What is the maximum population size we should target for our local Letterman publications?
Our local publications must stay within a strict population size of 20,000 to 150,000 residents to keep our target audience highly focused.
This limit keeps our communication highly specific. Our readers feel we are speaking directly to them whenever they open our weekly mailers inside Letterman.
Going after a massive city with millions of people makes it impossible to build a real relationship with local business owners. This update ends our past confusion about selecting territory sizes for our media systems.
How does exceeding the population limit damage our Facebook ads budget and targeting metrics?
Targeting a population over 150,000 people confuses the online ad system and dramatically inflates our cost per subscriber.
The online ad targeting algorithm acts like a local mail carrier who only drops flyers into specific mailboxes on a single street instead of dumping them randomly all over the state. When we keep our selection under the population cap, our customer acquisition costs stay perfectly in line.
Choosing a giant region spreads our promotional budget too thin and wastes money on people who do not care about local updates. Here's what changes for our blueprints: we pick micro-districts instead of entire cities to protect our spending.
What is the correct strategic method to break up a large metropolitan city inside Letterman?
We must divide massive target markets into smaller individual city districts before launching our sign-up pages.
For instance, instead of covering all of Brooklyn or Detroit, we can use ChatGPT to help us list the small individual districts inside those zones. The practical impact is we can build separate sister publications for different sections of our area over time.
Chad recommends starting in our own backyard with the single micro-region we know best. This method allows us to easily join local groups and handle community outreach, unlocking a steady path to scale our business safely without drowning in excessive back-end labor.
