Marketing
23 columns
200 rows
8 formats

Influencer Engagement Time Series

This dataset provides granular, hourly influencer engagement metrics across major social media platforms, including detailed audience demographics and campaign associations. Brands and agencies can leverage this data for AI-powered analysis of peak activity times, audience response profiles, and campaign effectiveness, enabling data-driven marketing strategies and influencer selection.

last updated 23 Oct 2025
by GoMask

The brief that made it

Identifying peak influencer activity and optimal posting times for campaigns

Sample rows

preview · 8 of 200 rows · all 23 columns

engagement_idstring	engagement_typestring	engagement_countinteger	is_paid_campaignboolean	audience_location_countrystring	influencer_idstring	influencer_namestring	platformstring	campaign_idstring	campaign_namestring	timestampdatetime	content_idstring	content_typestring	audience_reachinteger	audience_demographics_age_18_24float	audience_demographics_age_25_34float	audience_demographics_age_35_44float	audience_demographics_age_45_plusfloat	audience_demographics_gender_malefloat	audience_demographics_gender_femalefloat	audience_demographics_gender_otherfloat	brand_idstring	brand_namestring
ENG1-20240612-001	like	213	true	United States	INF001	Sophie Chen	Instagram	CMP101	Summer Glow	2024-06-12T09:00:00	CONT-IG-001	post	1050	41.2	32.5	19.1	7.2	34.7	63.3	2	BRD-001	Glow Cosmetics
ENG2-20240612-002	view	1205	false	India	INF002	Liam Patel	TikTok	blank	blank	2024-06-12T13:00:00	CONT-TT-001	video	3020	48.6	36.8	12.3	2.3	40.2	58.1	1.7	blank	blank
ENG3-20240612-003	comment	86	true	Mexico	INF003	Maya Rivera	YouTube	CMP102	Tech Trends	2024-06-12T15:00:00	CONT-YT-001	video	1750	22	37.5	29	11.5	70.3	27.3	2.4	BRD-002	Nova Tech
ENG4-20240612-004	reaction	41	false	South Korea	INF004	David Kim	Twitter	blank	blank	2024-06-12T16:00:00	CONT-TW-001	tweet	520	33.9	34.7	17.3	14.1	55.1	43.5	1.4	blank	blank
ENG5-20240612-005	share	54	true	United Kingdom	INF005	Emma Williams	Facebook	CMP103	Healthy Living	2024-06-12T11:00:00	CONT-FB-001	post	600	10.7	29.6	41.9	17.8	38	59.2	2.8	BRD-003	FitLife
ENG6-20240612-006	save	15	false	China	INF006	Lucas Zhang	LinkedIn	blank	blank	2024-06-12T10:00:00	CONT-LN-001	post	175	8.1	44.8	35.1	12	52.7	45.8	1.5	blank	blank
ENG7-20240612-007	view	789	true	Canada	INF007	Olivia Smith	Snapchat	CMP104	Fun Moments	2024-06-12T20:00:00	CONT-SC-001	story	1250	61.6	24.3	9.6	4.5	42.4	56.7	0.9	BRD-004	SnapFun
ENG8-20240612-008	view	1340	false	Spain	INF008	Carlos Martinez	Instagram	blank	blank	2024-06-12T21:00:00	CONT-IG-002	reel	2900	58.4	31	8.6	2	49.8	48.2	2	blank	blank
ENG9-20240612-009	like	924	true	India	INF009	Priya Gupta	TikTok	CMP105	Dance Fever	2024-06-12T18:00:00	CONT-TT-002	video	1980	52.2	34.1	11.8	1.9	36.2	61.4	2.4	BRD-005	MoveOn
ENG10-20240612-010	view	430	false	South Korea	INF010	Jin Park	YouTube	blank	blank	2024-06-12T22:00:00	CONT-YT-002	live_stream	1500	24.8	41	28.7	5.5	64.1	33.7	2.2	blank	blank
ENG11-20240612-011	comment	19	true	Australia	INF011	Natalie Carter	Facebook	CMP106	Eco Drive	2024-06-12T08:00:00	CONT-FB-002	post	245	7.9	22.7	38.1	31.3	39.7	58.9	1.4	BRD-006	GreenWheels
ENG12-20240612-012	click	6	false	United Arab Emirates	INF012	Amir Hassan	LinkedIn	blank	blank	2024-06-12T13:00:00	CONT-LN-002	post	55	3.7	52.9	33.4	10	56	41.7	2.3	blank	blank
ENG13-20240612-013	save	72	true	Italy	INF013	Isabella Rossi	Instagram	CMP107	Fashion Forward	2024-06-12T14:00:00	CONT-IG-003	story	330	46.1	39.5	9.3	5.1	24.6	72.9	2.5	BRD-007	ModaStar
ENG14-20240612-014	share	37	false	United States	INF014	Ethan Brown	Twitter	blank	blank	2024-06-12T19:00:00	CONT-TW-002	tweet	410	27.5	38.2	20.3	14	60.8	38.6	0.6	blank	blank
ENG15-20240612-015	like	163	true	France	INF015	Chloe Dubois	Facebook	CMP108	Travel Tales	2024-06-12T12:00:00	CONT-FB-003	post	740	13.9	35.7	28.4	22	41.3	56.6	2.1	BRD-008	VoyagePro
ENG16-20240612-016	comment	12	false	Egypt	INF016	Mohamed El-Sayed	LinkedIn	blank	blank	2024-06-12T17:00:00	CONT-LN-003	post	120	6.8	39.2	41.3	12.7	61.5	37.8	0.7	blank	blank
ENG17-20240612-017	view	765	true	Germany	INF017	Lina Müller	Instagram	CMP109	Vegan Vibes	2024-06-12T08:00:00	CONT-IG-004	reel	2350	35	37	21.5	6.5	32.2	66	1.8	BRD-009	GreenTaste
ENG18-20240612-018	share	302	false	Japan	INF018	Yuki Tanaka	TikTok	blank	blank	2024-06-12T09:00:00	CONT-TT-003	video	810	44.3	41.2	10.6	3.9	51.1	47.3	1.6	blank	blank
ENG19-20240612-019	like	298	true	United States	INF019	Ava Johnson	YouTube	CMP110	Healthy Eats	2024-06-12T11:00:00	CONT-YT-003	video	1750	19.6	33.2	36.9	10.3	26.4	71.8	1.8	BRD-010	FreshBite
ENG20-20240612-020	reaction	23	false	Singapore	INF020	Tom Lee	Facebook	blank	blank	2024-06-12T20:00:00	CONT-FB-004	post	135	10.5	31.8	41.6	16.1	48.2	51.2	0.6	blank	blank

What the 200 rows show

from the 200-row sample

View (engagement type) stands out: mean engagement_count is 1,479, against 129.9 for the rest.

49%is_paid_campaign = true
99median engagement_count
6content types
7platforms
950median audience_reach
31.5median audience_demographics_age_18_24

Mean engagement_count by engagement_type200 rows

engagement_count200 rows, in bands of 1,000

Median 99, from 5 to 5,240.

audience_location_country200 rows · top 10 of 35 values

United States27
United Kingdom14
Brazil12
Sweden10
Germany9
Singapore9
India8
Canada8
Australia8
Vietnam8

23 columns by typefrom the column list below

string 12
integer 2
float 7
datetime 1
boolean 1

Columns

23 columns in four groups

blueprint · 23 columns
column	type	description	example
Text 12 columns
`engagement_id`	string	Unique identifier for each engagement recordunique	ENG1-20240612-001
`influencer_id`	string	Unique identifier for the influencer	INF001
`influencer_name`	string	Public display name of the influencer	Sophie Chen
`platform`	string	Social media platform where engagement occurred (e.g., Instagram, TikTok, YouTube)7 values	Instagram
`campaign_id`	string	Unique identifier for the marketing campaign associated with the engagementoptional	CMP101
`campaign_name`	string	Name of the marketing campaign (if applicable)optional	Summer Glow
`content_id`	string	Unique identifier for the content posted by the influencer	CONT-IG-001
`content_type`	string	Type of content (e.g., post, story, video, live stream)6 values	post
`engagement_type`	string	Type of engagement (e.g., like, comment, share, view, click)7 values	like
`audience_location_country`	string	Primary country of the audience for this engagement recordoptional	United States
`brand_id`	string	Unique identifier for the brand sponsoring the campaign (if applicable)optional	BRD-001
`brand_name`	string	Name of the brand sponsoring the campaign (if applicable)optional	Glow Cosmetics
Numbers 9 columns
`engagement_count`	integer	Number of engagements of the specified type within the hour0 or more	213
`audience_reach`	integer	Estimated number of unique users reached by the content during the hour0 or more · optional	1050
`audience_demographics_age_18_24`	float	Percentage of audience aged 18-24 for this engagement record0 to 100 · optional	41.2
`audience_demographics_age_25_34`	float	Percentage of audience aged 25-34 for this engagement record0 to 100 · optional	32.5
`audience_demographics_age_35_44`	float	Percentage of audience aged 35-44 for this engagement record0 to 100 · optional	19.1
`audience_demographics_age_45_plus`	float	Percentage of audience aged 45+ for this engagement record0 to 100 · optional	7.2
`audience_demographics_gender_male`	float	Percentage of male audience for this engagement record0 to 100 · optional	34.7
`audience_demographics_gender_female`	float	Percentage of female audience for this engagement record0 to 100 · optional	63.3
`audience_demographics_gender_other`	float	Percentage of audience identifying as other genders for this engagement record0 to 100 · optional	2
Dates and times 1 column
`timestamp`	datetime	Date and hour when the engagement was recorded (granular to the hour)	2024-06-12T09:00:00
True or false 1 column
`is_paid_campaign`	boolean	Indicates if the engagement is part of a paid campaignoptional	true

Use it for

A marketing dashboard
The is_paid_campaign rate, engagement_count by engagement_type and a breakdown of audience_location_country. Excel, Power BI or Tableau.
Why do the 48 view rows have a mean engagement_count of 1,479?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Engagements200
ENG1-20240612-001213like
ENG2-20240612-0021205view
ENG3-20240612-00386comment
A software demo
Believable engagements with influencer_id, influencer_name and platform to fill a screen in front of a buyer.

This dataset200 rows23 columns

Yours1,000 rows23 columnsaudience_location_country: UK only

blueprint · influencer-engagement-time-series

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 23 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 represents an influencer-post event with hourly timestamp
Post engagement metrics include likes, shares, comments, and reach
Platform field restricted to top social media channels
Influencer category mapped to standardized taxonomy
Exclude bot activity and promotional spikes to focus on organic engagement

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: influencer-engagement-time-series

What should your data show?

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Sample rows

What the 200 rows show

Columns

Use it for

A marketing dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Marketing

What should your data show?