Job Changes
Professionals can move between companies or take on different responsibilities.
DATA QUALITY & VERIFICATION
B2B Data Verification Methodology
Learn how Data Fox researches, structures, standardizes, reviews and prepares business contact data for customer projects using a defined multi-stage quality-control process.
✓
Audience Research
✓
Field Standardization
✓
Verification Checks
✓
Final Quality Review
Verification methods and available fields vary by audience, geography and project requirements.
DATA PROCESS WORKFLOW
WHY VERIFICATION MATTERS
Why B2B Data Quality Matters
Business information changes continuously. A professional contact who was accurate at one point may later change employers, job titles, locations or contact details. Verification and quality review help make a database more useful at the time it is prepared.
Email Changes
Business email addresses can become inactive or change when employees move roles.
Company Changes
Companies can relocate, merge, rebrand, restructure or cease operations.
Market Changes
Company size, industry classification and other business attributes may change over time.
METHODOLOGY OVERVIEW
How Data Fox Prepares B2B Contact Data
Our workflow begins with the customer's targeting requirements and progresses through research, standardization, verification, deduplication, suppression and final quality review.
01
Define Audience
Set targeting criteria
→
02
Research
Identify relevant records
→
03
Cross-Check
Review business details
→
04
Standardize
Normalize data fields
→
05
Verify
Apply relevant checks
→
06
Deduplicate
Remove repeated records
→
07
Suppress
Apply applicable exclusions
→
08
Review
Final quality control
STEP 01
Define the Target Audience
Data quality begins with a clear project specification. Before research starts, Data Fox reviews the audience the customer wants to reach and the criteria relevant to the project.
Targeting criteria may include:
Industry
Job Title
Seniority
Job Function
Geography
Employee Size
Revenue Range
Company Type
Technology Criteria
Required Fields
EXAMPLE TARGETING REQUEST
U.S. Healthcare IT Decision-Makers
Industry
Healthcare
Geography
United States
Company Size
200–2,000 Employees
Job Titles
CIO, CTO, VP IT, IT Director
Data Fields
Name, Title, Email, Company, Location
STEP 02
Research & Identify Relevant Records
Once the audience is defined, relevant business and professional information can be researched using sources appropriate to the audience and project.
Depending on the project and availability, source categories may include:
Company Websites
Public Business Sources
Professional Directories
Industry Resources
Business Publications
Professional Information
Permitted Public Records
Third-Party Data Sources
The exact sources used can vary by audience, geography,
project and the type of business information requested.
STEP 03
Cross-Check Business Information
Where appropriate and available, business information can be compared across relevant sources to help assess whether the record aligns with the requested audience.
PERSON
↔
COMPANY
JOB TITLE
↔
EMPLOYER
COMPANY
↔
WEBSITE
LOCATION
↔
COMPANY
INDUSTRY
↔
BUSINESS ACTIVITY
SENIORITY
↔
JOB FUNCTION
STEP 04
Standardize Database Fields
Business information can appear in different formats across different sources. Standardization helps make the final database more consistent and easier to use.
- Names and professional titles
- Company names
- Industry categories
- Country and state formats
- Business phone formatting
- Website URLs
- Email formatting
- Company size and revenue ranges
Original Format
VP, Mktg.
→
Standardized
Vice President, Marketing
STEP 05
Review Business Email Information
Where business email information is included, applicable checks may be used as part of database preparation to help identify malformed, duplicate or potentially unusable addresses.
Email Syntax
Review whether an address follows a valid email structure.
Domain Review
Check whether the associated domain appears valid and usable.
Mail-Domain Checks
Apply relevant technical checks where supported by verification methods.
Duplicate Detection
Identify repeated email addresses within the prepared file.
Important:
Verification can help identify certain invalid or potentially
unusable email addresses, but email status can change after
validation. Data Fox does not represent that every email address
will remain deliverable indefinitely.
STEP 06
Review Contact & Company Information
CONTACT REVIEW
Professional Information
- Full name
- Job title
- Job function
- Seniority level
- Employer
- Professional location
COMPANY REVIEW
Firmographic Information
- Company name
- Website
- Industry
- Employee range
- Revenue range where available
- Company geography
STEP 07
Identify & Remove Duplicate Records
Raw research can contain overlapping or repeated records. Deduplication helps create a cleaner final database and reduces unnecessary repetition.
✓
Email-Level Duplicates
✓
Contact-Level Duplicates
✓
Person + Company Matches
✓
Repeated Source Entries
Final unique contact counts may differ from initial raw
research totals after duplicate and overlapping records
are identified.
STEP 08
Apply Applicable Suppression Checks
Where relevant to the project and Data Fox's internal records, applicable suppression and exclusion information can be considered during database preparation.
- Recorded opt-out requests
- Suppression requests
- Correction requests
- Data-removal requests
- Project-specific exclusions
✓
Suppression Matters
Maintaining applicable suppression information helps Data Fox continue honoring relevant data-removal and opt-out requests.
STEP 09
Final Database Quality Review
Before delivery, the prepared database can be reviewed against the agreed project specifications.
✓ Audience Criteria
✓ Geography
✓ Job Titles
✓ Seniority
✓ Required Fields
✓ Duplicate Status
✓ File Structure
✓ Formatting
✓ Record Count
✓ Sample Alignment
DELIVERY
Prepared for Customer Use
The final database is prepared in the agreed file format and according to the project specification.
TRANSPARENT EXPECTATIONS
Understanding Data Verification
Verification improves database quality, but it should not be interpreted as a guarantee that information can never change or that a campaign will achieve a particular result.
Verification Helps With
- ✓ Standardizing inconsistent data fields
- ✓ Identifying duplicate records
- ✓ Reviewing audience alignment
- ✓ Identifying certain malformed emails
- ✓ Reviewing business information
- ✓ Improving database usability
Verification Does Not Mean
- × Every field exists on every record
- × Information can never change
- × Every email remains deliverable forever
- × Every recipient will respond
- × Every campaign will convert
- × Business outcomes are guaranteed
METHODOLOGY FAQ
B2B Data Verification Questions
How does Data Fox verify B2B data? +
Depending on the project, Data Fox may use processes including audience review, research, source cross-checking, field standardization, email validation, duplicate removal, suppression checks and final quality review.
Does every record contain every data field? +
No. Available fields vary by audience, geography, source availability and project requirements. Data Fox reviews available field coverage before final delivery.
Are business email addresses verified? +
Where email information is included, relevant validation checks may be applied during database preparation. Email status can change after validation, so verification should not be interpreted as permanent deliverability.
How are duplicate records handled? +
Duplicate and overlapping records can be identified using relevant contact, email, company and combination-level matching during database preparation.
Can business information change after delivery? +
Yes. Professionals change jobs, businesses relocate or restructure, and contact information can change after a database has been prepared.
Can I request sample records first? +
Yes. You can provide your target audience and request available counts, field information and representative sample records where available.
How can I request correction or removal? +
Applicable correction, suppression or data-removal requests can be submitted through the Data Fox Opt-Out / Data Removal process.
EVALUATE YOUR TARGET AUDIENCE
Review the Data Before You Move Forward
Tell us your target industry, job titles, geography, company criteria and required fields. Data Fox can review available coverage and sample records for your audience.
✓ Available Audience Count
✓ Sample Records Where Available
✓ Available Data Fields
✓ Targeting Review
START YOUR REQUEST
Tell Us Who You Want to Reach
Start with your target audience. We can review the available database and project requirements.
Request Sample Data → Contact Data Fox