DataBrighten

    Sample marketing campaign data

    1,000 × 14rows × columns in the 1,000-row file

    Updated 3 November 2026. Fictional U.S. businesses and people, generated with a fixed seed.

    CSV XLSX JSON SQL
    textnumberdateyes/no
    Largest file10,000rows; also 100 and 1,000
    Columns14with a data dictionary below
    Dates2023-01-01 – 2024-12-01range in the file
    LicenceCC0synthetic, free for any use

    What is in it

    Each row is one fictional ad campaign: channel, dates, budget and actual spend, impressions, clicks, click-through rate, conversions, cost per acquisition, revenue and return on ad spend.

    First rows

    point at a column to light it up

    campaign_idtextcampaign_nametextchanneltextstart_datedateend_datedatebudgetnumberspendnumberimpressionsnumberclicksnumberctrnumberconversionsnumbercpanumberrevenuenumberroasnumber
    MC-0501Display - Loyalty - Q3 2023Display2023-09-022023-10-191578313877.613469403198710.005723259.8226971.71.94
    MC-0502Display - New Product - Q2 2023Display2023-04-122023-05-09106378170.242042560106230.005214556.3520201.742.47
    MC-0503Affiliate - Brand - Q4 2024Affiliate2024-10-142024-11-091960516958.032826338431070.015357829.3453171.733.14
    MC-0504Affiliate - Spring Sale - Q4 2023Affiliate2023-10-152023-11-011214811548.221924703208740.010835332.7133840.842.93
    MC-0505Display - New Product - Q1 2024Display2024-01-082024-02-0874396031.071507768100210.006615439.1615443.592.56
    MC-0506Paid search - Holiday - Q2 2023Paid search2023-04-202023-06-191569715972.34532411155060.029160226.5347668.832.98
    MC-0507Display - Retargeting - Q3 2024Display2024-09-132024-10-021737615660.13915025178260.004622768.9915402.730.98
    MC-0508Email - New Product - Q1 2024Email2024-03-252024-04-1099257455.12621260157200.025336020.7141323.235.54
    MC-0509Affiliate - New Product - Q2 2023Affiliate2023-04-232023-05-081495813480.092246682260590.011662321.6489658.796.65
    MC-0510Email - Clearance - Q4 2024Email2024-10-272024-11-2788047511.29625941224510.035944616.8466795.598.89

    Return on ad spend by channel

    revenue / spend, 1,000-row file

    Email5.25Affiliate4.98Paid search3.66Social2.85Display1.97Video1.92
    Show as a table
    channelvalue
    Email5.25
    Affiliate4.98
    Paid search3.66
    Social2.85
    Display1.97
    Video1.92
    Source: DataBrighten synthetic data (seed 42), computed from the file you can download here.

    Data dictionary

    ColumnTypeMeaning
    campaign_idtextCampaign number
    campaign_nametextName: channel + theme + quarter
    channeltextPaid search, Social, Display, Email, Video or Affiliate
    start_datedateStart
    end_datedateEnd, 14-60 days later
    budgetdecimalPlanned budget (USD)
    spenddecimalActual spend (USD)
    impressionsintegerAd impressions
    clicksintegerClicks
    ctrdecimalclicks / impressions
    conversionsintegerConversions
    cpadecimalspend / conversions (blank if 0)

    Practice questions

    answers checked in SQL and in Python

    Return on ad spend (revenue / spend) by channel?

    Email 5.25; Affiliate 4.98; Paid search 3.66; Social 2.85; Display 1.97; Video 1.92

    Excel

    =SUMIFS(M:M,C:C,"Email")/SUMIFS(G:G,C:C,"Email")

    SQL

    SELECT channel, ROUND(SUM(revenue)/SUM(spend),2) AS roas FROM marketing_campaigns GROUP BY channel ORDER BY roas DESC

    File: marketing-campaigns-1000

    How many campaigns overspent their budget?

    149 campaigns

    Excel

    =SUMPRODUCT(--(G2:G1001>F2:F1001))

    SQL

    SELECT COUNT(*) FROM marketing_campaigns WHERE spend > budget

    File: marketing-campaigns-1000

    Total spend and revenue?

    Spend $9,378,483.38, revenue $31,757,419.07

    SQL

    SELECT ROUND(SUM(spend),2), ROUND(SUM(revenue),2) FROM marketing_campaigns

    File: marketing-campaigns-1000