Evaluating the Effectiveness of Ecommerce Ads

I just audited a $3M e-commerce company’s ad account. Found 26% of “conversions” in their NEW customer campaign came from existing customers - nearly $30,000 worth of budget competing against themselves. Also found their P-Max campaign spending almost $20,000 on products already running in shopping campaigns. Pure audience overlap making their algorithm stupid. This happens because most advertisers obsess over keywords and bidding strategies but completely miss the biggest lever for ad efficiency: ↳ Controlling WHO sees your ads. Here's the audience targeting framework that destroys keyword competition: Step 1: PREVENT OVERLAP Most campaigns let new customers, retargeting audiences, and existing buyers all trigger the same ad groups. Our fix: Apply your customer list to each campaign, then set bid adjustments down 90%. This prevents existing customers from spending in new customer campaigns. Step 2: SEPARATE ROAS TARGETS ▪ Existing Customers: 600% ROAS target Why: They've already converted. Extremely high likelihood to purchase again. ▪ New Visitors: 400% ROAS target Why: Unknown conversion potential requires tighter efficiency targets. ▪ Retargeting Audiences: 250-280% ROAS target Why: Retargeting generates partial conversions - worth accepting lower ROAS. Step 3: ENABLE ALL AUDIENCES This account has 700+ audience segments available. They're only using 26 of them - all set to observation mode - collecting data but making zero bid adjustments. Even at 95% impression share and 3.87x ROAS, they're leaving efficiency on the table. Our fix: Enable ALL audiences in observation mode and use the data to target valuable audience segments that have previously been overlooked. Step 4: PRECISE RETARGETING Add another precision layer with time-based retargeting: 7-day, 14-day, 30-day, and 90-day segments each deserve different bidding strategies based on recency patterns. Step 5: SCALE AD SPEND Properly segmented campaigns get MORE efficient as you scale budget, not less. When properly implemented, you should be able to add a zero to your daily budget without changing efficiency metrics. That's how you know the system operates at maximum market capacity. THE TAKEAWAY This account was already operating at a 7.5/10—better than 95% of what I audit. But precision targeting makes the difference between hitting a ceiling and breaking through it. Stop fighting the keyword auction. Control the audience auction instead.

A D2C menswear founder I sat across last month showed me his Meta dashboard. ROAS 3.8x. Google Ads showing 3.2x. He was spending ₹15 lakh a month across both platforms and it seems like both channels are working. I asked him one question. What’s your blended ROAS when you check your bank account against total ad spend? He said 1.6x. Meta claims a conversion if someone even viewed an ad and bought within a day. Google claims the same conversion if that person searched the brand name before purchasing. Both platforms report the sale. Only one sale happened. According to a Varos industry benchmark, Meta reports 26% higher conversions on average compared to third-party analytics tools. Google Ads over-attributes by 15 to 20 percent when enhanced conversions are active. But that’s only the first leak. The second one is more expensive. His best-performing Meta ad was a Reel showing a guy walking into a meeting room in a sharp co-ord set. Great hook, strong thumb-stop rate. The ad worked. People clicked. They landed on the homepage. Not the co-ord set. Not even the category page. The homepage, with 400 SKUs and a banner for a monsoon sale that ended weeks ago. The average cart abandonment rate in Indian ecommerce is over 74 percent. Seven out of ten people who were interested enough to click, browse, even add to cart, still didn’t buy. The Reel sold a look. The landing page sold a catalogue. That disconnect between creative and destination is where clicks go to die. the third leak is slowest and difficult to catch - That co-ord set Reel had been running for six weeks. In the first week it was extraordinary. By week three, frequency had climbed, CPM followed, and the algorithm was still pushing it because it had no alternative. When your entire ad account depends on one type of creative, Meta’s delivery system concentrates on it until the audience stops responding. The DSGCP and Meta playbook surveyed over a hundred Indian D2C founders and found that 62 percent cited creative fatigue as a major bottleneck. Not targeting. Not budget. The creative dying while the campaign keeps running and nobody pausing it. Three leaks. Attribution inflates the win. The landing page bleeds the click. The creative fatigue while you’re still enjoying first week performance. The entire D2C performance marketing conversation in India is about the ad. Better hook. Sharper creative. Tighter targeting. Every conference panel, every Twitter thread, every agency pitch deck starts and ends with the ad. Nobody talks about what happens after the click. Nobody talks about what happens when both platforms count the same customer. Nobody talks about the slow death of a creative.

Ecommerce Meta Ads Checklist That Actually Drives Sales (Not Just Clicks) Running ads but not getting consistent results? Most brands don’t fail because of budget… they fail because they miss the fundamentals. Here’s a complete Meta Ads checklist every eCommerce brand should follow 👇 🔍 1. Tracking Setup (Foundation of Everything) If your tracking is broken, your ads are blind. ✔ Meta Pixel installed on all pages ✔ Conversion API (CAPI) active (server-side tracking) ✔ Events configured: ViewContent, AddToCart, InitiateCheckout, Purchase ✔ Event deduplication working (Pixel + CAPI) ✔ Domain verified ✔ Aggregated events set (Purchase prioritized) 👉 Without this, scaling is impossible. 🛒 2. Store Readiness (Conversion Matters More Than Traffic) Ads don’t convert — your store does. ✔ High-quality product pages (images, price clarity, CTA) ✔ Mobile-first optimization (fast loading = higher conversions) ✔ Smooth checkout (no friction) ✔ Trust elements (reviews, guarantees, return policy) 👉 Even the best ads fail with a weak landing experience. 🎯 3. Campaign Structure (Clarity Wins) Don’t overcomplicate. ✔ Objective: Sales ✔ Funnel: Prospecting → Retargeting → Scaling ✔ Budget split: 70% Cold | 20% Warm | 10% Hot ✔ ABO for testing, CBO for scaling 👥 4. Audience Setup (Let Algorithm Work Smart) Stop over-targeting. ✔ Broad targeting (minimum restrictions) ✔ Custom audiences (website visitors, ATC, buyers) ✔ Lookalikes (1–5%) ✔ Retargeting windows: 7 / 14 / 30 days 🎥 5. Creative Strategy (This Is Where Winners Are Made) Your creative = your sales engine. ✔ 3–5 creatives per ad set ✔ Multiple angles: problem, benefit, social proof ✔ Strong hook (first 3 seconds decide everything) ✔ Clear offer (discount, urgency, bonus) ✔ Native-style creatives (UGC works best) ✍️ 6. Ad Copy (Sell Emotion, Not Just Product) ✔ Address real customer pain points ✔ Focus on benefits, not features ✔ Strong CTA: Shop Now / Order Today 📊 7. Optimization (Data > Emotions) ✔ Test continuously ✔ Kill losing ads (no conversions = no mercy) ✔ Scale winners gradually ✔ Track key metrics: CPA, ROAS, CTR, CPM 🔁 8. Retargeting (Recover Lost Revenue) ✔ ATC retargeting (3–14 days) ✔ Checkout retargeting (high intent users) ✔ Offer-based retargeting (discount + urgency) 📈 9. Scaling (Smart Growth Only) ✔ Vertical scaling: Increase budget 20–30% ✔ Horizontal scaling: Duplicate winning ad sets ✔ Keep testing new creatives to avoid fatigue 💡 Final Thought: Winning in Meta Ads is not about hacks… it’s about execution. If you fix: 👉 Tracking 👉 Creatives 👉 Funnel You’ll automatically improve ROAS. If you’re running ads and not seeing results, save this checklist and audit your account today. 💬 Need help scaling your eCommerce brand? Let’s connect #MetaAds #FacebookAds #EcommerceGrowth #PerformanceMarketing #DigitalMarketing

I’ve helped 5 eCom brands exit for ~$500m. The acquirer always wanted lower CPAs: So we pull 8 levers: 1. Creative → Target ~1 new concept per $10k in monthly spend. → At $500k/mo, that's 50 concepts. → 70% video (top of funnel, builds awareness) → 30% static (bottom of funnel, closes sales) That's 35 video concepts, 15 static concepts. Then 2-3 hook variations per video, and 5-8 variations per static. That's roughly 70 videos and 90 statics. Cut 70%+ of creatives before they hit two weeks. Your top 1-2% of ads should drive ~50% of spend. In most accounts, 70-80% of creative continues performing month-over-month. That means: → To maintain: replace 20-30% monthly → To grow 20%: replace churn + add 20% more volume 2. Media buying There are three actions that cut CPA without new ads: → Pause or spend-cap everything above target CPA → Retest old winners with new copy, headlines, landing pages → Scale the top 1-2% to take ~50% of total spend 8-figure brands can cut CPAs by 50% with media buying alone. Keep testing budget under 20% of total ad spend. Limit budget changes to 10-15% max, but make changes twice as often. 3. Website optimization The benchmarks: → CVR: 3%+ (top 10% hit 4.7%+) → Add-to-cart: 7-10% → Checkout completion: 60%+ Sometimes a landing page with 10% higher CPA leads to faster repurchases and higher LTV. 4. Subscription optimization The targets: → Monthly subscription churn: under 7% → 12-month retention: 40%+ → Repeat purchase rate: 30%+ The lever is segmentation: → Subscription vs one-time buyers → 4 week vs 8 week vs 12 week frequencies → Product categories → Acquisition channels The gap between 2x and 4x purchase frequency is a 2x LTV multiplier. 5. CRO Target email opt-in: 2-5%. Run distinct landing pages for each avatar. Example avatars for a supplement brand: → General nutrition → Gut health → Weight loss 6. Tracking optimization Click-based attribution overvalues lower-funnel performance by up to 250%. Top-of-funnel creative can drive 13X more incremental acquisitions than bottom-of-funnel. Click attribution will tell you the opposite. Post-purchase surveys catch what click attribution misses. Track individual nCAC on every ad you run. 7. Ad copy and headlines Ad copy can boost performance by 30%. Give creators selling points, not exact scripts. Target: → 40%+ hook rate → 2%+ CTR → 2-3 hook variations per video concept minimum 8. Data reporting and analysis Know two numbers: Maximum spend (company stays profitable): → Gross margin - OpEx = maximum marketing spend % → Example: 50% margin - 10% OpEx = 40% max Target spend (customer stays profitable): → Project 3-month customer profitability = your target CPA → Example: $55 AOV, $30 first purchase profit, $39 at month 3 = $39 target CPA End of the day, acquirers want: → Profitable customer acquisition → Reliable new customer growth for 3+ years → LTV and margins optimized

This 10-minute change more than doubled the profit for one of my ecommerce clients. And it didn’t require new creative, audience testing, or a bigger budget. Here’s what actually happened: A DTC brand came to me running multiple Meta ad campaigns — each targeting slightly different stages of the buyer's journey. ROAS was stable — but just barely breaking even. Their main challenge? Structural inefficiency across the account: → Too many campaigns competing for the same users → Audience overlap driving up CPMs → Fragmented learning across campaigns, and ad sets → No clear segmentation between new, engaged, and existing audiences We made one change: Consolidated three separate campaigns into a single campaign to reduce audience overlap and improve learning. **Clearly define audience types (new, engaged, existing) for accurate reporting and deeper analysis.** Same creatives. Same product. Same total budget. Just one campaign — maximizing signal density, reducing audience overlap, and unlocking more efficient spend delivery. 📈 The result? → ROAS increased 31% → Revenue increased 31% → Net profit increased 1,750% (previous ROAS was breakeven — every lift went straight to profit) Meta was able to: → Centralize performance data — giving the algorithm a clearer feedback loop to optimize faster → Reduce fragmentation — so each ad set benefits from more data and quicker learning → Eliminate audience overlap — lowering CPMs and preventing budget cannibalization → Focus spend on the highest-intent users — improving efficiency without increasing complexity Takeaway: Big profit jumps don’t always come from big creative overhauls. Sometimes, it's one strategic restructure — done with intent — that unlocks sustainable scale. 💬 Running Meta ads and unsure if your campaign structure is built to scale efficiently? Shoot me a DM — happy to walk you through how I approach building lean, scalable account structures that drive real performance. – If you think someone in your network would benefit from this, like, comment or repost to share. Follow for more frameworks that tie ad structure to actual eCommerce profitability.

Most ecommerce brands approach creative testing by throwing ideas at the wall and seeing what sticks. But that's not the way to reliably scale. The foundation of creative performance is messaging that resonates with customers and your creative testing process needs to reflect that. We do that by breaking up creative testing into two distinct phases: "Explore" and "Expand." The Explore phase is where you're trying to find new angles that work. The word "angle" is key. If I'm right that the message is that critical, you shouldn't be testing formats & styles when you're trying to test angles; you should be testing messages. You should ask yourself questions likes: • What problems does my product solve for customers that I haven't tried talking about before? • How is my product better than alternatives my customers are considering? • What are customers saying they love about my product? And so on. Use AI to help you brainstorm this. Then take your best performing ad formats and rework them with these angles until you find new winners. Bonus points if you can rapidly configure landers, bundles & offers that drive the angle you're testing more aggressively. It'll make a more thorough test. You may even consider doing this with some kind of formula. We aren't great at doing exactly this, process-wise, but here's a way I've conceptualized it: • Step 1: Find 3 new angles Start with the overlap between customer desires and your product benefits. What do they REALLY want that your product delivers? Step 2: Create 6 ads per angle 3 simple stills (simple product image + clear, socially native copy) 3 midform explainer videos (15-45 seconds, voice-over focused) Both formats are fast and cheap to produce. The goal is testing messaging clarity, not production value. Once you find winning angles, that's when you expand with more formats, creators, and landing page variations. But that's for another post. This framework works because it prioritizes message over medium. If you can't nail your messaging, no amount of creative polish will help. So invest more time into your message than your media, test it broadly against your strongest existing ads, then double down on what actually drives results.

The mistake I see most often in eCommerce ad accounts: Optimising for the highest possible ROAS instead of the highest possible revenue at an acceptable ROAS. These are not the same goal. And confusing them costs real money. Here's the calculation every brand should run: What is my break-even ROAS? What is my target ROAS after accounting for margins and operating costs? Once you know that number, the goal becomes: maximise spend at or above the target. Not minimise spend to protect a higher number. An account spending $5,000/month at 5x ROAS is less valuable than one spending $100,000/month at 3x, if margins support 3x. We had a client ask us to slow down ad spend because production couldn't keep up with orders. That is the problem you want to have. The constraint was operational. The ads were working. Slowing down marketing to accommodate operations is a growth decision, not a performance one. Scale to your target efficiency. Not below it to feel comfortable.

Interesting episode from The Commerce Collective focusing on the concept of Retail Media spend being measured not just How Much but also How Well. Also could help with balancing out people's perceptions of impact of Retail Media from a short term and long term impact POV. Some of the key concepts and possibly new terminology include: • Efficiency and the Impression Tipping Point: The methodology uses Regression Discontinuity Design (RDD) to identify the "critical mass" or optimal range of daily impressions (or clicks for some ad types) where campaigns start delivering significant results, avoiding both under-spending and diminishing returns. • Relative Effectiveness of Ads: This approach utilizes Causal Directed Acyclic Graphs (DAGs) to map out and measure the influence of various factors (like ad spending across different types, page views, and search trends) on total sales revenue, isolating the incremental sales contribution of each ad type. • Ad Carryover (Long-Term Effectiveness): By employing a sophisticated time series model called VAMAX, this analysis measures advertising impact in two-week intervals, extending up to 12 weeks beyond the standard 14-day attribution window, while accounting for the expanded customer journey, including branded searches and brand loyalty. • Off Amazon Impact and #Omnichannel Measurement: This component uses the Amazon Shopper Panel, where participants share over 3 million receipts monthly, to understand the true total return on ad spend (ROAS) by measuring sales. • Science-Based Approach to Optimal Ad Spend: The overarching vision is for the Analytics and Insights team to use scientific methodologies to create strategic insights that enable advertisers to achieve optimal marketing decisions, focusing on spending smarter rather than just spending more Show Notes: What’s the real impact of your advertising - and how do you know when you’ve reached the point of diminishing returns? In this episode, Emma Irwin sits down with Iñigo Gutierrez Fernandez, Analytics & Insights Associate Principal at Amazon Ads, for a behind-the-scenes look at the science powering smarter budget decisions. Iñigo unpacks #Amazon’s holistic measurement framework, from pinpointing the “tipping point” for ad efficiency, to understanding both immediate and long-term campaign impact, and even tracking omnichannel results through the Amazon Shopper Panel. You’ll learn how to move beyond guesswork and use data to identify when your investment is working, which channels drive lasting value, and how to build a strategy that fits your brand’s goals. https://lnkd.in/gUsM2eB9

After spending over $700k / mo on Amazon Ads here is a 5-step framework I've learned to use to diagnose ad performance: - TACOS - Conversion Rate - Targeting - Campaign Management   To start, if TACOS is within goal, scale as aggressively as possible, if you're below your TACOS percentage you're missing out on profitable sales.   If TACOS is too high, check your conversion rate next. If you can't compete with your categories CVR you'll never be able to scale your ads.   If your conversion rate looks good - look into your ad targeting next, are you targeting shoppers who are specifically looking for you? Or are you going too broad? Always start low in the funnel and work your way up.   If your listing's CVR & your targeting is good - look at your campaign management. Overbidding? Overspending in the wrong campaign(s)? Only leveraging one match type? Time to improve your campaign management.   Work your way through the issues in this order and you'll turn your ad performance around in no time. 🤝 #Amazon #PPC #ecommerce #digitalmarketing #digitaladvertising

Published a case study with my client Watsons on their results testing Omni Ads when it was just a beta earlier this year Post pandemic, retail had a revenge come back But here's the problem, we kept optimizing our ads like it was 2020, last click attribution to ecommerce sales was the focus metric even for retailers So our product team at Meta started developing omnichannel ads as a solution to measure and optimise for online and offline sales Watsons Thailand was the perfect candidate for testing the beta solution as they - had 750+ stores across Thailand - was already sending offline events via CAPI - had a strong web and app ecommerce We ran a multi cell Conversion Lift Study to test: A. Their usual ads: Optimized for online purchases B. New omnichannel ads: Optimized for actual customer behavior (Online + Offline) Same creative. Same targeting. Same budget. The results? - 16.5X lift in return on ad spend for omnichannel ads, compared to usual ads optimised for purchases - 80% lower cost per conversion lift for omnichannel ads, compared to usual ads optimised for purchases - 3.4X increase in offline purchase value for omnichannel ads, compared to usual ads optimised for purchases The winners will be retailers who understand that online and offline aren't separate channels. They're different moments in the same customer journey. #meta #omniads