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How AI generates ad copy

Hero Marketer's ad copy generation isn't magic. This article explains roughly what's happening behind the scenes and why a few user choices matter so much for the output.

The inputs​

When you click Continue on the keywords step, Hero Marketer takes three things and combines them:

  1. Your product description and analysis. What you sell, who buys it, what jobs it does, what category it's in.
  2. The keywords from the cluster you picked. What customers are actually searching for.
  3. The destination URL and any extensions you've attached. Where ads send traffic and what auxiliary text shows.

Plus structural constraints from Google:

  • Headlines: up to 30 characters each.
  • Descriptions: up to 90 characters each.
  • A character allowance for display URL fragments.
  • Google's content policies (no excessive caps, no unverifiable claims, no trademark misuse).

What it produces​

A set of ad variations. Each variation has multiple headlines and descriptions, drafted to:

  • Address the search intent of the cluster's keywords. An ad for "alternative to jira" speaks to switching, not to first time discovery.
  • Reflect your product's specific positioning. What's distinctive, what jobs it does, what customer it's for.
  • Leave room for testing. Multiple headlines and descriptions per variation give Google's algorithm options to mix and match.

Why product description quality matters​

The single biggest lever on output quality is your product description. The AI can only write specifically about your product to the extent the description says specifically what your product does.

Thin description:

Linear is a project management tool. Easy to use and fast.

Output from this: generic ad copy that could apply to any project management tool. Headlines like "Powerful project management" and "Manage your work better".

Rich description:

Linear is a project management tool built for software teams. It replaces tools like Jira and Asana for engineers, designers, and product managers at series A through D startups, typically 20 to 200 people. The job teams hire Linear for is shipping software faster without bureaucracy. Customers describe their previous tools as slow, cluttered, and full of fields no one fills in. Linear's draw is speed, opinionated workflows, and a keyboard first interface that makes triage and status updates near friction free.

Output from this: ad copy that names actual jobs ("Ship software faster"), names competitor pain ("Faster than Jira"), and reflects positioning ("Keyboard first, built for engineering").

The richer description doesn't just produce more accurate copy. It produces copy that converts because it speaks to what real customers care about.

For guidance on writing a good description, see Describe your product.

Why we generate variations​

Google Ads runs as an auction with sophisticated machine learning underneath. Different headlines and descriptions perform differently for different queries, devices, and audiences.

By giving Google several options, you let its algorithm:

  • Match the right headline to the right query at the right time.
  • Test combinations and learn which work best.
  • Adapt as performance data accumulates.

A single hand crafted ad denies Google this flexibility. Multiple variations almost always outperform.

Why we generate keywords first, then copy​

The order matters. Keywords define intent. Copy is written to match intent.

If you wrote copy first and chose keywords later, you'd end up with mismatched campaigns: copy that doesn't speak to the actual queries triggering it. Hero Marketer goes keywords → copy because that's the order Google's auction works in (someone types a query, then Google picks an ad).

What the AI is bad at​

A few things ad copy generation doesn't do well:

  • Branding voice. If your brand has a very specific voice (Wendy's Twitter, Innocent Drinks tone), the AI's defaults won't capture it. Edit headlines manually to inject brand voice where it matters.
  • In jokes and inside references. Generic best practice prose. If your audience expects a specific cultural reference, the AI won't include it.
  • Aggressive claims. The AI defaults to defensible language. If your strategy is bold, hyperbolic copy that's still policy compliant, you'll likely want to rewrite.
  • Compliance specific copy. Legal disclaimers, regulated category language. Get a human to review for regulated categories.

For all of these: edit. The wizard supports inline edits to every headline and description. Treat the AI's output as a strong first draft, not a final.

Regeneration​

If the first set isn't right, regenerate. Each regeneration costs another credit and produces a new set with different angles.

Before regenerating, consider whether the issue is the input or the output:

  • If the description or keywords are off, fix those first. The output will follow.
  • If the description and keywords are right but the angles aren't compelling, regeneration gives you fresh angles.

A well regenerated campaign sometimes lands the right copy. A campaign with weak inputs will produce weak copy no matter how many times you regenerate.