https://www.ad-lab.io https://res.cloudinary.com/ditkju4qi/image/upload/v1777711751/ad-lab/yb0xjrwxtrewv1e3tbnc.png Ad-Lab Ad-Lab logo https://res.cloudinary.com/ditkju4qi/image/upload/v1778070614/OG_image_kzu6av.png Google + YouTube Ads agency for ecommerce Ad-Lab https://www.ad-lab.io/about https://res.cloudinary.com/ditkju4qi/image/upload/v1777712184/Patrick_Headshot_fsvplh.png Patrick Schenken, Founder & CEO, Dubai Patrick Schenken https://res.cloudinary.com/ditkju4qi/image/upload/v1777712184/Stephan_Headshot_xachhc.png Stephan Ochse, COO, Dubai Stephan Ochse https://www.ad-lab.io/resources/case-studies/casa-beyond-home-decor https://www.ad-lab.io/api/case-studies/cover/casa-beyond-home-decor Casa Beyond came in with broad campaigns, no SKU prioritisation, and ROAS pressure. We segmented by margin, built tight campaign clusters, and optimised for conversion-value-over-cost at the SKU level. Same brand, same products, same ad spend appetite. Different system. Casa Beyond scaled to $560K/month without raising CAC https://www.ad-lab.io/resources/case-studies/b2b-youtube-search-106k https://www.ad-lab.io/api/case-studies/cover/b2b-youtube-search-106k B2B client in a competitive niche. We ran YouTube + Google Search only. Steady climb from $0 to $106K of attributed revenue in 28 days. The system was the win, not the budget. $106K revenue from YouTube + Search in 28 days https://www.ad-lab.io/resources/case-studies/eu-cold-traffic-104k https://www.ad-lab.io/api/case-studies/cover/eu-cold-traffic-104k Most brands treat Google as a harvest channel for branded clicks. Built right, it becomes an acquisition engine. Here's how we drove €104K in revenue with 70%+ from cold traffic. €104K in revenue with 70%+ from cold traffic https://www.ad-lab.io/resources/case-studies/million-dollar-90-days https://www.ad-lab.io/api/case-studies/cover/million-dollar-90-days Once you cross $100K+ in monthly ad spend, your biggest risk isn't the platform. It's operational chaos. This account ran $469K of spend over 90 days with $1.18M in tracked revenue, blended 2.52x. Sustained, not a flash. $1.18M in sales on $469K ad spend across 90 days https://www.ad-lab.io/resources/case-studies/17x-roas-from-scratch https://www.ad-lab.io/api/case-studies/cover/17x-roas-from-scratch $9.9K spend → $178K revenue → 17.97x ROAS. No viral spike, no seasonal promo, no discount. Built from scratch with profitable scale in mind. Systems, not luck. 17.97x ROAS on a freshly built ecom account https://www.ad-lab.io/resources/case-studies/niche-ecom-42-days https://www.ad-lab.io/api/case-studies/cover/niche-ecom-42-days Fast-growing niche ecom brand. Six weeks. $8.7K of spend, $34.7K of sales at 3.05x ROAS. Engineered, not lucky. Funnel-stage campaign architecture + feed work + conversion-first landing pages. Niche ecom: $34.7K in 42 days at 3.05x ROAS https://www.ad-lab.io/resources/case-studies/fresh-campaign-3-47x https://www.ad-lab.io/api/case-studies/cover/fresh-campaign-3-47x Client had historically struggled to break performance ceilings. Fresh campaign, right system. 3.47x ROAS on $1.83K of spend. Quote from the client: "I have never seen this type of ROAS on this account." 3.47x ROAS on a fresh campaign in a struggling account https://www.ad-lab.io/resources/case-studies/500k-monthly-club https://www.ad-lab.io/api/case-studies/cover/500k-monthly-club One ecom client just crossed half a million in monthly Google Ads revenue. 2× growth since we partnered three months ago. Founder reaction: "Let's gooo." Q4 target is $1M/month. Crossed $500K/month in Google Ads revenue https://www.ad-lab.io/resources/case-studies/controlled-ramp-31k https://www.ad-lab.io/api/case-studies/cover/controlled-ramp-31k Most case studies start after the hard part is done. This one starts on day one of a brand-new Google Ads account with no historical data. As spend increased, performance didn't deteriorate. It improved. From €0 to €31K/month with no efficiency decay https://www.ad-lab.io/resources/case-studies/90-day-248k-lift https://www.ad-lab.io/api/case-studies/cover/90-day-248k-lift February: $172K revenue, $62.7K spend, inconsistent daily performance. March: $421K revenue, $178K spend, stable optimised performance. The difference? A growth system instead of a gamble. +$248K in 90 days without killing ROAS https://www.ad-lab.io/resources/case-studies/7-day-18-percent-lift https://www.ad-lab.io/api/case-studies/cover/7-day-18-percent-lift Most accounts chase growth by increasing budgets. This account did the opposite: structural tightening at the margins, no creative refresh, no budget changes. 18% more revenue in 7 days at the same spend. +18% revenue in 7 days. Without increasing spend https://www.ad-lab.io/resources/case-studies/youtube-conversions-doubled https://www.ad-lab.io/api/case-studies/cover/youtube-conversions-doubled Most YouTube performance issues aren't creative problems. They're signal problems. We changed three things: excluded app inventory, built a conversion-led video system, layered in a purchaser-based first-party audience. Conversions doubled. YouTube conversions +100% with no spend increase https://www.ad-lab.io/resources/case-studies/shopping-coverage-49-to-57 https://www.ad-lab.io/api/case-studies/cover/shopping-coverage-49-to-57 Shopping performance jumps when coverage improves, not when bids increase. We didn't raise bids or loosen targets. We implemented feed duplication. Impression share went from 49% to 57% against the same competitors. Shopping coverage 49% → 57% in one month https://www.ad-lab.io/resources/case-studies/bfcm-revenue-doubled https://www.ad-lab.io/api/case-studies/cover/bfcm-revenue-doubled Most accounts lose discipline in November. Budgets surge, promos stack, ROAS gets sacrificed. This account took a different path: revenue +112%, spend +134%, ROAS softened only 4% and stayed above 2x target. +112% revenue in November with ROAS holding above target https://www.ad-lab.io/resources/case-studies/schema-fix-conversions-doubled https://www.ad-lab.io/api/case-studies/cover/schema-fix-conversions-doubled Ads dialled. CTR healthy. CPC low. Conversions embarrassing. We went deeper than the campaign and looked at the tech layer. Google was showing a 4-day shipping estimate; the brand fulfilled in 2. Fixed the schema, conversion rate doubled in 7 days. Conversion rate doubled by fixing the shipping schema https://www.ad-lab.io/resources/case-studies/brand-nonbrand-split-true-cac https://www.ad-lab.io/api/case-studies/cover/brand-nonbrand-split-true-cac The account reported a 4.0x blended ROAS and everyone was happy. Then we separated branded search from real acquisition. Brand was running at 14x and carrying the whole number. Non-brand, the part that actually grows the business, sat at 2.4x and capped. Here's how we split them and doubled new-customer revenue. A 4.0x blended ROAS was hiding a non-brand account barely breaking even https://www.ad-lab.io/resources/case-studies/pmax-structure-asset-group-split https://www.ad-lab.io/api/case-studies/cover/pmax-structure-asset-group-split Most accounts run one Performance Max campaign with every product in it and wonder why it plateaus. The bidder can't tell a 12% margin clearance mug from a 60% margin hero sofa, so it averages. We rebuilt this account into a margin-tiered, feed-segmented PMax structure with brand excluded. Same budget, 38% more revenue, and the profitable SKUs finally got the spend. The Performance Max structure we put on every account over $50K a month https://www.ad-lab.io/resources/case-studies/full-funnel-youtube-scale-1m https://www.ad-lab.io/api/case-studies/cover/full-funnel-youtube-scale-1m This account was already good. Search, Shopping, and Performance Max were clean and profitable at a 3.0x blended ROAS. The problem with good accounts is they run out of demand to harvest. Push more budget into Search and you just pay more for the same clicks. We added YouTube and Demand Gen as a demand-creation layer, sequenced so it fed the harvest layers, and doubled the account in a quarter. Here's the full campaign map, every campaign and what it feeds. $520K to $1.06M a month by adding YouTube on top of a clean Search, Shopping, and PMax stack https://www.ad-lab.io/resources/case-studies/poas-profit-bidding-rebuild https://www.ad-lab.io/api/case-studies/cover/poas-profit-bidding-rebuild The account looked like a 3.2x ROAS winner. The problem: its bestsellers were its lowest-margin products, and the bidder was pouring budget into them because they converted. Revenue looked great. The bank account didn't. We fed profit into Google instead of revenue, let the bidder optimise for margin, and grew gross profit 36% without selling a dollar more. A 3.2x ROAS account that was losing money on its bestsellers https://www.ad-lab.io/resources/case-studies/feed-engineered-shopping-moat https://www.ad-lab.io/api/case-studies/cover/feed-engineered-shopping-moat The account was bidding fine and still invisible on half its catalogue. Shopping doesn't reward bids, it rewards relevance and coverage. We rebuilt the product feed (titles, attributes, GTINs, a supplemental feed) and layered a three-tier priority structure to funnel queries. Same budget, 41% more Shopping revenue, and products that had never shown up started winning. Shopping revenue +41% from feed engineering, with bids untouched https://www.ad-lab.io/resources/case-studies/troas-target-unlocked-scale https://www.ad-lab.io/api/case-studies/cover/troas-target-unlocked-scale The account ran a 4.5x tROAS target and everyone felt good about it. Trouble is, break-even was 2.2x, so a 4.5x target left a mountain of profitable volume on the table. We laddered the target down in controlled steps, watched the marginal ROAS at each one, and uncapped the winners. Spend more than doubled, ROAS settled at a healthy 3.4x, and revenue grew 71%. Every extra dollar still cleared break-even. A 4.5x tROAS target was throttling a profitable account. Lowering it added 71% revenue https://www.ad-lab.io/resources/case-studies https://cdn.prod.website-files.com/667ea7e37c1a688a520d6b30/667ea7e37c1a688a520d6bc4_Thumbnail%20Gina.jpg I hired them about two years ago after being completely sick of agency after agency promising the world. What I appreciate about Ad-Lab is that they put skin in the game. They are honest and scrappy, and they are working hard to scale your business every day. Gina, Bohemian Mama https://cdn.prod.website-files.com/667ea7e37c1a688a520d6b30/667ea7e37c1a688a520d6bc3_Thumbnail%20Gina-1.jpg Ad-Lab has treated my small business like a large company. My sales have been increasing, performance is always improving, and ROAS keeps getting better. Gina, Close By Me Jewelry https://cdn.prod.website-files.com/667ea7e37c1a688a520d6b30/667ea7e37c1a688a520d6bc1_Thumbnail%20James.jpg Ad-Lab has been invaluable to Umart. We scaled our spend from $20,000 to $170,000 per month with a 1500% ROAS. They exceeded our tough requirements, were responsive 24/7, and handled our demanding needs efficiently. I highly recommend Ad-Lab to any e-commerce or retailer looking to scale. James, Umart https://cdn.prod.website-files.com/667ea7e37c1a688a520d6b30/667ea7e37c1a688a520d6bc2_Thumbnail%20Omar.jpg We've increased our sales by 40-45% with Ad-Lab. Patrick and his team are specialists in Google Ads, and I wouldn't recommend anyone else. I'll be using them for the rest of my business life because they are truly the best. Omar, Billion Ballers