We fixed the funnel before running a single ad.
How we took one of our clients from an underperforming account to 2.4x ROAS and climbing, while cutting monthly ad spend by roughly 20%. We didn't spend more. We found the leaks first.
Skip to the numbersHigh-ticket offer · Long sales cycle · Meta paid media
Most Agencies Would Have Just Run the Ads
A high-ticket education client came to us with an account stuck around 1.3x ROAS, and pressure to spend its way out.
The obvious move was to take the budget, rebuild the campaigns, and buy more traffic. We audited instead. The leaks weren't in the ad account at all. They were in the offer, the landing experience, and the follow-up. Places more ad spend can't reach.
What We Found Before Spending a Rupee
We mapped the program, the offer, the competitors, and the funnel end to end. The verdict: fix the base first, or scale would only make the leaks more expensive.
The Best Reassurance Was Buried
The offer's strongest objection-killer, a refundable security deposit, sat far below the fold. Prospects were bouncing on a fear the offer had already answered. Whatever you sell, your best proof can't work where nobody reads it.
The Page Fought Its Own Data
GA4 behaviour data showed exactly which sections visitors engaged with. They were buried under sections people skipped. The page's order came from internal opinion rather than how buyers actually read it.
The Proof Didn't Hold Up
The social proof on display was the kind a skeptical buyer can't verify. In a high-ticket purchase, trust does most of the selling, so proof nobody can check becomes a leak.
No Way to Judge an Adset
High ticket plus low closure volume meant ROAS took months to "prove" anything, and months of budget went with it. The account had spend data, but no early signal of lead quality.
Three Moves, Three Different Muscles
These are selected, not a full list. Each move shows a different capability, and none of them started with "increase the budget."
Fixed the Base Before Scaling
The credibility muscle.
We rebuilt the landing experience around the real friction. The refundable-security-deposit term moved to the first screen, so the "I won't pay before I see results" objection dies right there instead of in a sales call. Then we reordered the page using GA4 behaviour data and moved the sections buyers actually engaged with to the top. Where the social proof couldn't be verified, we swapped in verified Google and Quora reviews that a skeptical buyer can check.
Built a Lead-Classification System
Judge an adset without waiting on closures.
For a high-ticket, low-closure-volume account, ROAS alone is too slow and too noisy to steer by. By the time it "proves" an adset is weak, the budget is already spent. So we built a lead-classification system. Every lead gets scored on the sales team's first impression, and those scores roll up to the adset level.
- Adset-level lead quality, not just lead count
- Keep-or-kill decisions in days, without waiting on a cohort to close
- Ad spend steered by what the sales floor actually sees
Proactive Reporting That Cut Spend 20%
Catch drift early, spend less finding out.
Weekly and monthly reporting built to flag funnel drift early, instead of letting a problem run until it breaks the numbers. The result: monthly spend cut from ₹1,36,000 to ₹1,08,000 (roughly 20%) while revenue and the core metrics kept rising. We treat reporting as a spend-efficiency tool. It earns its keep.
The Proof, From the Account Itself
Everything below comes straight from the account. Nothing is a projection; every figure was realized.
Reach got costlier. Leads got cheaper.
Monthly cost per 1,000 impressions (CPM) vs cost per lead (CPL), January–June.
View the data
| Month | CPM (₹) | CPL (₹) |
|---|---|---|
| January | 85 | 105 |
| February | 125 | 75 |
| March | 110 | 50 |
| April | 120 | 47 |
| May | 155 | 48 |
| June | 125 | 37 |
From 1.3x to 2.4x, and Still Climbing
2.4x is the realized figure. The latest cohort is still closing, so that number should move up rather than down. All of it on roughly 20% less monthly spend than when we started.
The strongest signal isn't a number, though. The client started us on paid media and has since handed over their entire social presence, Instagram to YouTube. A client expanding scope says more than any testimonial we could quote.