ikaadil/digital-advertisement-attribution-analytics

The repository includes various analytics techniques and models that can be used to identify which campaigns are generating the most traffic, leads, and conversions. Additionally, the repository also provides various data visualization tools that can be used to create reports and dashboards to monitor the performance of digital advertising campaign

digital-advertisement-attribution-analytics

Features

• Add signup event
• Get distinct user count since time
• Add pageview event
• Get analysis which contain pageview count and successfull advertisement count

Installation

It requires Python3, pipenv to run. Install the dependencies

pipenv shell
python app.py

Api

Add event: POST http://127.0.0.1:5000/event

Payload

{
  "name": "signup",
  "fingerprint": "b998efcb-1af3-4149-9b56-34c4482f6691",
  "user_id": "5566bd0538665441d6ad80011",
  "created_at": "2021-01-02 12:33:41.127641"
}

Response

{
    "status": "successfully added"
}

Get distinct user count since a date time

GET http://127.0.0.1:5000/event?date_time=2023-02-01

Response

{
    "number_of_unique_user": "10"
}

Add pageview event

POST http://127.0.0.1:5000/pageview

Payload

{
  "fingerprint": "b998efcb-1af3-4149-9b56-34c4482f6691",
  "user_id": null,
  "url": "https://www.company.com/en/library",
  "referrer_url": "https://www.google.com",
  "created_at": "2023-01-01 12:33:41.127641"
}

Response

{
    "status": "successfully added"
}

Get analysis

GET http://127.0.0.1:5000/pageview?date_time=2022-02-06&show_succeeded_ad=true

Response

{
  "pageview_count": [
    {
      "null": 1
    },
    {
      "facebook": 1
    },
    {
      "google": 3
    }
  ],
  "succeeded_ad_count": [
    {
      "null": 1
    },
    {
      "google": 1
    }
  ]
}

Here null means direct visit