Paid Ads: Planning and Running Google, Meta and LinkedIn Campaigns

Overview

Ad platforms now automate most bidding and much of the targeting. What stays with the advertiser decides the outcome: a target grounded in unit economics, accurate conversion signals, a structure that concentrates data, creative worth showing, and the discipline not to disturb a campaign while it learns. This skill covers those parts and gives the agent the platform limits it must respect.

Platform features change several times a year. Statements about campaign types, bid strategies and policies below were checked against the vendors' help pages; re-check the linked concepts in the current documentation before promising a specific setting exists.

Instructions

1. Gather the inputs

From the user: what is sold and its price, gross margin, how many leads or trials become customers, monthly budget, countries and languages, the landing page, past ad results, whether a customer list exists, and whether the product falls in a restricted category (housing, employment, financial products, health, politics).

From the project: the tags on the site (gtag(, a Google Tag Manager container, fbq(), the consent banner and what it does to those tags, the event fired on the conversion, and whether anything is sent server-side.

2. Check that the budget can work

Save as ads_math.py. Arguments: monthly budget, monthly price, gross margin, payback months, lead-to-customer rate, expected cost per click, landing page conversion rate.