Hi there,
Thanks for reaching out. Happy to give you some initial thoughts and guidance on how to approach testing your ads, especially with a higher average order value product like yours.
Your question about whether $100 over two days is enough to test an ad for a $300 AOV product is a very common one. It's understandable to want to be efficient with budget, but for a higher ticket item like this, that initial test might be cuttin' things a bit short.
Why £100 might not be enough data...
When you're optimising for purchases, the advertising platform's algorithim needs conversion data to figure out who is most likely to buy. For a $300 product, you're naturally going to get fewer purchases than you would for, say, a £10 item. Getting only 1 purchase out of every 10 ads tested on a $100 budget isn't surprising and actually highlights that the platform isn't getting enough purchase signals quickly enough to learn effectively.
Think about the sales cycle too. Even if someone clicks your ad, it's not always an impulse purchase for a $300 item. They might need more time, might compare options, or just not be ready to buy that very second. A 2-day window is unlikely to capture many of these conversions.
You also mentioned that even your winning ads sometimes go 3-4 days without a purchase. This sort of fluctuation is totally normal, especially with higher ticket items. If your winning ads behave like that, it stands to reason that promising but not-yet-converting ads also need more time to prove themselves.
Seeing Add to Carts and Checkouts is a good sign...
The fact that some ads generate Add to Carts and Checkouts initiated is actually a strong positive signal. It means your ad creative and targeting are likely working to bring in the *right* type of person who is interested enough to take significant steps down the funnel. They just aren't completing the purchase immediately.
Cutting these ads off at $100 might mean you're stopping just before they might have converted. It also suggests that either the timing isn't right for the buyer (they need nurturing/retargeting) or there might be something on your website during the later stages (shipping costs, lack of trust, payment options?) that's causing them to drop off. We've seen this with ecom stores where poor site trust signals kill conversions even when the ads are good.
So, what can you do?
You have a couple of options to consider based on this. The goal is to give the ads enough opportunity to generate meaningful data for the platform to optimise and for you to properly evaluate their potential.
- Increase your test budget: You might need to spend £200-£300 or more per ad initially, depending on your target CPA for a $300 AOV product, to get enough impressions and clicks to potentially see purchases.
- Extend your testing duration: Running tests for 5-7 days, rather than just 2, gives the ad platform more time to find converting customers and smooth out those daily fluctuations where sales might dip.
- Consider optimising for a lower funnel event: While optimising for Purchase is always ideal in the long run, during the initial testing phase, especially with limited budget/time or a high AOV, you could consider optimising for Add to Cart or Checkout Initiated. This gets the platform more data points quicker, which helps it find users likely to take *some* action. Once you identify ads that are consistently driving these lower funnel events, you can either switch them to Purchase optimisation or use them for audiences in a later-stage funnel campaign (like retargeting). Just be aware that optimising for lower events *can* sometimes bring in less qualified traffic than optimising directly for Purchase.
Here's a quick overview of the main actionable step:
| Problem | Recommended Action | Why |
|---|---|---|
| Not enough purchase data for $300 AOV product on $100/2-day test budget | Increase initial ad test budget (£200-£300+) AND extend test duration (5-7 days) | Allows platform algorithim more time and data to optimise for Purchase; accounts for longer sales cycles and natural sales fluctuations for higher AOV products. |
Implementing these changes should give your potentially good ads a much better chance to perform and give you clearer data on which ones are actually winners for your product.
Considering expert help...
Testing effectively, especially for B2C products with higher AOVs or longer sales cycles (like some of the SaaS clients we've worked with where ROI takes longer), can be tricky. It requires careful consideration of budget, time, optimisation goals, and understanding funnel drop-offs.
If this feels complex or you're struggling to find a profitable testing methodology, working with an expert can often accelerate the process and avoid wasted spend. They can help define the right testing parameters, analyse data points beyond just immediate purchases (like site behaviour after click), and build out a full-funnel strategy including retargeting.
If you'd like to discuss this further or get more tailored advice based on your specific situation and website, we'd be happy to offer a free consultation. It's a good way to dive deeper into your funnel and see if there are other factors at play.
Regards,
Team @ Lukas Holschuh
