Target the Gaze, Not the Demographic

  • We used Google Ads, YouTube pre-rolls, Facebook, and Instagram ad placements styled as “gift ideas” or “surprise her” clickbait—tactically aimed at the male gaze. Because men don’t search “buy lingerie,” they click “10 sexy gifts she’ll love (but you’ll enjoy more).”

  • That language shift? It’s the difference between a 1.3% CTR and a 6.9% CTR.
    (Nice.)

Machine Learning Sorted the Pretenders from the Purchasers

  • Using AWS SageMaker, we trained models to identify behavioral signals of actual buyers. It wasn’t just about clicks—it was about:

    • Bounce rates

    • Scroll depth

    • Repeat views

    • Purchase velocity on other “giftable” items

    SageMaker processed those signals and flagged the high-intent window shoppers—those who weren’t just curious, but had their American Express ready and Apple Pay primed.

Retargeting That Didn’t Feel Like Retargeting

  • We piped those ML segments into AdRoll, dynamically generating retargeting ads based on previous ad copy that hit hardest. If “For her (but really, for you)” worked, that guy saw three versions of it—each slightly tuned to his behavior.

  • One for desktop. One for mobile. One for Instagram, with a 5-second reel and a bold CTA that practically read: “Click this or live in regret.”

From Click to CRM in One Pipeline

    • New click → model scored it

    • Score passed to AdRoll and the custom CRM

    • Personalized drip sequence launched based on score via Amazon Pinpoint or Klaviyo

      From there, we used AWS Lambda and Amazon EventBridge to handle event-based automation:The CRM was enriched with demographic, purchase history, and click-pattern metadata. Translation: when Chad clicked three different “Buy her a gift” links but never checked out, we didn’t guess what to do next—we knew.

The Stack Behind the Seduction

The full tech stack turned thirsty clicks into predictable revenue, all while maintaining security and scale:

  • AWS SageMaker – behavior prediction, ad scoring

  • Amazon S3 – storing ad engagement logs + campaign variants

  • AWS Lambda – compute for real-time triggers

  • Amazon EventBridge – orchestrating user behavior flows

  • Amazon Pinpoint – SMS/email automation, segmentation

  • Amazon DynamoDB – storing structured user behavior and CRM tagging

  • Amazon CloudWatch – for keeping tabs on performance in real-time

So no, it wasn’t about lace.

It was about algorithms, trained to spot a man on the edge of emotional justification. We didn’t make him want to buy. We just made it easy for him to believe it was his idea.

Ready to turn human nature into ad conversion? Let’s go.