Dataset, Jembatan Legal Explaining WhatsApp Lead Generation from Meta Ads Campaigns Using Interpretable Machine Learning

This dataset contain Meta Ads campaign performance data from Jembatan Legal, an Indonesian legal service provider that focus on business legal services such as PT (Perseroan Terbatas), CV (Commanditaire Vennootschap), and PT Perorangan establishment. The data is collected from Meta Ads platform reports across multiple advertising campaign run during specific period, with more than a hundred campaign observations.
Each observation represent one unit of advertising campaign activity and include various performance metric, namely: Age, Gender, Amount Spent (IDR), Impressions, Reach, Link Clicks, CPC (Cost Per Click), CPM (Cost Per 1,000 Impressions), CTR (Click-Through Rate), Post Engagements, Post Reactions, Post Comments, Post Saves, Post Shares, Page Engagement, 3-second Video Plays, Video Average Play Time, and New Messaging Contacts.
The target variable is New Messaging Contacts, that represent the number of potential customer who contacted the company via WhatsApp after seeing the advertisement. This dataset is used to identify which Meta Ads performance metric is most predictive of customer communication via WhatsApp, using decision tree classification approach.
The dataset can be used for research in digital marketing, social media advertising effectiveness, lead generation, and machine learning application in business analytics, particularly in the context of SME in developing country.