When I came onto this brand, it was doing around $600–$800/day.
- Website looked solid.
- Ads had potential.
- Numbers were decent at the top of funnel.
But the real constraint?
👉 Cost per Add to Cart was good.
👉 Cost to Initiate Checkout was good.
❌ Cost per Purchase was way too high.
That told me the leak was happening between checkout start → purchase.
2. Fixing Checkout & Cart Trust
So the first moves I made were not ads — but trust elements at checkout.
- Added TrustPilot widget on cart.
- Stacked guarantees (money-back guarantee on product page AND checkout).
- Tweaked default Shopify checkout theme copy (like the “Secure Checkout” text).
- Swapped out checkout logo for stronger branding.
These little tweaks compounded fast. Conversions picked up immediately.
3. Post-Purchase Upsell System
Next constraint: ROAS was too tight to scale.
So we needed more money per customer.
I implemented a post-purchase upsell funnel (same setup I dropped in my Figma).
- Offer #1: Free product, charge shipping = ~$CAC.
- Offer #2: Added a second upsell.
- Offer #3: Added a third upsell.
- Downsells: If they declined the first one, we had 2 downsells lined up.
📊 Example math:
- CAC = $15.
- If upsell = +$15, then CAC is basically negated.
- Front-end acquisition becomes breakeven → scaling is easy.
Takeaway: If your post-purchase funnel is printing, scaling becomes a math game — not a guessing game.
4. Creative Breakdown
Once checkout + upsells were solid, we turned focus to creatives.
What I saw:
- Lots of ripped creatives.
- A couple image ads doing okay.
- ONE big marketing angle carrying everything.
So the move was obvious:
- Built a dedicated creative bucket for that angle.
- Dove deeper into the personas & emotions inside that one angle.
- Built out a market research doc with all new insights.
5. Data → Research → Creative Flow
To scale with confidence, I needed hard data to back every creative decision.
- Did a full Ads Manager breakdown → where the spend was going, what the metrics looked like.
- Analyzed every creative using Google Studio to understand why it worked and who it targeted.
- Implemented a post-purchase survey with open-ended questions.
- Every single answer was so specific it could be turned into its own ad.
- Exported this and used it inside Claude to supercharge insights.
- Zigpoll is best app > export csv. > upload to AI
Takeaway: Your customer is literally handing you the winning ad copy and angles — if you bother to ask.
6. Creative Team Alignment
Everything tied back into:
- Giving the creative team clarity.
- Having a feedback loop between customer data → research → creatives → ads.
- Making sure scaling wasn’t random but a controlled expansion.
That’s the first steps: fix trust, boost AOV with upsells, mine data, and align creatives.
Scaling isn’t “turning up budgets” — it’s removing constraints one by one until momentum compounds.