Technology Adoption Survey Responses

This dataset contains detailed survey responses on user adoption, barriers, and satisfaction with emerging technologies, linked to respondent demographics and technology categories. It enables researchers to analyze adoption trends, identify barriers, and assess user satisfaction across diverse populations and technology types. Ideal for academic studies, market analysis, and product development insights.

  • last updated 20 Aug 2025
  • by GoMask
The brief that made it

Academic research on technology adoption patterns

Sample rows

preview · 8 of 200 rows · all 18 columns
response_idstringrespondent_employment_statusstringrespondent_ageintegerrecommend_to_othersbooleanrespondent_education_levelstringsurvey_datedaterespondent_genderstringrespondent_countrystringtechnology_namestringtechnology_categorystringadoption_statusstringadoption_yearintegerusage_frequencystringprimary_use_casestringsatisfaction_ratingintegerbarriers_to_adoptionstringbenefits_experiencedstringadditional_commentsstring
TASR-00001employed full-time28truemaster's degree2024-04-18femaleUnited StatesChatGPTAIadopted2023dailyproductivity assistance5blankincreased efficiency, faster researchVery useful, saves hours weekly.
TASR-00002retired53truedoctoral degree2024-03-23maleGermanySmart Home HubIoTadopted2021weeklyhome automation4blankgreater convenience, energy savingsSetup is complex but worth it.
TASR-00003student19blankstudent2024-02-09maleIndiaBlockchain Walletblockchainconsideringblankneverblankblanklack of knowledge, security concernsblankWould use if more tutorials were available.
TASR-00004employed part-time35falsebachelor's degree2024-05-01femaleCanadaMeta Quest ProVR/ARadopted2022monthlyvirtual meetings3blankimproved collaboration, immersive experienceNeeds better battery life.
TASR-00005employed full-time41blankmaster's degree2024-03-07non-binaryUnited KingdomTesla Full Self-DrivingAInot adoptedblankneverblankblankcost, safety concernsblankWaiting for regulatory approval.
TASR-00006retired62truehigh school diploma2024-01-19maleAustraliaPhilips HueIoTadopted2019dailysmart lighting4blankeasy control, remote accessWish it worked better with older routers.
TASR-00007student24blankbachelor's degree2024-04-02femaleBrazilOculus Rift SVR/ARconsideringblankneverblankblankprice, hardware requirementsblankInterested in gaming applications.
TASR-00008employed full-time46trueassociate degree2024-02-28prefer not to sayJapanMicrosoft CopilotAIadopted2024weeklycoding assistance4blankfaster development, fewer errorsIntegration with IDE could be smoother.

What the 200 rows show

from the 200-row sample

Retired (respondent employment status) stands out: mean respondent_age is 60.6, against 34.7 for the rest.

  • 92%recommend_to_others = true
  • 38median respondent_age
  • 3adoption statuses
  • 4usage frequencies
  • 5respondent genders
  • 5technology categories
Mean respondent_age by respondent_employment_status200 rows
0408039.4emplo…91 rows35.5emplo…21 rows21.1stude…37 rows37.6unemp…9 rows60.6retir…39 rows49.3other3 rows
respondent_age200 rows, in bands of 10
025501347463833203105080respondent_age →

Median 38, from 15 to 74.

respondent_education_level200 rows · 9 values
  1. bachelor's degree52
  2. master's degree37
  3. high school diploma35
  4. doctoral degree22
  5. student22
  6. associate degree19
  7. less than high school6
  8. retired4
  9. other3
18 columns by typefrom the column list below
  • string 13
  • integer 3
  • date 1
  • boolean 1

Columns

18 columns in four groups
blueprint · 18 columns
columntypedescriptionexample
Text 13 columns
response_idstringUnique identifier for each survey responseuniqueTASR-00001
respondent_genderstringGender identity of the respondentmale · female · non-binary · prefer not to say · other · optionalfemale
respondent_education_levelstringHighest education level attained by the respondent7 values · optionalmaster's degree
respondent_countrystringCountry of residence of the respondentUnited States
respondent_employment_statusstringEmployment status of the respondent6 values · optionalemployed full-time
technology_namestringName of the emerging technology referenced in the responseChatGPT
technology_categorystringCategory of the technology (e.g., AI, IoT, blockchain, VR/AR)5 categories · optionalAI
adoption_statusstringWhether the respondent has adopted the technologyadopted · considering · not adoptedadopted
usage_frequencystringHow often the respondent uses the technologydaily · weekly · monthly · rarely · never · optionaldaily
primary_use_casestringMain purpose for which the respondent uses the technologyoptionalproductivity assistance
barriers_to_adoptionstringMain barriers preventing adoption (if not adopted or considering)optionalcost, safety concerns
benefits_experiencedstringKey benefits experienced by the respondent from using the technologyoptionalless stress, safer drive
additional_commentsstringAny additional feedback or comments provided by the respondentoptionalFees can be high.
Numbers 3 columns
respondent_ageintegerAge of the survey respondent13 to 12028
adoption_yearintegerYear the respondent adopted the technology (if adopted)1,990 to 2,024 · optional2023
satisfaction_ratingintegerRespondent's satisfaction with the technology (1-5 scale)1 to 5 · optional5
Dates and times 1 column
survey_datedateDate the survey was completed2024-04-18
True or false 1 column
recommend_to_othersbooleanWhether the respondent would recommend the technology to othersoptionaltrue

Use it for

  • recommend to o…92%115 of 125 rowsmean respondent age b…39.4empl…35.5empl…21.1stud…37.6unem…

    A technology dashboard

    The recommend_to_others rate, respondent_age by respondent_employment_status and a breakdown of respondent_education_level. Excel, Power BI or Tableau.

  • Why do the 39 retired rows have a mean respondent_age of 60.6?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable responses with survey_date, respondent_age and respondent_gender to fill a screen in front of a buyer.

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This dataset200 rows18 columns
Yours1,000 rows18 columnsrespondent_country: UK only

blueprint · technology-adoption-survey-responses

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 18 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.

Rules it was built with
  • Survey response and user profile anonymized
  • Adoption status labeled
  • Barrier and satisfaction scores recorded
  • Device/platform attributes included
Rows
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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
technology-adoption-survey-responses

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