Purpose:

The Python script automatically tags marketing campaigns with a service dimension based on the campaign name.

To Elaborate

The script is designed to automate the process of tagging marketing campaigns with a specific service dimension. This is achieved by analyzing the campaign names and assigning a service category based on predefined keywords. The script processes data from a primary data source, identifies campaigns related to specific services like ‘Dental Implants’ or ‘Invisalign’, and tags them accordingly. This helps in organizing and categorizing campaigns for better analysis and reporting, ensuring that each campaign is associated with the correct service type.

Walking Through the Code

1. Data Initialization
   • The script begins by setting up the primary data source, inputDf, which contains information about campaigns, including their names and statuses.
   • It defines constants for the column names used in the data processing, such as ‘Campaign’, ‘Account’, ‘Service’, and ‘Campaign ID’.
2. Service Tagging Function
   • A function named tag_service is defined to determine the service category based on the campaign name.
   • The function checks if the campaign name contains specific keywords (‘Implantes’ or ‘Invisalign’) and returns the corresponding service name (‘Dental Implants’ or ‘Invisalign’). If no keywords are found, it returns an empty string.
3. Applying the Function
   • The tag_service function is applied to each campaign name in the input data frame (inputDf) to populate the ‘Service’ column in the output data frame (outputDf).
   • This step effectively tags each campaign with the appropriate service dimension.
4. Result Preview
   • The script concludes by printing a preview of the first few rows of the output data frame, allowing users to verify the tagging results.

Vitals

• Script ID : 1399
• Client ID / Customer ID: 1306927943 / 60270393
• Action Type: Bulk Upload
• Item Changed: Campaign
• Output Columns: Account, Campaign, Service, Campaign ID
• Linked Datasource: M1 Report
• Reference Datasource: None
• Owner: dwaidhas@marinsoftware.com (dwaidhas@marinsoftware.com)
• Created by dwaidhas@marinsoftware.com on 2024-09-18 19:17
• Last Updated by dwaidhas@marinsoftware.com on 2024-09-18 21:37

> See it in Action

Python Code

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
##
## name: Auto Tag Campaigns with Service Dimension 
## description:
##  
## 
## author: Dana Waidhas 
## created: 2024-09-18
## 

today = datetime.datetime.now(CLIENT_TIMEZONE).date()

# primary data source and columns
inputDf = dataSourceDict["1"]
RPT_COL_CAMPAIGN = 'Campaign'
RPT_COL_ACCOUNT = 'Account'
RPT_COL_SERVICE = 'Service'
RPT_COL_CAMPAIGN_ID = 'Campaign ID'
RPT_COL_CAMPAIGN_STATUS = 'Campaign Status'

# output columns and initial values
BULK_COL_ACCOUNT = 'Account'
BULK_COL_CAMPAIGN = 'Campaign'
BULK_COL_SERVICE = 'Service'
BULK_COL_CAMPAIGN_ID = 'Campaign ID'

# Function to tag Service based on campaign name
def tag_service(campaign_name):
    if 'Implantes' in campaign_name:
        return 'Dental Implants'
    elif 'Invisalign' in campaign_name: 
        return 'Invisalign'
    else:
        return ''

# Apply the function to each campaign
outputDf[BULK_COL_SERVICE] = inputDf[RPT_COL_CAMPAIGN].apply(tag_service)

# Preview the result
print(tableize(outputDf.head()))

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