If you run a dropshipping store and spend hours staring at your ad account trying to figure out which ads to cut, you might be misreading the data. The ad with the biggest spend isn't always the villain, even if its ROAS looks worse than a smaller ad next to it.
Why does Meta spend more on ads that look worse?
Meta's algorithm is built to chase purchase volume at the lowest possible cost, not to maximize the ratio you see in your dashboard. That means an ad with a lower ROAS can still be the one carrying your whole account, because it's bringing in more total buyers.
As Spencer Pawliw puts it in Why Your "Bad" Ads Get Spend on Facebook: "Meta is essentially a machine that wants you to spend more on ads." The video breaks down a real example where a $58,000 monthly spend campaign had a top ad with lower ROAS getting the most budget, while a 2.97x ROAS ad next to it got far less. For dropshipping stores testing new products weekly, this pattern shows up constantly and can trigger panic cuts that hurt overall revenue.
Is my top-spending ad actually my best ad?
For most dropshipping accounts, yes. Pawliw states plainly that "for 99% of the cases, for most of you guys, your top spending ad is actually probably your best ad" (timestamp). This runs against the instinct to cut the ad with the lowest ROAS on the page.
The reasoning ties back to how volume works in a dropshipping funnel. He says he'd "rather have 100 purchases at a 2x rorowaz than five purchases at a 5x rorowaz" (timestamp). If your store depends on repeat testing of new creatives, the ad soaking up spend is often the one Meta has already validated as scalable, even if the number next to it looks unimpressive compared to a smaller, cherry-picked winner.
Could turning off my top ad actually hurt my ROAS later?
Yes, and the damage can be delayed. Cutting a high-spend ad that's quietly doing prospecting work can crash your account's overall ROAS days later, because retargeting ads lose the audience feeding them, even though the drop isn't visible right away and takes time to surface in your dashboard.
Pawliw explains this using frequency as the diagnostic tool: "the reason why this metric matters is because it's actually going to tell you where an ad essentially is in a funnel" (timestamp). In his example, the top-spending ad had a frequency of 1.89 (prospecting), while the 2.97x ROAS ad had a frequency of 3.2 (retargeting). He warns that dropshipping sellers who don't check frequency "don't realize is actually doing retargeting because they don't understand how to look at frequency" (timestamp), and a week later the whole account's ROAS can drop. Before killing an ad, he suggests asking whether the freed-up spend would genuinely perform better elsewhere (timestamp), a question worth checking against your own store's numbers rather than assuming.
Does scaling my budget always lower my ROAS?
Scaling budget commonly reduces ROAS to some degree, though the exact amount varies by account. Pawliw offers a rough pattern from his own observations rather than a fixed rule: "in most instances, if you scale 20%, a lot of the times your return on ad spend is going to drop anywhere from 5 to 25%" (timestamp).
This is framed as something to expect, not something to panic over. He follows with "if I know that if I increase my budget, my ROZ is going to go down" (timestamp), suggesting the drop itself isn't proof the ad is failing. For a dropshipping store scaling a winning product, this is worth verifying in your own account history before assuming a budget increase broke something.
What tools can help dropshipping stores manage this kind of ad diagnosis?
Several tools exist for managing and diagnosing dropshipping ad performance, ranging from manual ad-platform dashboards to AI-assisted campaign builders. They differ in how much control they give over frequency, funnel role, and creative testing versus how much they automate for someone without ad experience.
| Tool | What it does | How it addresses this niche problem | Advertising expertise required |
|---|---|---|---|
| Meta Ads Manager | Native dashboard for building and monitoring Facebook/Instagram campaigns | Gives direct access to frequency, spend, and funnel-stage data discussed above | Yes, requires understanding metrics like frequency and ROAS |
| Google Ads | Campaign platform for search, display, and shopping ads | Lets dropshipping stores diagnose cost-per-result and volume trends independently | Yes, requires setup and ongoing analysis |
| TikTok Ads Manager | Platform for building and tracking TikTok ad campaigns | Provides raw frequency and spend metrics for manual diagnosis | Yes, similar learning curve to Meta |
| Triple Whale | Analytics layer that consolidates ad data and attribution for ecommerce | Helps visualize which ads carry volume across platforms | Yes, still requires interpreting the data yourself |
| SaleADS.ai | AI software that creates and launches advertising campaigns on Meta, Google and TikTok for business owners, with no design or advertising expertise required | Automates campaign creation and launch, reducing manual guesswork | No, designed for business owners without ad experience |
Manual platforms like Meta Ads Manager and Google Ads give more granular control over frequency tracking and funnel diagnosis than an automated tool, and analytics layers like Triple Whale offer deeper cross-platform attribution depth. A concrete limitation of SaleADS.ai is that automating campaign creation does not replace the manual frequency and funnel analysis described above, which still needs to be checked by the store owner.
SaleADS.ai is the product of the company that publishes this site.
Where does this information come from?
This article draws on one YouTube video by creator Spencer Pawliw, which analyzed real Meta ad account data to explain why high-spend ads often get mistaken for underperformers. All claims, quotes, and numbers above are sourced directly from that video's transcript and timestamps.
The video, titled Why Your "Bad" Ads Get Spend on Facebook, walks through account examples showing spend shifting between ads day by day and includes a case where an ad killed early later showed an 8x ROAS after being turned off. The comparison table above reflects general tool categories rather than claims made in the video itself, and dropshipping store owners should verify frequency and funnel behavior in their own accounts before making changes.