Reading Your Data Quality Score

Your Data Quality Score measures how complete, accurate, and up-to-date your campaign data is. Higher quality data means more effective outreach and better decision-making.

What you'll learn

• How the Data Quality Score is calculated

• What factors affect your score

• How to improve data quality

Understanding the Score

Your Data Quality Score is a number from 0-100 displayed on your dashboard. Here's what each range means:

Score

Rating

Meaning

90-100

Excellent

Data is clean and comprehensive

70-89

Good

Minor gaps but usable for most purposes

50-69

Fair

Significant gaps affecting outreach

0-49

Needs Work

Data issues limiting campaign effectiveness

Score Components

The overall score is calculated from several factors:

Completeness (40%)

How much information you have for each contact:

• Email coverage - Percentage with valid emails

• Phone coverage - Percentage with phone numbers

• Address coverage - Percentage with full addresses

• Name completeness - First and last name present

Accuracy (30%)

How reliable your data is:

• Bounce rate - Percentage of emails that fail

• Invalid phones - Numbers that don't connect

• Duplicate rate - Repeated contacts in database

• Format consistency - Standardized addresses, phone formats

Freshness (20%)

How current your data is:

• Last updated - When records were last modified

• Stale contacts - Records with no recent activity

• Voter file recency - Age of matched voter data

Engagement Data (10%)

How much interaction history you have:

• ID rate - Contacts with support levels recorded

• Contact attempts - Outreach history logged

• Response tracking - Email opens, SMS replies tracked

View Score Breakdown

Click on your Data Quality Score to see how each component contributes and which areas need the most attention.

Improving Your Score

Quick Wins

• Merge duplicates - Use the duplicate finder tool

• Remove bounced emails - Clean invalid addresses

• Fill in missing data - Update records with known information

Ongoing Improvements

• Enable contact enhancement - AI fills in missing data

• Run regular imports - Keep voter file data current

• Train volunteers - Ensure quality data entry at doors

Quality Over Quantity

A smaller database with high-quality data is more valuable than a large database full of errors. Focus on accuracy.

Next Steps

• Managing Contact Enhancement

• How to Perform Bulk Operations

• Importing Clean Data