Survey Respondents
This dataset provides detailed records of survey respondents, including demographic information, completion rates, segmentation labels, and response quality metrics. It enables in-depth analysis of participant behavior, demographic trends, and survey effectiveness, making it ideal for market research, academic studies, and customer insights.
Sample rows
preview · 8 of 200 rows · all 17 columns| respondent_idstring | completion_statusstring | completion_ratefloat | attention_check_passedboolean | segment_labelstring | survey_idstring | response_datedatetime | response_quality_scorefloat | ageinteger | genderstring | ethnicitystring | education_levelstring | income_bracketstring | countrystring | regionstring | citystring | response_time_secondsinteger |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| RSP0001 | completed | 100 | true | young professionals | SURV2024A | 2024-04-28T09:32:14Z | 92.5 | 29 | female | White | bachelor's degree | 40k-60k | USA | California | San Francisco | 775 |
| RSP0002 | partial | 85.6 | false | college students | SURV2024B | 2024-04-28T16:45:01Z | 67.1 | 19 | male | Hispanic | associate degree | 20k-40k | Canada | Ontario | Toronto | 420 |
| RSP0003 | completed | 100 | true | urban mid-career | SURV2024C | 2024-04-29T13:24:20Z | 80.2 | 37 | non-binary | Black | master's degree | 60k-80k | UK | Greater London | London | 1012 |
| RSP0004 | abandoned | 0 | false | teenagers | SURV2024D | 2024-04-29T19:15:10Z | blank | 16 | female | East Asian | high school | <20k | Australia | Victoria | Melbourne | 10 |
| RSP0005 | completed | 100 | true | retirees | SURV2024E | 2024-04-30T08:41:55Z | 97.9 | 66 | male | White | doctorate | 100k+ | Germany | Bavaria | Munich | 1345 |
| RSP0006 | partial | 54.7 | false | university students | SURV2024A | 2024-04-30T14:03:28Z | 45.6 | 22 | male | South Asian | bachelor's degree | 20k-40k | India | Maharashtra | Mumbai | 312 |
| RSP0007 | completed | 100 | true | mid-career professionals | SURV2024B | 2024-05-01T11:24:55Z | 75.8 | 45 | female | Arab | master's degree | 80k-100k | UAE | Dubai | Dubai | 889 |
| RSP0008 | abandoned | 2 | false | low engagement | SURV2024C | 2024-05-01T16:36:22Z | 3.2 | 8 | other | Native American | other | <20k | USA | Arizona | Phoenix | 22 |
| RSP0009 | completed | 100 | true | young professionals | SURV2024D | 2024-05-02T09:05:37Z | 88.7 | 34 | female | Latino | bachelor's degree | 40k-60k | Mexico | Jalisco | Guadalajara | 718 |
| RSP0010 | partial | 68.3 | false | midlife learners | SURV2024E | 2024-05-02T13:44:58Z | 48.9 | 54 | female | East Asian | associate degree | 20k-40k | Singapore | Central Region | Singapore | 365 |
| RSP0011 | completed | 100 | true | centenarians | SURV2024A | 2024-05-03T10:56:22Z | 100 | 102 | male | White | doctorate | 100k+ | Japan | Kanto | Tokyo | 1482 |
| RSP0012 | partial | 60.4 | false | privacy-conscious | SURV2024B | 2024-05-03T15:10:39Z | blank | blank | prefer not to say | Prefer not to say | prefer not to say | prefer not to say | France | Île-de-France | Paris | 211 |
| RSP0013 | completed | 100 | true | graduate students | SURV2024C | 2024-05-04T09:31:11Z | 86.4 | 24 | female | Mixed | bachelor's degree | 40k-60k | USA | New York | New York | 663 |
| RSP0014 | abandoned | 5 | false | infants | SURV2024D | 2024-05-04T18:55:29Z | 2.8 | 0 | male | Unknown | other | <20k | Brazil | São Paulo | São Paulo | 19 |
| RSP0015 | completed | 100 | true | retirees | SURV2024E | 2024-05-05T08:24:37Z | 71.3 | 64 | female | White | associate degree | <20k | USA | Florida | Orlando | 978 |
| RSP0016 | partial | 77.2 | false | students | SURV2024A | 2024-05-05T15:39:55Z | 41.6 | 21 | female | Pacific Islander | high school | <20k | New Zealand | Auckland | Auckland | 316 |
| RSP0017 | completed | 100 | true | young professionals | SURV2024B | 2024-05-06T09:44:21Z | 84.9 | 33 | male | Middle Eastern | bachelor's degree | 60k-80k | Egypt | Cairo | Cairo | 921 |
| RSP0018 | abandoned | 1.3 | false | inactive | SURV2024C | 2024-05-06T17:17:35Z | blank | 38 | prefer not to say | Prefer not to say | prefer not to say | prefer not to say | Spain | Catalonia | Barcelona | 5 |
| RSP0019 | completed | 100 | true | young professionals | SURV2024D | 2024-05-07T13:08:42Z | 77.6 | 28 | female | Asian | high school | 20k-40k | South Korea | Seoul | Seoul | 765 |
| RSP0020 | partial | 33.9 | false | teenagers | SURV2024E | 2024-05-07T21:22:03Z | 23.4 | 17 | male | Black | high school | <20k | USA | Texas | Houston | 135 |
What the 200 rows show
from the 200-row sampleAbandoned (completion status) stands out: mean completion_
- 56%attention_
check_ passed = true - 99.5median completion_
rate - 5surveys
- 5genders
- 7education levels
- 7income brackets
Median 99.5, from 0.0 to 100.0.
- string 11
- integer 2
- float 2
- datetime 1
- boolean 1
Columns
17 columns in four groups| column | type | description | example |
|---|---|---|---|
| Text 11 columns | |||
respondent_id | string | Unique identifier for each survey respondentunique | RSP0001 |
survey_id | string | Identifier for the specific survey completed by the respondent5 surveys | SURV2024A |
completion_status | string | Indicates whether the survey was completed, partially completed, or abandonedcompleted · partial · abandoned | completed |
gender | string | Gender of the respondentmale · female · non-binary · prefer not to say · other · optional | female |
ethnicity | string | Ethnic background of the respondentoptional | White |
education_level | string | Highest level of education attained by the respondent7 values · optional | bachelor's degree |
income_bracket | string | Income bracket of the respondent7 values · optional | 40k-60k |
country | string | Country of residence of the respondentoptional | USA |
region | string | Region or state/province within the countryoptional | California |
city | string | City of residenceoptional | San Francisco |
segment_label | string | Demographic segment or group assigned to the respondent (e.g., 'young professionals', 'retirees')optional | young professionals |
| Numbers 4 columns | |||
completion_rate | float | Percentage of survey questions answered by the respondent (0-100)0 to 100 | 100 |
response_quality_score | float | Quality metric for the respondent's answers (e.g., based on consistency, attention checks; 0-100)0 to 100 · optional | 92.5 |
age | integer | Age of the respondent in years0 to 120 · optional | 29 |
response_time_seconds | integer | Total time taken by the respondent to complete the survey in seconds0 or more · optional | 775 |
| Dates and times 1 column | |||
response_date | datetime | Timestamp when the respondent submitted the survey | 2024-04-28T09:32:14Z |
| True or false 1 column | |||
attention_check_passed | boolean | Indicates if the respondent passed embedded attention checksoptional | true |
Use it for
A marketing dashboard
The attention_
check_ passed rate, completion_ rate by completion_ status and a breakdown of segment_ label. Excel, Power BI or Tableau. Why do the 30 abandoned rows have a mean completion_
rate of 1.8? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Respondents200RSP0001100completedRSP000285.6partialRSP0003100completed
A software demo
Believable respondents with survey_
id, response_ date and completion_ status to fill a screen in front of a buyer.
blueprint · survey-respondents
Behind this dataset
Same schema. As many rows as you need.
These 200 rows came out of a blueprint — 17 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.
- Survey start before completion timestamp
- Completion rate percentage 0-100
- Demographic categories for segmentation
- Response quality score based on completeness
- Incentive status for participation tracking
1 credit per row. Preview 20 rows free. Buy rows for the full run.
- Exports
- CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
- Licence
- yours to use, including commercially
- API slug
- survey-respondents