✓ TestedWorks with CSV, Excel, Google Sheets → JSON-LD Schema
By dataclean.to team · 2026-02-12
SurveyMonkey collects respondent email addresses through survey email fields, collector settings, and integration data. Whether you are running customer satisfaction surveys, employee feedback forms, or market research questionnaires, the email data you export has quality issues ranging from deliberate fake entries by reluctant respondents to accidental typos by those who want to participate but rush through the form. dataclean.to validates your SurveyMonkey export to separate real respondent contacts from unreliable entries.
The Problem
SurveyMonkey email data quality varies by how the survey was distributed and whether the email field was optional or required. When email is required, respondents who want anonymity enter fake addresses (test@test.com, none@none.com, na@na.com). Web link surveys shared publicly attract bot responses with random email addresses. Email collector surveys pre-populate the respondent's email, but forwarded survey links result in responses attributed to the original recipient rather than the actual respondent. SurveyMonkey's email question type validates format but not domain existence, so addresses at nonexistent domains pass through. Panel responses (SurveyMonkey Audience) include panel member emails that the respondent may not use as their primary address. Multi-page surveys where the email question is on the first page sometimes have the email captured even when the respondent abandons the survey later, creating records with an email but incomplete response data. Embedded surveys on websites collect whatever the form field allows. SurveyMonkey response export documentation
How to Fix It
1
Export survey responses from SurveyMonkey
In SurveyMonkey, go to the survey's Analyze Results section and click Export. Choose CSV or XLS format. Include all responses, or filter by completion status to exclude partial responses with only an email and no survey data.
2
Upload to dataclean.to
Import the SurveyMonkey export. The platform identifies email columns (whether from email questions or collector metadata) and validates every respondent address.
3
Remove deliberately fake entries
Detect common fake email patterns from respondents who did not want to share their real address: test@test.com, no@no.com, abc@abc.com, and single-character addresses. These follow recognizable patterns distinct from genuine typos.
4
Fix genuine respondent typos
Correct domain misspellings from respondents who intended to provide their real email but made entry errors. These are valuable contacts who engaged with your survey and deserve accurate follow-up.
5
Export validated respondent contacts
Download clean survey data with validated email addresses. Use the verified contacts for follow-up communications, incentive delivery, or import into your CRM linked to their survey responses.
Frequently Asked Questions
How do I tell the difference between a typo and a deliberately fake email?
Deliberate fakes follow patterns: very short addresses (a@b.com), repeated characters (aaa@aaa.com), words indicating refusal (noemail@noemail.com), or well-known test domains (test.com, example.com). Typos show recognizable misspellings of real domains (gmial.com, yahooo.com).
Should I make the email question required in surveys?
Making email required increases response rate for the field but also increases fake entries from respondents who do not want to share. Making it optional gives you fewer but more genuine addresses. Cleaning helps either way, but optional fields produce higher-quality data overall.
Can I clean responses from multiple SurveyMonkey surveys?
Yes. Export each survey's responses separately and upload them to dataclean.to. This is useful when you want to build a consolidated contact list from respondents across multiple research studies.
Example: Input → Output
name
email
phone
city
status
Alice Johnson
alice@example.com
+1-555-0101
New York
active
alice johnson
ALICE@EXAMPLE.COM
5550101
new york
Active
Red rows show common data quality issues. dataclean.to normalizes and generates JSON-LD automatically.