Your dashboard looks busy, but your account is optimizing for cheap, not for serious. If one of these is your reality, keep reading. Every story below started here.
Calendar full, buyers missing, no-shows eating your closers alive.
ROAS stuck, one-time buyers, discounts doing the selling instead of the brand.
Volume up, quality garbage, sales team furious at marketing.
Trials that never activate, a CAC that never pays back.
Not a report you file away. A different way your account behaves, and a team that knows why.
Your account starts feeding the people who actually purchase, not the cheapest clicks Meta can find.
SOPs, checklists and a daily optimization system, so your account stops being a black box.
We train the people you have, and if you hire, you pull from 200+ buyers trained in this exact system.
With Trackocity and Pixel Conditioning you finally see what's really working, so you scale it instead of guessing.
A framework built to grow spend without breaking efficiency, proven across hundreds of accounts.
You stop reacting to every daily number. In a client's words: "I don't get nightmares anymore, because I know exactly."
Same framework underneath. The only question is whether you run the machine yourself, or have us in the trenches with you.
You want control. We arm you with the full system.
You want us in the trenches. Weekly. On your account.
Real businesses. Real turnarounds. Every one of these started stuck, exactly where you might be right now. Read as many as you like. They all follow the same shape: they came to us bleeding somewhere, so we found the leak and installed a system, and the numbers moved.
They were selling, but the account was stuck at a ROAS of 3, and a third of every rupee of revenue was disappearing back into Meta. At that math the margin is gone. But they couldn't see where the money was actually leaking, so they kept spending blind.
So we rebuilt their reporting and attribution on Trackocity, killed the frequency and audience waste, and installed a catalog engine that fed Meta the right products. Therefore ROAS crossed 8, Meta's cut of revenue fell to 12%, and customer lifetime value climbed inside two weeks.
"When that changes, it completely changes the financial dynamics of the company."
They inherited an account running at a 1.28 ROAS, with the majority of shoppers falling off the product page before they ever reached checkout. But the account was optimizing for the wrong signal, chasing cheap clicks instead of purchases, and the previous agency's own math was off.
So we rebuilt it into a clean three-bucket structure, switched optimization to purchases, scaled founder-led UGC to dozens of videos a week, and layered in Trackocity and session-level analytics. Therefore their ROAS hit an all-time high near break-even on new customers, conversion rate climbed from under 4% to 6%, average order value rose 20%, and acquisition efficiency jumped 2.5×.
Their account had been trained to spend on losers, and return on ad spend had collapsed to 0.66. Worse, they have one iron rule: they never, ever discount. But without a real source of truth, they couldn't tell which campaigns deserved budget.
So we de-optimized hard, ran our Nuke Method of fifty-plus campaigns a day with hourly kill-and-scale calls, rebuilt attribution on Trackocity, and shipped twenty deliberately ugly ads a day. Therefore ROAS climbed past 2.6, and their hero product went from 25-30 orders a day to 80-90, peaking past 100, all at full price.
Most brands only fix the account when a sale is coming and then panic. Jaey did it the other way around. So we fixed the normal days first and nearly halved their cost per acquisition. Therefore when the sale actually hit, the system was already in place, and ROAS hit 4× instead of collapsing under the volume.
His cost per lead was climbing every week, his ad spend was rising while quality was dropping, and he'd been stuck like that for three or four months. One messy account, barely a handful of ads, and a pixel that had frozen on the wrong data. But he had no structure and no way to track what was really happening.
So we rebuilt him into a clean three-campaign structure, retrained his pixel on real purchases, and scaled his creative past thirty ads. Therefore his fat-loss cost per acquisition landed near ₹1,000 against a market paying ₹30,000, his funnel conversion went from 44% to 58%, and his daily spend scaled from five figures to six.
"I don't get nightmares anymore, because I know exactly."
At one point ₹1 lakh in spend produced 249 bookings and exactly one sale. But the lead quality kept swinging wildly, because the pixel was learning from junk.
So we stabilized the spend, retrained the pixel on serious buyers through Pixel Conditioning, and added an order bump to lift order value. Therefore spend held steady past seven figures a month, cost per lead settled at ₹287 (a 43% drop), and his sales team felt the quality shift first.
"I had no idea about the ABC of Facebook ads. Now I'm nailing it."
They'd run a profitable business for years, and then their cost per acquisition suddenly doubled, from around ₹900 to ₹1,800, and for the first time they started seeing losses. But the real leak was duplicate audiences and zero attribution, invisible on the dashboard.
So under our consulting they fixed the tracking, added an order bump, moved to purchase optimization, and became one of the first fitness brands in India running on YouTube ads. Therefore their CPA came back under control, the order bump opted in at 58% against a 25% norm, and landing-page conversion climbed to 2.44%.
"Now our CPA is back under control."
They were already getting good results running ads themselves, but they couldn't scale, and at that level small mistakes cost big money. But they had no SOP for the daily optimization that scale demands.
So we standardized a target cost per acquisition, built an offer ladder from a ₹199 front end up to a ₹7,000 makeover, and scaled with creative volume. Therefore leads went from 20 a day to 400, at a consistent three-figure cost, for a paid product, and one month crossed ₹1.6 Cr in spend against ₹1.64 Cr in revenue.
"At no point did I feel like Sannidhya is not part of the team. He works with you as if he is."
Their dashboard proudly reported 44,561 leads. But only 1,237 of them were real. The business was making every decision on a number inflated by 1,785%.
So we rebuilt attribution onto a single source of truth, and fixed the creative — a single caption change tripled click-through from 0.5% to 1.5%. Therefore they finally saw what was actually working, and real customer growth ran at 30% month over month.
This is the arena Sannidhya spent four years in, and it's where "serious buyers, not volume" became non-negotiable, because in finance a junk lead is a compliance liability, not just a wasted click. So across a five-year partnership we held cost per lead at £12-14, roughly 40% under the market benchmark. Therefore the account generated over 274,000 qualified leads on more than £5.2M of managed spend, without the quality falling apart at scale.
Most SaaS accounts break the moment you push spend, because the cost per acquisition runs away from you. So we scaled their monthly spend from six figures to seven while holding the CPA steady, and tightened the webinar funnel around it. Therefore the show-up rate held above 80%, touching 88% on their best runs, in a category where 50% is considered good.
Same system, a completely different problem: fill arenas around the world for one of the biggest names in Punjabi and Sufi music, Satinder Sartaaj.
tickets sold across the tour
tickets a day at run-rate
cost per ticket at best efficiency
A world tour across Australia, the US and India isn't a ROAS game, it's a cost-per-seat game, and the clock is brutal: when a show date arrives, every empty seat is gone forever. But the ticketing ads were running on a Traffic objective, optimizing for clicks, not for people actually reaching checkout.
So we rebuilt the entire account around the Initiate-Checkout signal, stood up a server-side Conversion API that pushed real purchaser data back to Meta every thirty minutes, wired in Trackocity, and localized the creative down to the emotion and even the language, Urdu fonts for the Dubai show. Therefore the tour moved 281,000 tickets across 32 shows at roughly 5,000 a day. New York became the biggest market and nearly sold out. San Jose came in at $8.13 a ticket, Sacramento at $4.30.
And then the real test. Thirteen days out from a Melbourne show, only 1,200 of 8,000 seats were gone. The brief from the artist's camp was one line: sell it out. So we planned the budget backwards from capacity, ran hourly slot-level reporting anchored to the venue's timezone, and pushed. Therefore the room filled. The whole point was never a vanity metric. It was a full house, on the night, every night.
Not consulting clients, course students. In their own words.
A few of the brands that trusted us with their growth
Every account on earth is stuck at one of these three. Every story above was really just a matter of finding which one, and fixing it in the right order.
Volume of the right creative, built to a system, so the algorithm always has a winner to find.
A daily SOP for what to look at and what to cut, so nothing good gets starved and nothing bad gets fed.
Add budget where it pays and pull where it doesn't, so growth doesn't torch your efficiency.
More than $125M in Meta ad spend managed over a decade, across the UK, US, Canada, India, Australia and the GCC. Four of those years were lead generation for car finance and claims in the UK, at six-figure spends, where bringing serious buyers instead of volume was the only way to survive.
Author of the bestselling Facebook ads book, 10,000+ copies sold. The trainer behind 200+ media buyers now placed inside client businesses. He's in every consultation personally, which is why capacity is deliberately small.