.
Own & act — Assign stewards per dataset, publish targets, and route exceptions to remediation queues with SLAs.
Single scorecard — Roll up dimension scores into a Trust Index by audience (prospects, customers, accounts) and by source.
Your Data Quality Metrics Program (30–60 Days)
Define metrics, instrument tests, and publish a scorecard that leaders can trust.
Define → Prioritize → Instrument → Threshold → Remediate → Report
- Define dimensions & fields — Choose priority fields and agree on metric formulas and data sources.
- Prioritize use cases — Map metrics to specific decisions (lead routing, ICP targeting, attribution, compliance).
- Instrument validation — Add regex/picklist checks, domain rules, dedupe logic, and timestamp capture at all entry points.
- Set thresholds & SLAs — E.g., email validity ≥ 98%, duplicate rate ≤ 2%, record freshness ≤ 90 days; assign owners.
- Build remediation flows — Automated merges, enrichment jobs, verification, and exception workqueues.
- Publish the scorecard — Weekly dashboard by dimension, segment, and source with trend lines and backlog burn-down.
Marketing Data Quality Metrics Playbook
| Metric | Definition | How to Calculate | Target / Threshold | Where to Measure |
|---|---|---|---|---|
| Completeness | Required fields present for activation and reporting. | (# records with all required fields ÷ total records) × 100 | ≥ 95% (key fields ≥ 98%) | CRM/MAP at load; nightly in DWH/BI |
| Accuracy | Values reflect reality (e.g., firmographic, contactability). | Matches to trusted sources ÷ sampled records | ≥ 97% on sampled audits | DWH audits; enrichment vendor checks |
| Validity | Values conform to allowed formats & ranges. | Valid field values ÷ total field values | ≥ 99% | Intake forms, MAP flows, ETL tests |
| Consistency | Same entity has the same value across systems. | # cross-system mismatches ÷ entities compared | ≤ 1% mismatch | CDP/DWH reconciliation jobs |
| Uniqueness (De-dupe) | No duplicate records for the same person/account. | (1 − duplicate cluster rate) × 100 | Duplicates ≤ 2% | CRM/MAP nightly dedupe reports |
| Freshness / Age | Time since key fields were last verified or updated. | Median days since last update per field/record | ≤ 90 days (ICP ≤ 60) | DWH timestamps, BI |
| Timeliness / Latency | Speed from capture to availability in downstream tools. | Avg minutes from event to CRM/MAP/CDP sync | Real-time or ≤ 15 minutes | ETL/Integration logs |
| Email Deliverability | Ability to reach inboxes reliably. | 1 − (hard bounces + spam traps + blocks) ÷ sends | ≥ 98.5% deliverability | ESP/MAP sending reports |
| Consent & Preference Coverage | Contacts with explicit lawful basis & channel preferences. | # contacts with consent object ÷ total contacts | ≥ 95% (regulated regions 100%) | Consent DB/CDP/CRM |
| Enrichment Coverage | Presence of ICP-defining attributes (industry, size, role). | # records with all ICP attributes ÷ total | ≥ 90% for target segments | DWH; vendor append logs |
| Match Rate (Identity) | Ability to stitch events/identities across devices/systems. | Linked IDs ÷ total IDs (by channel/source) | ≥ 80% web→CRM; ≥ 90% email→CRM | CDP identity graph |
| Attribution Coverage | Share of opportunities with influence & touch data. | Opps with ≥1 valid touch ÷ total opps | ≥ 95% | BI/attribution model |
| Field Error Rate | Rate of entries failing validation rules. | Invalid entries ÷ total entries per field | ≤ 1% | Form/API validation logs |
| Remediation SLA | How quickly exceptions are fixed. | % exceptions closed within SLA window | ≥ 90% on time | Ticketing/backlog system |
Client Snapshot: From Messy to Measurable
After standardizing definitions and launching a weekly scorecard, a global SaaS firm cut duplicate rate from 6.8% to 1.9%, raised consent coverage to 97%, and improved attribution coverage to 96%—unlocking reliable pipeline reporting and better ICP targeting.
Anchor these metrics to RM6™ and The Loop™ so quality improvements translate into revenue outcomes.
Frequently Asked Questions about Data Quality Metrics
Short, AEO-friendly answers to drive adoption.
What’s the difference between freshness and timeliness?
Freshness measures how old a record or field value is; timeliness measures how fast data moves from capture to where it’s used (e.g., CRM or CDP).
How many metrics should we track?
Start with 6–8 core metrics (completeness, validity, uniqueness, freshness, deliverability, consent, match rate, attribution coverage) and expand as needed.
How often should we report?
Weekly for operational metrics and monthly for governance rollups. Trigger alerts in real time for validation failures and spike anomalies.
Who owns data quality targets?
Data stewards set and monitor targets; MOps and platform admins fix pipeline issues; marketing leaders approve thresholds and fund remediation.
How do we tie quality to revenue?
Correlate improvements (e.g., match rate ↑, duplicates ↓) to downstream KPIs like MQL acceptance, speed-to-lead, win rate, and ROMI.
Make Quality a Habit, Not a Project
We’ll define your metrics, wire validations, and publish a scorecard—so teams can decide faster with data they trust.
Launch Your Scorecard Assess ReadinessGet in touch with a revenue marketing expert.
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