Competitor ad research: a playbook or a daily pipeline

The job is finding ads that are already working — by keyword and market — and getting them in front of the person who writes the next one.

It is easy to turn that into a product tour. Consultancy starts smaller. How many ads does someone actually open today. Which libraries they already have login to. What “winning” means in their mouth (days running, upload velocity, a hunch). Where the file has to land: Slack, a sheet, an editor’s queue.

When a playbook is the honest answer

If one buyer already knows the three accounts that matter, and they check them twice a week, a written habit plus a shared folder is enough. A pipeline would add login risk and a feed nobody reads.

If several people spend half a day hunting the same libraries, and they still miss geography or a keyword, then collection is the job. The competition spy automation case study is that slice: pull from the libraries you name, score, bundle by topic, drop into Slack. The desk still decides what to shoot.

We will not call a dump of three hundred videos a strategy. We will ask who is paid to watch them.

When the job is a product, not a script

If you need search, history, transcripts, and more than one buyer in the same wall, that is a different scope. Spying Agent is the product-shaped version of the same research job. We will not start there on a first call unless you already know you want a login and a wall, not a morning Slack.

Sequence matters. AI consultancy writes the job. Automation or a product build comes after the desk can say what they will ignore.

Bring last week’s research folder or Slack channel. Book thirty minutes or write hello@jamilglobal.com.