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Targeted Marketing Strategy with Facebook Ads

Facebook Ads Campaign

I developed a Python script to scrape publicly available data from a government website, collecting hundreds of postal codes into a raw text file. This data was then strategically used in a Facebook ad campaign to target specific locations. The campaign was highly successful, resulting in an influx of phone calls and new clients for the law firm within just a few days.

Background

A law firm sought to efficiently connect with potential class action participants. Demographic research identified key geographic areas with eligible individuals. Traditional marketing methods lacked the precision needed to reach these communities effectively, prompting the need for a data-driven approach to engage the most relevant locations.

Project Objectives

  • Use a Python script to collect relevant geographic information.
  • Ensure collected postal codes were formatted correctly for Facebook Ads as they were added to a raw data file.
  • Implement targeted Facebook advertising campaigns using the collected data.
  • Maximize return on ad spend through precise geographic targeting.

Project Challenges

The main challenge was to efficiently collect and process large volumes of publicly available geographic data from government websites to identify potential client locations. This required developing a custom Python script that could accurately scrape and format postal code data for marketing use.

  • Design and implement an efficient web scraping solution.
  • Process and clean hundreds of postal codes for marketing use.
  • Integrate the data with Facebook's advertising platform.
  • Optimize ad targeting parameters for maximum reach.
  • Track and measure campaign performance metrics.

Solutions

To achieve targeted client acquisition, I developed a custom Python-based web scraping solution to gather postal codes and incorporated them into Facebook ads. This strategic use of location data enabled precise geographic targeting, contributing to significant client growth for the law firm.

Key solutions implemented:

  • Automated Data Collection: Developed a Python script to efficiently scrape and extract postal codes from government websites, ensuring comprehensive geographic coverage.
  • Data Processing Pipeline: Created a straightforward solution where the collected postal codes were added to a raw text file formatted to match Facebook Ads requirements.
  • Geographic Targeting: Implemented strategic location-based targeting through Facebook's advertising platform using the processed data.
  • Campaign Optimization: Fine-tuned ad targeting parameters and audience settings to maximize reach within specific postal codes.

Tech Stack:

  • Python Logo
  • Facebook Ads Logo
  • Google Analytics Logo

Results

The targeted advertising campaign delivered exceptional results, significantly increasing client acquisition and demonstrating the effectiveness of data-driven geographic targeting.

Rapid Client Acquisition

The law firm experienced an immediate surge in client inquiries, with phones ringing consistently during the first few days of the campaign launch, leading to multiple new client acquisitions.

Precise Geographic Targeting

Successfully identified and targeted hundreds of relevant postal codes, ensuring ad spend was focused exclusively on areas with high potential for client acquisition.

Efficient Data Collection

The automated scraping solution successfully processed and collected data from government websites, creating a comprehensive database of target locations that could be easily updated and maintained.

Optimized Ad Performance

The targeted approach led to highly efficient ad spend, with the campaign delivering strong engagement rates and conversions within the specifically targeted geographic regions.

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