July 28, 2026
CRM Data Quality Scorecard for HubSpot: Grade Your Database A–F
Free calculator and CSV template for grading HubSpot contacts and companies on five dimensions.
A CRM data quality scorecard turns "our HubSpot data is messy" into five numbers you can measure again next week. This free version grades contacts and companies separately. Enter the percentage of records that pass each check, and the calculator returns a score out of 100 and an A–F grade.
The model is deliberately small. You can explain it in a meeting, audit the inputs, and spot which part of the database is dragging down the grade.
Free calculator · no signup · runs in your browser
Grade your HubSpot database
Enter the pass rate for each dimension. Use a sample or your full database, but keep the same scope when you score it again.
Nothing you enter is uploaded or saved. The calculator runs in this page.
What is a CRM data quality scorecard?
A scorecard is a repeatable audit of the records that support a real CRM process. It is not a count of every blank property in HubSpot. Most portals have optional fields, old experiments, and properties that matter only to one team.
Start by defining the records and fields in scope. For example:
- Active contacts created or updated in the last 12 months.
- Companies attached to open deals.
- The fields used for routing, segmentation, reporting, and outreach.
Score contacts and companies separately. A portal can have clean contacts and weak company data, or the reverse. Combining them too early hides the useful part of the result.
For the wider framework behind these dimensions, read the complete HubSpot data quality guide.
The scorecard formula
This model uses five dimensions and a weighted average:
Score = (completeness × 0.25) + (validity × 0.25) + (consistency × 0.20) + (uniqueness × 0.15) + (freshness × 0.15)
Completeness and validity carry the most weight because missing or unusable values can stop a workflow outright. Consistency affects day-to-day use, while uniqueness and freshness protect the database from duplicate effort and stale decisions.
| Score | Grade | Working interpretation |
|---|---|---|
| 90–100 | A | Reliable for the process you tested |
| 80–89.9 | B | Usable, with a contained cleanup list |
| 70–79.9 | C | Material gaps need an owner |
| 60–69.9 | D | Risky for automation or reporting |
| Below 60 | F | Do not rely on it without review |
There is no universal CRM grading standard. This is a practical model, not a certification. Its value comes from using the same definitions, scope, and sample method each time.
How to collect the five pass rates
Use the same basic calculation for every dimension:
Pass rate = records that pass ÷ records assessed × 100
Audit the full in-scope set if it is manageable. For a large portal, take a random sample that is big enough to include different owners, sources, and lifecycle stages. Save the segment or export so the next score can use the same rules.
HubSpot's data quality tools can surface fill rates, duplicate issues, formatting issues, and property insights. Availability varies by subscription and permissions. A spreadsheet or Marketplace scan can provide the same inputs when the native view does not cover your plan or scoring rules.
Completeness: are required values present?
Choose the properties required for the process you are testing. Then count populated required-field cells and divide by all required-field cells in scope.
For 100 active contacts with four required fields, there are 400 required-field cells. If 352 are populated, completeness is 88%.
Do not include every property in the portal. A blank optional field should not lower the grade.
Validity: can the values be used?
A populated field can still fail. Define a pass rule for each field:
- Email has usable syntax and a domain worth reviewing for delivery.
- Phone follows the format your workflows expect.
- Company domain is a domain, not a full URL or free-text note.
- Numeric and date values sit inside a sensible range.
HubSpot supports property validation rules for many field types, although enforcement differs by input source. Existing values are not always repaired retroactively, so measure what is already in the database. The HubSpot email validation guide gives a more detailed set of email checks.
Consistency: do equivalent values look alike?
Consistency measures predictable formatting and controlled choices. Examples include lowercase emails, one phone standard, agreed country values, and names without stray punctuation.
Count records that follow the chosen standard. Write the standard down before scoring. "Looks tidy" is not an audit rule.
Uniqueness: how much duplicate excess exists?
Use this formula:
Uniqueness = 100 − (excess duplicate records ÷ records assessed × 100)
In each confirmed duplicate group, one record is the keeper. The rest are excess. If a set of 1,000 contacts contains 30 confirmed excess records, uniqueness is 97%.
Potential duplicate suggestions are not confirmed duplicates. Review them before they affect the score. HubSpot's duplicate manager compares contact and company properties, but access and bulk actions depend on the subscription.
Freshness: when was the record last checked?
Pick a window that matches the process. Ninety days may suit active sales contacts. Twelve months may be enough for a stable company record.
Freshness is the percentage of records verified inside that window. "Last modified" is only a proxy: a workflow can update a hidden property without confirming the person's job, email, or company. Use a dedicated verified date when freshness matters.
Contact and company scorecards need different rules
The dimensions stay the same, but the checks change.
| Dimension | Contact pass example | Company pass example |
|---|---|---|
| Completeness | Email, owner, and lifecycle fields are present | Domain, owner, and routing fields are present |
| Validity | Email and phone pass the chosen rules | Domain resolves and numeric fields are plausible |
| Consistency | Names, email, and phone follow the standard | Domain, country, and company name follow the standard |
| Uniqueness | No confirmed excess contact record | No confirmed excess company record |
| Freshness | Contact was verified inside the contact window | Company was reviewed inside the company window |
Do not compare contact and company scores as if they were a contest. Use each grade to find the next cleanup job.
What A, C, and F look like
| Example | Completeness | Validity | Consistency | Uniqueness | Freshness | Score |
|---|---|---|---|---|---|---|
| A database | 96% | 94% | 92% | 99% | 91% | 94.4 / A |
| C database | 78% | 74% | 68% | 92% | 52% | 73.2 / C |
| F database | 44% | 42% | 35% | 76% | 28% | 44.1 / F |
The C example is common: uniqueness is fine, but old records and uneven formatting pull the grade down. That tells you where to work. Deduplication would not be the first job.
If the first grade is lower than expected, use the step-by-step HubSpot cleanup plan to turn the weak dimensions into owned work.
Set boundaries for automatic fixes
A low dimension score does not make every related change safe to automate.
| Good automation candidate | Keep for review |
|---|---|
| Trim spaces and normalize clear casing | Fill a missing factual value |
| Format a phone when the country is known | Guess a country or phone code |
| Remove a protocol from a clear company domain | Replace an uncertain domain |
| Flag a malformed email | Change consent or suppression status |
| Create a duplicate review queue | Merge records based on a weak match |
Use a sample before any bulk change. Track the rule, date, and number of records affected. The score should improve because records became more useful, not because the test was made easier.
Review the score every week
Keep the weekly review short:
- Score the same contact and company segments.
- Compare each dimension with the previous result.
- Investigate the largest fall, not just the overall grade.
- Check whether an import, form, or integration created the pattern.
- Assign the next cleanup action and record its owner.
A grade can stay flat while the problem changes. Keep all five dimension scores alongside the total.
Manual scorecard versus Simple Data Hygiene
This calculator grades a segment or database from the pass rates you enter. Simple Data Hygiene grades individual HubSpot contacts and companies from record-level checks, then rolls those results into a portal report. The two methods answer different questions.
Use the manual scorecard to agree on business rules, scope, and improvement targets. Use a Simple Data Hygiene scan to find specific record issues, preview safe formatting fixes, and track the grade distribution over time.
Run a Simple Data Hygiene scan and compare it with your manual score.