CTtheDisrupter simplifies dashboard metrics
- Charley T, who posts as CTtheDisrupter, urged advertisers to strip Meta dashboards to a few decision metrics instead of tracking dozens of columns. - His core setup centers on cost per acquisition, average order value, return on ad spend, and GPT, or gross profit per transaction. - The pitch matches his broader “profit over ROAS” teaching across Disrupter Academy and YouTube. (youtube.com)
Charley T, the marketer behind CTtheDisrupter, is telling media buyers to cut their dashboards down to a handful of numbers that actually change spending decisions. (youtube.com) (tiktok.com) The short version is simple: stop staring at crowded Meta Ads Manager views and track cost per acquisition, average order value, return on ad spend, and GPT, his shorthand for gross profit per transaction. (tiktok.com) (youtube.com) GPT is the number he keeps returning to. In Charley T’s framing, it is average order value minus cost per acquisition, a custom column that shows how much gross profit each sale leaves after ad cost. (tiktok.com) (youtube.com) That changes what a “good” ad looks like. A campaign with a higher acquisition cost can still be the better buy if it brings in larger baskets and leaves more profit per order. (youtube.com 1) (youtube.com 2) Charley T has been pushing that argument across longer trainings, not just in one social post. In a six-month-old YouTube livestream, he told viewers to optimize for “true profit” and said custom metrics such as GPT and profit volume help buyers decide where to scale. (youtube.com) He makes the same case in a recent ad-account audit, where he said one ad was losing about $100 per sale while another could “double profits overnight” once the account was read through a GPT lens. (youtube.com) The broader pitch is that simpler dashboards create cleaner signals for operators. Disrupter Academy’s course materials pair GPT with a small set of other readings — spend, frequency, cost per thousand impressions, and cost per result — instead of sprawling reports. (youtube.com) That approach also lines up with a practical problem inside ad platforms: a high return on ad spend can still mask weak unit economics if margins are thin, shipping is expensive, or customers buy low-value products. (triplewhale.com) (fullycounted.com) So the explainer here is less about a new formula than a reporting habit. Charley T’s message is to remove columns that do not trigger a decision and keep the ones that tell you whether each sale is actually worth buying. (tiktok.com) (youtube.com)