Client Background

Client: A leading Marketing firm in the USA

Industry Type:  Marketing

Services: Marketing consulting

Organization Size: 100+

Project Objective

Upload daily data from Google Local Service Ads dashboard to BigQuery database.

Project Description

  • Extracts data from LSA dashboard for the last 24 hours.
  • The data is uploaded to BigQuery database “lsa_lead_daily_data”
  • The script runs every morning and is deployed to Heroku by the name “lead-details-to-db”.
  • The data is collected only for the companies that are not marked in red in the “Missed Messages Notification Automation – Master File” sheet.
  • The following data is uploaded:
    • Number of Leads
    • Cost Per Lead
    • Lead Type
    • Dispute amount to be approved
    • Dispute amount approved
    • Cost per Call

Our Solution

  • Use LSA API to extract data.
  • Clean the data to make it readable and dispose the data not needed.
  • Upload data to a BigQuery database everyday at a fixed time.
  • Deploy to Heroku to run the script everyday.

Project Deliverables

A working deployed automated tool that runs everyday in the morning hours and uploads a report to database. Tool is monitored everyday. 

Tools used

Heroku

LSA API

BigQuery API

Sheets API

Language/techniques used

Python

Skills used

Data extraction, cleaning and summarising

Databases used

BigQuery –  lsa_lead_daily_data

Web Cloud Servers used

Heroku

What are the technical Challenges Faced during Project Execution

Making sure that the data uploaded is for the right company.

How the Technical Challenges were Solved

Monitoring daily logs and uploads for some time and making sure data was correct

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