Overview
Bringing your historical survey data into Culture Amp can provide helpful context and insights. In most cases, the fastest and simplest way to do this is through External Comparisons, which allow you to benchmark current survey results against past scores.
This guide will walk you through factors to consider when bringing data over from an external provider and explain why External Comparisons are usually the best approach for most organizations.
If your team has a specific need to bring across full historical response data, we’ll also cover Full Survey Import considerations.
Why We Recommend External Comparisons First
For most organizations, External Comparisons are the simplest and quickest way to bring past data into Culture Amp.
Key Benefits:
Fast turnaround (usually within 2–3 business days)
No need to upload individual responses or participants
You don’t need to set up a comparison before running your survey—External Comparisons can be added anytime after your survey is live.
Great for identifying high-level trends across surveys
You can always revisit a Full Survey Import later. Starting with External Comparisons means you can start gaining insights sooner—with less effort.
Comparison Overview
Feature | External Comparison (Recommended) | Full Survey Import |
Purpose | Benchmark past scores alongside new results | Migrate every individual response |
Timeline | 2–3 business days | 2–6 weeks |
Effort Required | Low | High |
Import Limit | Unlimited | Max 5 surveys |
Data Needed | Summary-level scores | Full response-level data |
Supports Attributed or Unattributed Data | Yes ✔️ | Yes ✔️ |
Requires All Past and Present Users to Be Added to the Platform | No ✖️ | Yes ✔️ (for attributed surveys) |
Supports | Engagement, Exit, and Onboarding surveys | Engagement surveys only |
Data Considerations Before You Import
Understanding the requirements for each method can help you choose the right path—and avoid setup issues later on.
External Comparisons
External Comparisons only require summary-level data. You’ll need favorable percentages at the question level, and optionally by factor and/or demographic.
What’s needed:
Favorable % per question (based on Agree/Strongly Agree responses on a 5-point scale)
Optional: Favorable % per factor
Optional: Favorable % per demographic (e.g. department, location)
You’ll need a survey in Culture Amp with questions and factors (how questions are grouped in reports)—that match or are equivalent in intent to those in your external data. Once your survey is set up, you can load the external data against it at any time.
If you’re including demographic comparisons (optional), ensure those demographics have been created as account demographics in Culture Amp.
Things to keep in mind:
No individual response data or participant uploads are required
Works best when your Culture Amp survey question and structure closely matches your external survey.
Culture Amp’s favorable score includes responses of 4 (Agree) and 5 (Strongly Agree) on a 5-point scale.
If comparing factor scores, note that Culture Amp includes only participants who answered all questions within a factor.
Tip:
Full Survey Imports
Full Survey Imports bring in individual-level response data. This option requires more preparation and a longer lead time.
What’s needed:
Full response file (CSV or XLS), including:
Each respondent
Their answers to each question
Demographic information (if available)
All past and present participants must be uploaded as users in Culture Amp (for attributed surveys)
Rating scale conversion, if your past scale differs from Culture Amp’s 5-point scale.
Example file format:
Respondent | Question 1 | Question 2 | Question 3 | Question 4 |
Employee 1 | 2 | 5 | 3 | 5 |
Employee 2 | 3 | 3 | 4 | 5 |
Rating Scale Alignment
If your previous surveys used a different rating scale (e.g. 7-point, 10-point 11-point etc), you’ll need to map your historical scores to Culture Amp’s 5-point scale for each individual response.
Culture Amp 5-Point Scale
Score | Label |
1 | Strongly Disagree |
2 | Disagree |
3 | Neither Agree nor Disagree |
4 | Agree |
5 | Strongly Agree |
Check out the Example conversion below for 11, 10 and 7 point scales:
Additional Considerations
Just because you can import the data doesn’t mean you should. Ask yourself whether the historical data will add clarity or create confusion in your analysis.
Watch out for:
Incompatible rating scales: If your previous scale used labels like “Fair to Poor,” as an example it may not map cleanly to Culture Amp’s agreement-based model. This can skew comparisons.
Centrality bias: People often avoid extreme responses on longer or more complex scales. A switch in format can change how people answer—even if their opinions haven’t changed.
Age of the survey: Older data can help show long-term trends, but may not represent your current culture or team makeup.
Choosing the Right Import Method
External Comparisons
✅ Pros
Fast to set up
Low data requirements
Easy to match with current Culture Amp surveys
Great for benchmarking and identifying trends
Supports question, factor, and demographic comparisons (one level)
❌ Cons
One level of demographic comparison
Full Survey Imports
✅ Pros
Includes individual-level data
Supports more detailed demographic slicing
❌ Cons
Complex to set up
Requires full past and present user list (for Attributed surveys) and large, clean data files
Takes 2–6 weeks to complete
Often not necessary to meet your goals
What's Up Next?
Follow the step-by-step guides below to get started:
How to Import External Comparisons – A quick and simple method for benchmarking past scores
Migrating Full Surveys into Culture Amp – A detailed process for importing full historical survey data
💬 Need help? Just reply with "Ask a Person" in a support conversation to speak with a Product Support Specialist.