Government
24 columns
200 rows
8 formats

Local Government Feedback Survey

This dataset contains synthetic responses from residents evaluating local government services, including demographic information, service usage, satisfaction ratings, and open-ended feedback. It is designed for public policy analysis, service quality monitoring, and targeted improvement initiatives, enabling data-driven decision-making for local authorities.

last updated 21 Aug 2025
by GoMask

The brief that made it

Service quality benchmarking and improvement planning

Sample rows

preview · 8 of 200 rows · all 24 columns

response_idstring	respondent_education_levelstring	respondent_ageinteger	would_recommend_serviceboolean	respondent_ethnicitystring	survey_datedate	respondent_genderstring	respondent_employment_statusstring	address_streetstring	address_citystring	address_statestring	address_postal_codestring	address_countrystring	service_typestring	service_access_frequencystring	service_satisfaction_ratinginteger	service_quality_ratinginteger	service_timeliness_ratinginteger	service_staff_professionalism_ratinginteger	service_accessibility_ratinginteger	service_cost_ratinginteger	service_improvement_suggestionsstring	contact_permissionboolean	contact_emailstring
R00001	associate degree	25	true	Latino	2024-01-02	female	student	220 Maple Ave	Chicago	IL	60616	USA	education	daily	5	5	4	5	5	4	More online course options would be helpful.	false	blank
R00002	bachelor's degree	40	true	White	2024-03-15	male	employed	1350 Ocean Blvd	San Diego	CA	92101	USA	public safety	monthly	4	3	3	4	4	3	More police presence in residential areas.	true	john.safety@samplemail.com
R00003	doctorate	66	true	Jewish	2023-12-12	female	retired	17 Rue Montmartre	Paris	blank	75001	France	parks and recreation	rarely	3	4	2	3	4	4	Restrooms could be cleaner.	false	blank
R00004	high school	19	false	Filipino	2024-05-01	non-binary	student	78 Rizal St	Manila	blank	1008	Philippines	transportation	weekly	2	2	1	3	2	3	Buses are often late; need better scheduling.	false	blank
R00005	none	87	true	Irish	2024-02-28	male	retired	12 Main St	Dublin	blank	D01	Ireland	social services	monthly	4	4	5	4	5	5	Great staff, but more support for elderly needed.	true	patrick.social@irishmail.ie
R00006	other	120	false	Chinese	2024-04-04	female	retired	88 Beijing Rd	Beijing	blank	100000	China	waste management	rarely	1	2	1	2	2	1	Trash collection is inconsistent.	false	blank
R00007	high school	34	false	Black	2024-06-14	male	unemployed	400 Pine St	Detroit	MI	48226	USA	waste management	monthly	2	2	2	1	3	2	Missed pickups, need better communication.	false	blank
R00008	bachelor's degree	52	false	Arab	2024-05-21	female	employed	22 Al Maktoum St	Dubai	blank	00000	UAE	other	never	1	1	1	1	1	1	blank	false	blank
R00009	doctorate	73	true	French	2024-03-05	prefer not to say	retired	14 Avenue des Champs	Nice	blank	06000	France	parks and recreation	weekly	5	4	5	5	4	5	Love the walking trails, keep them maintained.	false	blank
R00010	master's degree	29	true	Indian	2024-05-25	male	employed	44 MG Road	Mumbai	blank	400001	India	transportation	daily	4	4	3	4	4	5	Metro is reliable but can be crowded.	true	raj.transport@indiamail.in
R00011	other	57	true	Hispanic	2024-04-10	other	employed	789 Calle 7	Mexico City	blank	01030	Mexico	social services	monthly	3	3	2	3	3	3	Better outreach for families in need.	true	luis.social@mexmail.mx
R00012	associate degree	46	false	Native American	2024-01-18	female	unemployed	315 Cedar Ct	Phoenix	AZ	85004	USA	waste management	rarely	2	2	1	2	2	2	Bins are not always emptied on time.	false	blank
R00013	high school	23	true	Mexican	2024-02-08	male	student	56 Avenida Central	Guadalajara	blank	44100	Mexico	education	daily	3	3	2	4	3	3	School needs more computers.	false	blank
R00014	none	120	false	blank	2024-04-23	prefer not to say	retired	blank	Reykjavik	blank	101	Iceland	parks and recreation	never	1	1	1	1	1	1	blank	false	blank
R00015	bachelor's degree	35	true	Korean	2024-03-29	female	employed	120 Gangnam-daero	Seoul	blank	06130	South Korea	transportation	daily	5	5	5	5	5	4	Metro is clean and efficient.	true	mina.transport@koramail.kr
R00016	master's degree	32	true	White	2024-05-16	male	employed	145 King St	Toronto	ON	M5H 1J9	Canada	public safety	weekly	4	4	3	4	4	4	More visible patrols needed downtown.	false	blank
R00017	bachelor's degree	27	true	Chinese	2024-06-03	female	employed	600 Nathan Rd	Hong Kong	blank	999077	Hong Kong	parks and recreation	monthly	5	4	5	5	5	4	Events for families are great.	true	li.parks@hkmail.hk
R00018	other	48	false	Middle Eastern	2024-02-17	male	unemployed	1245 King Fahd Rd	Riyadh	blank	11564	Saudi Arabia	waste management	monthly	2	2	2	2	2	2	Service could be more reliable.	false	blank
R00019	student	22	true	Brazilian	2024-01-27	female	student	102 Avenida Paulista	Sao Paulo	blank	01310-000	Brazil	education	daily	3	4	3	3	3	3	More scholarships for international students.	true	ana.edu@brmail.com
R00020	master's degree	58	false	White	2024-06-07	male	employed	521 Elm St	Houston	TX	77002	USA	public safety	monthly	3	2	2	3	3	3	Better traffic enforcement needed.	false	blank

What the 200 rows show

from the 200-row sample

None (respondent education level) stands out: mean respondent_age is 106.6, against 40.1 for the rest.

67%would_recommend_service = true
40median respondent_age
4respondent employment statuses
5respondent genders
5service access frequencies
7service types

Mean respondent_age by respondent_education_level200 rows

respondent_age200 rows, in bands of 20

Median 40, from 18 to 120.

respondent_ethnicity182 rows with a value · 18 left blank

White31
Asian23
Latino15
Jewish12
Black12
Indian12
Arab10
Filipino9
Irish8
Chinese8

24 columns by typefrom the column list below

string 14
integer 7
date 1
boolean 2

Columns

24 columns in four groups

blueprint · 24 columns
column	type	description	example
Text 14 columns
`response_id`	string	Unique identifier for each survey responseunique	R00001
`respondent_gender`	string	Gender identity of the respondentmale · female · non-binary · prefer not to say · other	female
`respondent_ethnicity`	string	Ethnic background of the respondentoptional	Latino
`respondent_education_level`	string	Highest level of education completed by the respondent7 values · optional	associate degree
`respondent_employment_status`	string	Current employment status of the respondentemployed · unemployed · student · retired · other · optional	student
`address_street`	string	Street address of the respondentoptional	220 Maple Ave
`address_city`	string	City of residence of the respondent	Chicago
`address_state`	string	State or region of residence of the respondent	IL
`address_postal_code`	string	Postal code of the respondent's addressoptional	60616
`address_country`	string	Country of residence of the respondent	USA
`service_type`	string	Type of local government service being evaluated7 values	education
`service_access_frequency`	string	How often the respondent uses the servicedaily · weekly · monthly · rarely · never	daily
`service_improvement_suggestions`	string	Open-ended feedback or suggestions for service improvementoptional	Love the park events.
`contact_email`	string	Email address for follow-up, if permission grantedoptional	luis.social@mexmail.mx
Numbers 7 columns
`respondent_age`	integer	Age of the respondent at the time of survey18 to 120	25
`service_satisfaction_rating`	integer	Overall satisfaction rating for the service (1-5 scale)1 to 5	5
`service_quality_rating`	integer	Quality rating for the service (1-5 scale)1 to 5 · optional	5
`service_timeliness_rating`	integer	Timeliness rating for the service (1-5 scale)1 to 5 · optional	4
`service_staff_professionalism_rating`	integer	Staff professionalism rating for the service (1-5 scale)1 to 5 · optional	5
`service_accessibility_rating`	integer	Accessibility rating for the service (1-5 scale)1 to 5 · optional	5
`service_cost_rating`	integer	Cost rating for the service (1-5 scale)1 to 5 · optional	4
Dates and times 1 column
`survey_date`	date	Date when the survey was completed	2024-01-02
True or false 2 columns
`would_recommend_service`	boolean	Whether the respondent would recommend the service to others	true
`contact_permission`	boolean	Whether the respondent gives permission to be contacted for follow-upoptional	false

Use it for

A government dashboard
The would_recommend_service rate, respondent_age by respondent_education_level and a breakdown of respondent_ethnicity. Excel, Power BI or Tableau.
Why do the 34 none rows have a mean respondent_age of 106.6?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Responses200
R0000125associat…
R0000240bachelor…
R0000419high sch…
A software demo
Believable responses with survey_date, respondent_age and respondent_gender to fill a screen in front of a buyer.

This dataset200 rows24 columns

Yours1,000 rows24 columnsaddress_street: UK only

blueprint · local-government-feedback-survey

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 24 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

Rating 1-5 per service
Free text comments (100-300 chars)
Respondent anonymized and randomized
Survey date within current year

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

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: local-government-feedback-survey

What should your data show?

No signup. No card.

Sample rows

What the 200 rows show

Columns

Use it for

A government dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Government

What should your data show?