Script 151: Campaign Maturity Dimension Tagging

Purpose:

The Python script categorizes ExplorAds and Yahoo DSP campaigns into maturity labels based on their spending thresholds over the past year.

To Elaborate

The script is designed to assign maturity labels to advertising campaigns based on their spending over the previous 365 days. It specifically targets campaigns from ExplorAds and Yahoo DSP platforms. For ExplorAds campaigns, the script assigns labels such as ‘New’, ‘New - Launch’, ‘New - Round 2’, ‘New - Round 3’, ‘New - Round 4’, ‘New - Round 5’, and ‘Mature’ based on specific spending thresholds. The script uses these thresholds to determine the maturity of a campaign, with higher spending indicating a more mature campaign. The script also handles Yahoo DSP campaigns, assigning them labels like ‘New’, ‘Mature I’, and ‘Mature II’ based on similar criteria. This categorization helps in understanding the lifecycle stage of each campaign, which can be crucial for budget allocation and strategic planning.

Walking Through the Code

  1. Define Criteria for ExplorAds Tagging:
    • The script begins by setting conditions to categorize ExplorAds campaigns into different maturity labels based on their spending.
    • It checks if the campaign’s spending falls within specific ranges and whether the current maturity label is null or different from the intended label.
  2. Create DataFrames for Each Maturity Label:
    • For each maturity condition, a new DataFrame is created containing campaigns that meet the criteria.
    • The maturity label is assigned to the respective DataFrame, such as ‘New’, ‘New - Launch’, etc.
  3. Merge DataFrames:
    • The script combines all non-empty DataFrames into a single output DataFrame.
    • This merged DataFrame represents the final categorized campaigns, which are then printed or stored for further analysis.

Vitals

  • Script ID : 151
  • Client ID / Customer ID: 1306925431 / 60269477
  • Action Type: Bulk Upload (Preview)
  • Item Changed: Campaign
  • Output Columns: Account, Campaign, Campaign Maturity
  • Linked Datasource: M1 Report
  • Reference Datasource: None
  • Owner: Byron Porter (bporter@marinsoftware.com)
  • Created by Byron Porter on 2023-05-30 18:54
  • Last Updated by alejandro@rainmakeradventures.com on 2024-01-26 18:56
> See it in Action

Python Code

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#
# Campaign Maturity Dimension Tagging
#
#
# Author: Byron Porter
# Date: 2023-05-31
#
# 2023.11.09 - Removed the $125 in spend threshold for New - Launch campaign maturity label. The "New" label will no longer be used. - BP
# 2023.11.20 - Lowered spend thresholds for each campaign maturity label

# define column parameters
RPT_COL_CAMPAIGN = 'Campaign'
RPT_COL_ACCOUNT = 'Account'
RPT_COL_PUB_COST = 'Pub. Cost $'
RPT_COL_CAMP_MATURITY = 'Campaign Maturity'
BULK_COL_ACCOUNT = 'Account'
BULK_COL_CAMPAIGN = 'Campaign'
BULK_COL_CAMP_MATURITY = 'Campaign Maturity'




################################# ExplorAds Tagging ################################# 

# Create criteria for what is considered New vs Mature
new = (inputDf[RPT_COL_PUB_COST] < 100) & (inputDf[RPT_COL_ACCOUNT] == 'ExplorAds Google') & (inputDf[RPT_COL_CAMP_MATURITY].isnull())
new1 = (inputDf[RPT_COL_PUB_COST] >= 100) & (inputDf[RPT_COL_PUB_COST] < 160) & (inputDf[RPT_COL_ACCOUNT] == 'ExplorAds Google') & (inputDf[RPT_COL_CAMP_MATURITY] != 'New - Launch')
new2 = (inputDf[RPT_COL_PUB_COST] >= 160) & (inputDf[RPT_COL_PUB_COST] < 225) & (inputDf[RPT_COL_ACCOUNT] == 'ExplorAds Google') & (inputDf[RPT_COL_CAMP_MATURITY] != 'New - Round 2')
new3 = (inputDf[RPT_COL_PUB_COST] >= 225) & (inputDf[RPT_COL_PUB_COST] < 280) & (inputDf[RPT_COL_ACCOUNT] == 'ExplorAds Google') & (inputDf[RPT_COL_CAMP_MATURITY] != 'New - Round 3')
new4 = (inputDf[RPT_COL_PUB_COST] >= 280) & (inputDf[RPT_COL_PUB_COST] < 400) & (inputDf[RPT_COL_ACCOUNT] == 'ExplorAds Google') & (inputDf[RPT_COL_CAMP_MATURITY] != 'New - Round 4')
new5 = (inputDf[RPT_COL_PUB_COST] >= 400) & (inputDf[RPT_COL_PUB_COST] < 750) & (inputDf[RPT_COL_ACCOUNT] == 'ExplorAds Google') & (inputDf[RPT_COL_CAMP_MATURITY] != 'New - Round 5')
mature = (inputDf[RPT_COL_PUB_COST] >= 750) & (inputDf[RPT_COL_ACCOUNT] == 'ExplorAds Google') & (inputDf[RPT_COL_CAMP_MATURITY] != 'Mature')

# Use criteria to create new DataFrames. One for each maturity label
newDf = inputDf.loc[new, [RPT_COL_ACCOUNT, RPT_COL_CAMPAIGN, RPT_COL_CAMP_MATURITY]].copy()
newDf.loc[:, RPT_COL_CAMP_MATURITY] = 'New'

new1Df = inputDf.loc[new1, [RPT_COL_ACCOUNT, RPT_COL_CAMPAIGN, RPT_COL_CAMP_MATURITY]].copy()
new1Df.loc[:, RPT_COL_CAMP_MATURITY] = 'New - Launch'

new2Df = inputDf.loc[new2, [RPT_COL_ACCOUNT, RPT_COL_CAMPAIGN, RPT_COL_CAMP_MATURITY]].copy()
new2Df.loc[:, RPT_COL_CAMP_MATURITY] = 'New - Round 2'

new3Df = inputDf.loc[new3, [RPT_COL_ACCOUNT, RPT_COL_CAMPAIGN, RPT_COL_CAMP_MATURITY]].copy()
new3Df.loc[:, RPT_COL_CAMP_MATURITY] = 'New - Round 3'

new4Df = inputDf.loc[new4, [RPT_COL_ACCOUNT, RPT_COL_CAMPAIGN, RPT_COL_CAMP_MATURITY]].copy()
new4Df.loc[:, RPT_COL_CAMP_MATURITY] = 'New - Round 4'

new5Df = inputDf.loc[new5, [RPT_COL_ACCOUNT, RPT_COL_CAMPAIGN, RPT_COL_CAMP_MATURITY]].copy()
new5Df.loc[:, RPT_COL_CAMP_MATURITY] = 'New - Round 5'

matureDf = inputDf.loc[mature, [RPT_COL_ACCOUNT, RPT_COL_CAMPAIGN, RPT_COL_CAMP_MATURITY]].copy()
matureDf.loc[:, RPT_COL_CAMP_MATURITY] = 'Mature' 


# Merges the defined data frames, excluding those that are empty, and prints resulting outputDf
dataframes = [newDf, new1Df, new2Df, new3Df, new4Df, new5Df, matureDf]
non_empty_dataframes = [df for df in dataframes if not df.empty]

if non_empty_dataframes:
    outputDf = pd.concat(non_empty_dataframes)
    print("outputDf", tableize(outputDf))
else:
    print("Empty outputDf")
    outputDf = pd.DataFrame(columns=[RPT_COL_ACCOUNT, RPT_COL_CAMPAIGN, RPT_COL_CAMP_MATURITY])

Post generated on 2025-03-11 01:25:51 GMT

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