Influencer Campaign Performance Data
This dataset provides granular, campaign-level performance metrics for influencer marketing initiatives, including engagement, conversion, audience reach, and demographic insights. Marketers can analyze ROI, optimize future campaigns, and benchmark influencer effectiveness across platforms and content types. The dataset is ideal for strategic planning, reporting, and cross-campaign comparisons.
Sample rows
preview · 8 of 200 rows · all 24 columns| campaign_idstring | content_typestring | conversionsinteger | audience_demographics_location_countrystring | campaign_namestring | brand_namestring | influencer_idstring | influencer_handlestring | platformstring | campaign_start_datedate | campaign_end_datedate | content_idstring | content_publish_datedatetime | audience_reachinteger | engagementsinteger | engagement_ratefloat | clicksinteger | conversion_ratefloat | roifloat | campaign_budgetfloat | currencystring | audience_demographics_genderstring | audience_demographics_age_groupstring | audience_demographics_location_citystring |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| CAMP001 | Reel | 570 | United States | Spring Style Launch | Urban Vogue | INF1001 | @ | 2024-03-01 | 2024-03-30 | CNT001 | 2024-03-05T14:00:00 | 58000 | 9280 | 16 | 2400 | 23.75 | 3.2 | 18000 | USD | Female | 25-34 | New York | |
| CAMP002 | Video | 820 | United States | Tech Trends 2024 | GadgetHub | INF1002 | @ | YouTube | 2024-02-10 | 2024-03-05 | CNT002 | 2024-02-15T18:30:00 | 104000 | 7800 | 7.5 | 6500 | 12.62 | 2.1 | 42000 | USD | Male | 25-34 | San Francisco |
| CAMP003 | Story | 28 | United States | Wellness for Women | BrightLife | INF1003 | @ | 2024-01-20 | 2024-02-10 | CNT003 | 2024-01-22T09:00:00 | 8300 | 950 | 11.45 | 210 | 13.33 | 0.9 | 1500 | USD | Female | 45-54 | Miami | |
| CAMP004 | Post | 280 | Germany | Eco Living Challenge | GreenSteps | INF1004 | @ | TikTok | 2024-03-15 | 2024-04-05 | CNT004 | 2024-03-16T20:00:00 | 17500 | 5600 | 32 | 1400 | 20 | 2.7 | 6000 | EUR | Mixed | 18-24 | Berlin |
| CAMP005 | Story | 400 | France | Global Luxury Watches | Timepiece Elite | INF1005 | @ | 2024-02-25 | 2024-03-28 | CNT005 | 2024-02-26T12:00:00 | 310000 | 14500 | 4.68 | 3500 | 11.43 | 0.8 | 65000 | EUR | Female | 35-44 | Paris | |
| CAMP006 | Post | 82 | United States | Fresh Bites Launch | PureTaste | INF1006 | @ | 2024-03-10 | 2024-03-25 | CNT006 | 2024-03-12T11:00:00 | 9800 | 2940 | 30 | 490 | 16.73 | 3.9 | 1700 | USD | Female | 25-34 | Austin | |
| CAMP007 | Story | 120 | United States | Yoga for Mindfulness | ZenFlow | INF1007 | @ | 2024-02-01 | 2024-02-28 | CNT007 | 2024-02-05T08:30:00 | 14500 | 3120 | 21.52 | 650 | 18.46 | 2.2 | 2500 | USD | Female | 25-34 | Los Angeles | |
| CAMP008 | Post | 5 | United States | Senior Living Wellness | Golden Years | INF1008 | @ | 2024-01-15 | 2024-02-06 | CNT008 | 2024-01-18T10:00:00 | 2600 | 210 | 8.08 | 30 | 16.67 | 0.6 | 300 | USD | Female | 55+ | Tampa | |
| CAMP009 | Reel | 350 | Japan | Luxury Tokyo Trends | Sakura Couture | INF1009 | @ | 2024-03-01 | 2024-03-31 | CNT009 | 2024-03-04T13:00:00 | 225000 | 9500 | 4.22 | 4200 | 8.33 | 1.1 | 48000 | JPY | Mixed | 25-34 | Tokyo | |
| CAMP010 | Story | 370 | Australia | Travel Challenge Sydney | Go Explore | INF1010 | @ | 2024-03-10 | 2024-04-01 | CNT010 | 2024-03-13T16:00:00 | 42000 | 8200 | 19.52 | 1100 | 33.64 | 4.7 | 9500 | AUD | Male | 18-24 | Sydney | |
| CAMP011 | Reel | 340 | India | Fitness Motivation India | MoveUp | INF1011 | @ | TikTok | 2024-02-15 | 2024-03-10 | CNT011 | 2024-02-17T10:00:00 | 17000 | 5300 | 31.18 | 1100 | 30.91 | 3.2 | 2800 | INR | Mixed | 18-24 | Mumbai |
| CAMP012 | Story | 120 | France | Luxury Watches Paris | ChicTime | INF1012 | @ | 2024-03-01 | 2024-03-30 | CNT012 | 2024-03-02T14:00:00 | 120000 | 4200 | 3.5 | 2000 | 6 | 0.6 | 43000 | EUR | Female | 35-44 | Paris | |
| CAMP013 | Reel | 610 | United Kingdom | Fashion Forward London | Modish | INF1013 | @ | 2024-02-10 | 2024-03-01 | CNT013 | 2024-02-13T15:00:00 | 81000 | 13700 | 16.91 | 3200 | 19.06 | 3.7 | 21000 | GBP | Mixed | 25-34 | London | |
| CAMP014 | Story | 380 | United States | Active Living Challenge | LifeRun | INF1014 | @ | 2024-03-06 | 2024-03-27 | CNT014 | 2024-03-08T09:00:00 | 42000 | 9500 | 22.62 | 1020 | 37.25 | 4.2 | 9500 | USD | Female | 25-34 | Chicago | |
| CAMP015 | Post | 98 | Netherlands | Foodie Finds Amsterdam | TasteTrail | INF1015 | @ | 2024-02-15 | 2024-03-05 | CNT015 | 2024-02-17T13:00:00 | 10500 | 2650 | 25.24 | 340 | 28.82 | 3.3 | 1200 | EUR | Female | 25-34 | Amsterdam | |
| CAMP016 | Video | 310 | United States | Tech for Teens | ByteBoost | INF1016 | @ | YouTube | 2024-03-01 | 2024-03-20 | CNT016 | 2024-03-02T15:00:00 | 55000 | 6200 | 11.27 | 2100 | 14.76 | 2.4 | 9000 | USD | Male | 13-17 | Seattle |
| CAMP017 | Post | 18 | United Kingdom | Wellness Manchester | FeelGood | INF1017 | @ | 2024-02-04 | 2024-02-25 | CNT017 | 2024-02-07T11:00:00 | 5200 | 420 | 8.08 | 75 | 24 | 0.7 | 800 | GBP | Female | 45-54 | Manchester | |
| CAMP018 | Story | 353 | Germany | Fitness Challenge Berlin | ActiveEdge | INF1018 | @ | TikTok | 2024-03-05 | 2024-03-26 | CNT018 | 2024-03-08T11:30:00 | 16800 | 4760 | 28.33 | 1370 | 25.77 | 3.5 | 5500 | EUR | Male | 18-24 | Berlin |
| CAMP019 | Reel | 260 | Italy | Taste of Milan | BelloCibo | INF1019 | @ | 2024-02-20 | 2024-03-15 | CNT019 | 2024-02-21T19:00:00 | 26000 | 6300 | 24.23 | 800 | 32.5 | 2.9 | 3100 | EUR | Female | 25-34 | Milan | |
| CAMP020 | Post | 4 | United States | Senior Health Austin | VitalCare | INF1020 | @ | 2024-01-18 | 2024-02-10 | CNT020 | 2024-01-20T08:00:00 | 1800 | 160 | 8.89 | 20 | 20 | 0.5 | 200 | USD | Female | 55+ | Austin |
What the 200 rows show
from the 200-row sampleOther (content type) stands out: mean conversions is 3.9, against 533.4 for the rest.
- 351.5median conversions
- 4audience demographics genders
- 6platforms
- 7currencies
- 8audience demographics age groups
- 24audience demographics location cities
Median 351.5, from 0 to 2,150.
- string 13
- integer 4
- float 4
- date 2
- datetime 1
Columns
24 columns in three groups| column | type | description | example |
|---|---|---|---|
| Text 13 columns | |||
campaign_id | string | Unique identifier for the influencer marketing campaignunique | CAMP001 |
campaign_name | string | Descriptive name of the campaign | Spring Style Launch |
brand_name | string | Name of the brand running the campaign | Urban Vogue |
influencer_id | string | Unique identifier for the influencer | INF1001 |
influencer_handle | string | Social media handle or username of the influencer | @ |
platform | string | Social media platform where the campaign was run (e.g., Instagram, TikTok, YouTube)6 values | |
content_id | string | Unique identifier for the specific content piece (post, video, etc.) | CNT001 |
content_type | string | Type of content created (e.g., post, story, video, reel)Post · Story · Video · Reel · Other | Reel |
currency | string | Currency code for campaign budget (e.g., USD, EUR)7 currencies · optional | USD |
audience_demographics_gender | string | Dominant gender of the audience (e.g., Male, Female, Mixed)Male · Female · Mixed · Unknown · optional | Female |
audience_demographics_age_group | string | Dominant age group of the audience (e.g., 18-24, 25-34)7 values · optional | 25-34 |
audience_demographics_location_country | string | Dominant country of the audience12 countries · optional | United States |
audience_demographics_location_city | string | Dominant city of the audienceoptional | New York |
| Numbers 8 columns | |||
audience_reach | integer | Number of unique users who saw the content0 or more | 58000 |
engagements | integer | Total number of engagements (likes, comments, shares, etc.)0 or more | 9280 |
engagement_rate | float | Engagement rate as a percentage (0-100)0 to 100 | 16 |
clicks | integer | Number of clicks on links or call-to-action elements in the content0 or more · optional | 2400 |
conversions | integer | Number of completed desired actions (e.g., purchases, sign-ups) attributed to the content0 or more · optional | 570 |
conversion_rate | float | Conversion rate as a percentage (0-100)0 to 100 · optional | 23.75 |
roi | float | Return on investment for the campaign (percentage or ratio)optional | 3.2 |
campaign_budget | float | Total budget allocated for the campaign (in USD)0 or more · optional | 18000 |
| Dates and times 3 columns | |||
campaign_start_date | date | Date when the campaign started | 2024-03-01 |
campaign_end_date | date | Date when the campaign ended | 2024-03-30 |
content_publish_date | datetime | Date and time when the content was published | 2024-03-05T14:00:00 |
Use it for
A marketing dashboard
Conversions by content_
type and a breakdown of audience_ demographics_ location_ country. Excel, Power BI or Tableau. Why do the 36 Other rows have a mean conversions of 3.9?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Campaigns200CAMP001570ReelCAMP002820VideoCAMP00328Story
A software demo
Believable campaigns with campaign_
name, brand_ name and influencer_ id to fill a screen in front of a buyer.
This dataset200 rows24 columns
Yours1,000 rows24 columnsaudience_demographics_location_country: UK only
blueprint · influencer-campaign-performance-data
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
- Record influencer ID and campaign
- Track engagement and conversion rates
- Flag top-performing campaigns
- Exclude non-promotional posts
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-campaign-performance-data