Other
22 columns
60 rows
8 formats

Nonprofit Volunteer Engagement Metrics

This dataset provides a comprehensive view of volunteer engagement across nonprofit projects, capturing detailed metrics on participation, hours contributed, impact scores, and feedback. It enables organizations to analyze the effectiveness of remote and hybrid volunteer initiatives, identify trends, and improve operational efficiency in service delivery. The dataset is ideal for optimizing volunteer management, reporting, and strategic planning.

last updated 10 Jan 2026
by GoMask

The brief that made it

Analyze volunteer engagement trends across projects and time periods

Sample rows

preview · 8 of 60 rows · all 22 columns

volunteer_idstring	engagement_typestring	hours_contributedfloat	is_active_volunteerboolean	location_countrystring	volunteer_first_namestring	volunteer_last_namestring	volunteer_emailstring	volunteer_phonestring	project_idstring	project_namestring	project_typestring	engagement_idstring	engagement_datedate	tasks_completedinteger	impact_scorefloat	feedback_ratingfloat	supervisor_idstring	supervisor_namestring	location_citystring	location_statestring	feedback_commentsstring
V1001	remote	3.5	true	USA	Rachel	Nguyen	rachel.nguyen1@email.org	(212) 555-1043	P3001	STEM Outreach	education	E5001	2022-03-10	2	84.3	4.7	S2001	Helen Wright	New York	NY	Great experience working with the kids remotely.
V1002	in-person	5	true	USA	Samuel	Lee	samuel.lee2@email.org	415-555-6874	P3002	Nature Cleanup	environment	E5002	2022-04-15	4	78.1	4.2	S2002	Eliot Robinson	San Francisco	CA	Loved meeting new people and making a difference outdoors.
V1003	hybrid	2	true	UK	Fatima	Ali	f.ali@email.org	020 7946 0020	P3003	Health Awareness	health	E5003	2022-04-22	1	59.5	3.8	S2003	Priya Sharma	London	London	blank
V1004	in-person	6.25	false	USA	James	Smith	jsmith@email.org	773-555-9192	P3004	Community Meals	health	E5004	2022-05-02	5	92.2	5	S2004	Maria Lopez	Chicago	IL	Rewarding day helping serve meals.
V1005	remote	1.5	true	Australia	Amelia	Turner	amelia.turner@email.org	0452 900 792	P3005	Literacy Partners	education	E5005	2022-05-10	1	60.3	3.5	S2005	Derek Chen	Sydney	NSW	Sessions went smoothly.
V1006	remote	2.75	true	USA	Olivia	Johnson	olivia.j@email.org	blank	P3001	STEM Outreach	education	E5006	2022-06-12	1	71	4	S2001	Helen Wright	Boston	MA	Enjoyed collaborating with the team virtually.
V1007	in-person	4	false	USA	David	Kim	david.kim@email.org	206-555-8890	P3006	Urban Gardens	environment	E5007	2022-07-01	2	85.9	4.9	S2002	Eliot Robinson	Seattle	WA	Hot day but worth the effort.
V1008	hybrid	3	true	USA	Sofia	Martinez	sofia.martinez@email.org	555-0123	P3007	Clean Water Initiative	environment	E5008	2022-07-15	2	68.2	4.1	S2006	Gregory Allen	Denver	CO	Appreciated the flexibility of hybrid work.
V1009	remote	2	false	UK	Mohammed	Khan	mkhan@email.org	0117 555 2345	P3008	Mental Health Support	health	E5009	2022-07-21	1	73.7	3.9	S2003	Priya Sharma	Bristol	England	blank
V1010	in-person	4.5	true	UK	Liam	Evans	liam.evans@email.org	020 7946 0022	P3009	Youth Mentoring	education	E5010	2022-08-03	3	88.1	4.8	S2007	Laura Brooks	Manchester	England	Really enjoyed mentoring in person.
V1011	remote	2	false	Australia	Chloe	Williams	chloe.w@email.org	blank	P3005	Literacy Partners	education	E5011	2022-08-17	1	56.5	blank	S2005	Derek Chen	Melbourne	VIC	blank
V1012	hybrid	3.25	true	New Zealand	Lucas	Brown	lucas.brown@email.org	021 555 8765	P3010	Senior Tech Support	education	E5012	2022-09-02	2	80	4.3	S2008	Janet Wu	Auckland	Auckland	Helping seniors with tech was rewarding.
V1013	in-person	5.5	true	USA	Noah	Baker	noah.baker@email.org	312-555-7777	P3004	Community Meals	health	E5013	2022-09-14	4	81.4	4.2	S2004	Maria Lopez	Chicago	IL	Well organized.
V1014	hybrid	3.75	false	USA	Emily	Scott	emily.scott@email.org	555-1280	P3011	Green Schools	environment	E5014	2022-10-08	3	76.2	4.7	S2009	Samuel Reed	Portland	OR	Students loved the activities.
V1015	in-person	7	true	Canada	William	Walker	william.walker@email.org	416-555-4401	P3012	Food Security	health	E5015	2022-10-18	6	95.6	5	S2010	Anna King	Toronto	ON	Very impactful work.
V1016	remote	1.25	false	USA	Grace	Stewart	grace.stewart@email.org	blank	P3007	Clean Water Initiative	environment	E5016	2022-11-05	1	44.2	3.4	S2006	Gregory Allen	Dallas	TX	Would like more resources for remote volunteers.
V1017	remote	2	true	Canada	Benjamin	White	benjamin.white@email.org	555-3408	P3013	Digital Literacy	education	E5017	2022-11-18	1	65.5	4.1	S2008	Janet Wu	Vancouver	BC	blank
V1018	hybrid	3.5	false	New Zealand	Zara	Patel	zara.patel@email.org	021 555 1201	P3010	Senior Tech Support	education	E5018	2022-12-01	2	79.4	4.5	S2008	Janet Wu	Wellington	Wellington	Seniors showed great improvement.
V1019	in-person	4.25	true	USA	Mia	Clark	mia.clark@email.org	555-8790	P3006	Urban Gardens	environment	E5019	2022-12-11	2	82.8	4.6	S2002	Eliot Robinson	San Diego	CA	Great teamwork on-site.
V1020	hybrid	2.5	true	USA	Harper	Reed	harper.reed@email.org	555-2341	P3011	Green Schools	environment	E5020	2023-01-09	2	62	3.7	S2009	Samuel Reed	Houston	TX	blank

What the 60 rows show

from the 60-row sample

In-person (engagement type) stands out: mean hours_contributed is 5.5, against 2.7 for the rest.

65%is_active_volunteer = true
3.5median hours_contributed
3project types
3median tasks_completed
69.6median impact_score
4.1median feedback_rating

Mean hours_contributed by engagement_type60 rows

hours_contributed60 rows, in bands of 1

Median 3.5, from 1.3 to 7.0.

location_country60 rows · top 10 of 25 values

USA16
Canada7
UK6
Germany4
Australia3
New Zealand3
India2
UAE2
Egypt1
Russia1

22 columns by typefrom the column list below

string 16
integer 1
float 3
date 1
boolean 1

Columns

22 columns in four groups

blueprint · 22 columns
column	type	description	example
Text 16 columns
`volunteer_id`	string	Unique identifier for each volunteerunique	V1001
`volunteer_first_name`	string	First name of the volunteer	Rachel
`volunteer_last_name`	string	Last name of the volunteer	Nguyen
`volunteer_email`	string	Email address of the volunteerunique	rachel.nguyen1@email.org
`volunteer_phone`	string	Contact phone number of the volunteeroptional	(212) 555-1043
`project_id`	string	Unique identifier for the nonprofit project	P3001
`project_name`	string	Name of the nonprofit project	STEM Outreach
`project_type`	string	Type of project (e.g., education, health, environment)3 types	education
`engagement_id`	string	Unique identifier for each volunteer engagement instanceunique	E5001
`engagement_type`	string	Type of engagement (remote, hybrid, in-person)remote · hybrid · in-person	remote
`feedback_comments`	string	Optional qualitative feedback from the volunteeroptional	Sessions went smoothly.
`supervisor_id`	string	Unique identifier for the project supervisor overseeing the engagementoptional	S2001
`supervisor_name`	string	Name of the project supervisoroptional	Helen Wright
`location_city`	string	City where the engagement took place (if applicable)optional	New York
`location_state`	string	State or region of the engagement locationoptional	NY
`location_country`	string	Country of the engagement locationoptional	USA
Numbers 4 columns
`hours_contributed`	float	Number of hours contributed by the volunteer in this engagement0 or more	3.5
`tasks_completed`	integer	Number of tasks completed during this engagement0 or more · optional	2
`impact_score`	float	Quantitative measure of the impact achieved during this engagement (e.g., 0-100 scale)0 to 100 · optional	84.3
`feedback_rating`	float	Volunteer feedback rating for this engagement (e.g., 1-5 scale)1 to 5 · optional	4.7
Dates and times 1 column
`engagement_date`	date	Date of the volunteer engagement activity	2022-03-10
True or false 1 column
`is_active_volunteer`	boolean	Indicates if the volunteer is currently active	true

Use it for

A dashboard
The is_active_volunteer rate, hours_contributed by engagement_type and a breakdown of location_country. Excel, Power BI or Tableau.
Why do the 21 in-person rows have a mean hours_contributed of 5.5?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Volunteers60
V10013.5remote
V10025in-person
V10046.25in-person
A software demo
Believable volunteers with volunteer_first_name, volunteer_last_name and volunteer_email to fill a screen in front of a buyer.

This dataset60 rows22 columns

Yours1,000 rows22 columnslocation_city: UK only

blueprint · nonprofit-volunteer-engagement-metrics

Behind this dataset

Same schema. As many rows as you need.

These 60 rows came out of a blueprint — 22 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

Each row captures a unique volunteer-project interaction.
Engagement scores are calculated based on activity frequency and task completion.
Remote participation is flagged to enable comparison with on-site engagement.
Projects must be categorized by program type for granular analysis.
Feedback ratings are included if submitted by volunteers.

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: nonprofit-volunteer-engagement-metrics

What should your data show?

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Sample rows

What the 60 rows show

Columns

Use it for

A dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Other

What should your data show?