The challenge
AMD needed to activate real purchase intent and convert traffic into measurable sales across multiple retailers without depending on intermediate landing pages that would slow the user down. The problem was not reach. The problem was signal quality: how to distinguish people who merely saw a product message from people showing high-intent retailer behavior.
In consumer technology, media can create a lot of apparent engagement that never becomes retail demand. Pretty dashboards. Weak sell-through. A classic crime scene.
The system
The solution was a performance architecture centered on the Click eTailer event as a proxy for high purchase intent. Instead of optimizing only for shallow traffic, the system prioritized users moving toward retailer environments where product comparison and purchase behavior could happen.
1. Intent signal definition
The Click eTailer event became the operating signal. It translated paid media activity into a more commercially meaningful action: a user choosing to move from campaign exposure into a retail context.
2. Full-funnel paid architecture
- TikTok Smart+ campaigns optimized for conversion among in-market audiences.
- Meta Advantage+ and lookalikes built from users with demonstrated intent history.
- Google Display and YouTube used for scaled prospecting and product-context education.
3. UGC-style product clarity
Creative was produced to make the product decision easier: clear use cases, direct benefit framing, real context, and fast comprehension. The goal was not to make tech look shiny. It was to help buyers understand why they should click toward a retailer.
The results
The system generated 154K high-intent Click eTailer actions, a +152% year-over-year increase, while reducing CPL by 33%. Investment scaled +62% YoY while maintaining efficiency, and unit sales grew +43% YoY, representing 25,902 additional units.
Operating lesson: if the conversion environment lives in retail, the campaign signal cannot stop at the ad click. The optimization target needs to approximate commercial intent as closely as the available data allows.
Why it matters
This case is a clean example of the difference between media optimization and revenue-system design. A media team might optimize for CPC, CTR, or landing-page traffic. A revenue system asks: which signal is closest to commercial value, how do we optimize toward it, and how do we keep the creative loop tied to that signal?
Reusable pattern
The AMD model applies to brands where the final purchase happens outside the brand's owned site: retail, marketplaces, dealer networks, distributors, app stores, or offline points of sale.