How to Monitor Your Competitors' Ads Automatically (Google, LinkedIn and Bing) with Apify

When a competitor launches a new ad campaign, it often appears first in their advertisements. Google, LinkedIn, and Microsoft all provide public ad libraries that show who is advertising and what they are running. However, these libraries do not offer a way to automatically notify you of new ads, which is where automation comes in handy. This guide explains how to set up an automated feed of new competitor ads delivered daily to Slack or email, as well as how to analyze the data using Python and pandas.

The tutorial covers building a daily job that checks competitors on Google (Search, Display, YouTube), LinkedIn, and Bing, producing output containing only ads that appeared since the previous run. Alerts can be set up in Slack or email, or via a webhook into Zapier, Make, or n8n. A small Python script is also provided to collect the results and count new ads per competitor per week.

Ad transparency libraries exist to ensure the public can see who is paying for ad placements. Europe's Digital Services Act (DSA) primarily drives this transparency, requiring LinkedIn and Microsoft to publish run dates, reach, and targeting for ads shown in the EU. These libraries are the most reliable public source of competitor creative, as platforms publish the data themselves.

Three Apify actors are used in this guide: Google Ads Transparency Scraper & New Ads Monitor, LinkedIn Ad Library Scraper & New Ads Monitor, and Bing / Microsoft Advertising Ads Library Scraper & Microsoft Ads Monitor. Each actor wraps one library and follows the same conventions, including an "Only new ads" mode that stores ads seen previously in a named key-value store on your Apify account. On later runs, the actors output only the ads they have not seen before.

To get started, create an Apify account (free plan includes monthly platform credit) and open the actor page. Click "Try for free," switch the input editor to JSON, paste an input, and click "Start." When the run finishes, open the Output tab and export the data as JSON, CSV, or Excel.