Meta Ads Performance Analysis

Did META just expose itself with this new feature? Because what it quietly rolled out this week… might just change how we measure success in performance marketing. 👀 Let me break it down: Say your campaign shows 500 conversions. But the new column might say: 👉 “Actually, only 400 of those were incremental. Meaning, they happened because of your ad.” The other 100? Meta’s model says they would’ve happened anyway, from repeat buyers, brand recall, direct traffic, whatever. For the first time, Meta is letting you filter signal from noise. 🧠 Now let’s apply this with a real-world lens: Imagine two brands: 1️⃣ Jewelry Brand- AOV ₹5,000, low repeat 2️⃣ Personal Care Brand- AOV ₹500, high repeat Both run ₹1L/day campaigns. In jewelry, ads initiate desire: discovery > consideration > action. → Incremental Attribution: High → ROAS looks real In personal care, ads often hit already-warm users: reminder > restock. → Incremental Attribution: Low → ROAS looks good, but impact is questionable This is the gap most marketers never measure, and Meta just gave us a way in. 📊 So how can we use this? - Start by adding the “Incremental Attribution” column in Ads Manager. - Compare campaigns. Products. Funnel stages. Creatives. Offers. Ask: → Which ads are genuinely creating new demand? → Where are we paying for conversions that would've happened anyway? → Are our retargeting campaigns cannibalizing organic sales? 🔍 How I’m using it already: We’ve started analyzing multiple live campaigns. Some campaigns that looked strong on ROAS… fell flat on incrementality. Others with average performance? Turns out they were driving real new demand. We’re now: → Ranking campaigns based on incremental lift → Scaling the top ones for the next few days → Watching to see how that impacts real growth and CAC If this works, Incremental attribution = your new bullshit filter. -------------------------- P.S. I’ve seen this feature live on only 2 ad accounts so far, and I’m already having fun digging into the gaps. If you’ve got access to this already, what are you seeing? 👀

Has your Meta performance stagnated? REACH is often the culprit, but its hard to see this when looking at the standard ads manager views. If you are not continually driving new reach, you will eventually run into performance ceilings. To drive new reach, you need to launch new creative, target new/broad audiences, and most importantly move away from click-based attribution. Accounts optimized to 1-day click attribution see the highest cost of reach and hit performance ceilings far sooner than those with view optimization. This is because Meta is ONLY going after people likely to click - this is a small % of the population and greatly constraints your total potential reach. Brands optimize to 1-day click because it looks good in last click attribution. But the long term side effects cannot be ignored. We just ran this analysis for a prospective client (apparel brand, everything optimized to 1d click, use last click internally) and the story is quite dire. Looking at April: - The brand spent 25% more YoY - They paid 62% more to reach their audience - And they reached 23% FEWER people YoY The "certainty" you are buying with 1d click attribution is quite literally destroying your business. At these rates, this brand will run out of money in months. So what can you do? 1. First, pull this analysis for your business. You'll need to use Ads reporting to get the right total reach counts. My friend Kevin Kovach also talks about rolling reach often. You can work with your Meta rep on this specific analysis. 2. If you are running 1-day click attribution, begin testing 7dc/1dv ASAP. It's critical you run this as a lift study, as the results are guaranteed to look worse in any last click model. 3. If your problems persist even after attribution changes, focus on other levers like creative. We've seen video be a powerful lever for finding new audiences - the first place I would start is UGC video. New Engen

How to Audit a 7-Figure Meta Ads Account Like a Pro When I audit a 7-figure Meta ads account, the goal isn’t just to find inefficiencies—it’s to unlock scale. Most accounts I audit are messy: ✔️ Bloated structures with redundant campaigns ✔️ Poor alignment between ad spend, customer acquisition cost (CAC), and business profitability ✔️ No clear process for testing, scaling, and optimizing Here’s how I audit accounts... Step 1: Account-Level Financial Performance Before diving into the ads, I start at the business level. Scaling isn’t just about ROAS—it’s about profitable customer acquisition. Key metrics to analyze: 📊 MER (Marketing Efficiency Ratio) & AMER (Acquisition MER) – Is ad spend translating to profitable revenue? 📉 CAC vs. LTV – Is the cost to acquire a customer sustainable in the long run? 📈 Blended ROAS vs. Platform ROAS – Are platform-reported numbers misleading? 💰 Contribution Margin – Does scaling ad spend improve or erode profits? This step ensures Meta isn’t just driving revenue—it’s driving profitable revenue. Step 2: Campaign Structure & Organization Next, I review the campaign architecture. It should have a clean, hierarchical structure with clear objectives. 🚀 The Ideal Structure: 1️⃣ Testing Campaigns – New creatives & audiences (structured and controlled) 2️⃣ Scaling Campaigns – High-performing creatives & audiences (increased budgets, bid strategies applied) ❌ Red Flags in Structure: ⚠️ Randomly mixed testing & scaling in one campaign ⚠️ Poor naming conventions (hard to analyze performance) Step 3: Creative Performance & Messaging Meta ads succeed or fail based on creative. I analyze: 📊 Creative Performance Metrics: ✔️ CTR (Link Click-Through Rate) – Is the ad engaging? (Target: 1.5%+) ✔️ Thumb-Stop Ratio – How many people watch the first 3 seconds? ✔️ Engagement & Shareability – Do people interact, comment, and share? Step 4: Bid Strategy & Budget Allocation Scaling isn’t just about increasing budgets—it’s about doing it efficiently. 💰 Analyzing Bidding & Scaling Strategies: ✔️ Manual vs. Auto Bidding – Is the account using bid caps, cost caps, or lowest-cost bidding correctly? ✔️ Scaling Strategy – Are budgets scaling gradually, or are sudden jumps causing instability? ✔️ Budget Efficiency – Are some ad sets spending too much with poor results, while winners are capped? Step 4: Action Plan & Next Steps After identifying what’s broken, I create a clear, step-by-step plan to fix inefficiencies, optimize scaling, and increase profitability. Immediate Fixes (0-7 Days) ✅ Pause redundant campaigns & consolidate structure ✅ Cut high-spend, low-return ad sets ✅ Implement strict CPA-based budget controls Short-Term Strategy (7-30 Days) ✅ Launch systematic creative testing ✅ Introduce structured scaling campaigns ✅ Optimize bidding If your account lacks clarity, structure, and a clear path to scale, it’s time for a real audit. Drop “AUDIT” in the comments, and let’s take a look. 🚀

We've scaled brands to 9 figures on Meta. Before we touch the budget, we look at 4 metrics. If you're spending $50k+ a month and wondering why you can't scale, the answer is in here. Metric 1: Spend Efficiency This tells you one thing: did your best ads actually get the spend they deserved? Most accounts we audit have the same problem. Winners sitting at low spend while garbage creatives are burning cash at a high CPA. That's Meta's algorithm making decisions you should be making. What you want to see: → Nothing in the top right (high spend, high CPA — you're scaling losers. Kill these.) → Bottom left is fine — that's your testing zone, new ads at low spend → A handful of dots bottom right with strong CPA — those are winners that actually got scaled If your top right is packed, you have a management problem before you have a scaling problem. Metric 2: Creative Freshness If the red is growing, your ads are aging out faster than you're replacing them. Each bar shows what percentage of your active creatives are fresh (under 30 days), aging (30-60 days), or stale (60+ days). Watch what happens from January to June — the green shrinks from 70% to 18% while the red balloons from 10% to 60%. That's a creative pipeline dying in slow motion. Most brands want to 3x their budget but they're launching the same number of ads they were at 1x. That math doesn't work. Use this to figure out how many new creatives you need per month to stay ahead of the decay. Metric 3: Freshness Trend This tracks what percentage of your ad spend is going to creatives under 30 days old. Below 50% means you could be coasting on stale creative. Which means you could be one algo update away from a very bad week. When you see the line dipping into the danger zone — like April through June and again in September — that's your creative machine falling behind. You can bring back old winners occasionally, but if the overall trend keeps dropping, you have a production problem disguised as a performance problem. Metric 4: Optimization Cadence When is someone actually managing the account? Look at the dropoff from Wednesday to the weekend. Monday through Wednesday the account gets 28-34 changes per day. By Friday it's 12. Saturday and Sunday? Basically ghost towns — 3 and 2 changes respectively. Weekends off means 30% of your budget is running on autopilot. Performance climbs early in the week, fatigues over the weekend with nobody watching, and Monday is spent rebuilding instead of scaling. You lose 2 days every single week. Read them together and you can diagnose almost any scaling problem: Bad efficiency + low cadence = nobody's managing the account. Bad efficiency + high cadence = wrong changes. Strategy problem. Low pipeline + high churn = not making enough ads. High pipeline + still stale = making ads. They just aren't good. Before you jump in and claim that budget is the bottleneck, make sure you have a solid grasp of these …

Companies spend thousands on Meta ads but often see high CPC, low CTR, and weak conversions. After analyzing five (sales) campaigns yesterday, I found common mistakes that kill performance. Here’s how to fix them 👇 𝗕𝗶𝗴𝗴𝗲𝘀𝘁 𝗺𝗶𝘀𝘁𝗮𝗸𝗲𝘀 𝗶𝗻 𝗠𝗲𝘁𝗮 𝗔𝗱 𝗦𝗲𝘁𝘂𝗽 🔹 High Frequency ≠ Success If frequency is 3.8+ in cold audience campaigns, your audience is too narrow—the same people see the ad repeatedly and stop engaging. Retargeting campaigns? High frequency (3-5+) is fine because those users already showed intent. 🔹 Budget Misallocation High-performing campaigns aren’t scaled despite low CPC and high CTR. Poorly performing ads keep running without creative refreshes, wasting spend. 🔹 Wrong Ad Formats & Placements • Static images overused instead of video formats. • Carousel ads lack storytelling - each slide should highlight a different benefit. • Meta Reels & Stories underutilized, despite having the lowest cost per interaction.    🔹 Lack of testing & iteration • No A/B testing on creatives, headlines, or CTAs. • No experimentation with visuals or audiences. 𝗕𝗶𝗴𝗴𝗲𝘀𝘁 𝗺𝗶𝘀𝘁𝗮𝗸𝗲𝘀 𝗶𝗻 𝗔𝗱 𝗖𝗿𝗲𝗮𝘁𝗶𝘃𝗲𝘀 🚫 Weak Call-to-Action (CTA) “Shop Now” is too generic. Better CTAs: • Sign Up Now • Claim Your Discount • Reserve Your Spot 🚫 Generic Headlines that don’t drive action Bad Example: Big Sale! 60% Off! Better: • Last Chance! 60% Off – Don’t Miss Out! • Only Today – 60% Off! 🚫 Poor visual hierarchy • CTA buttons blend in - use high-contrast colors. • No countdowns (e.g., "Only X Hours Left!"). • No badges/stickers like “LIMITED OFFER” or “50% DISCOUNT.” 🚫 Too similar images in Carousel Ads Each slide should emphasize different benefits, like: • 50% Off Everything • Mentor Support • 24/7 Access • 10,000+ Happy Users 🚫 Story Ads look like regular Feed posts • No motion elements (GIFs, animations, swipe-up prompts). • No stickers like “Only X Hours Left!” • No engaging hooks - start with a question: Have you used your 50% discount yet? 𝗧𝗵𝗲 𝘁𝗿𝘂𝘁𝗵 𝗮𝗯𝗼𝘂𝘁 𝗟𝗼𝗼𝗸𝗮𝗹𝗶𝗸𝗲 𝗔𝘂𝗱𝗶𝗲𝗻𝗰𝗲𝘀 𝘃𝘀. 𝗖𝗿𝗲𝗮𝘁𝗶𝘃𝗲 Lookalike audiences aren’t the magic bullet anymore. Before (pre-iOS 14): Lookalikes worked well - Meta had more user data. Now: Meta favors broad targeting, meaning strong creatives outperform segmentation. Why? • Limited tracking (iOS 14 impact) - Meta relies more on creative performance. • Creative is the number 1 success driver, not audience targeting. • Broad audiences often outperform lookalikes - Meta auto-optimizes based on engagement. How to fix your Meta Ads? ✔ Segment cold vs. warm audiences properly. ✔ A/B test creatives, headlines, and CTAs. ✔ Use more video & dynamic content. ✔ Prioritize Meta Stories & Reels. ✔ Make CTA buttons & key elements pop. Small changes = big impact. But don't change things every day! You'll never get out of the learning phase. A campaign that isn’t working today might explode tomorrow - with the right optimization.

Meta just rolled out major improvements to its value optimization models and the results are hard to ignore. Advertisers optimizing for conversion value instead of volume are seeing up to 29% higher ROAS. This update means Meta’s AI is now better at understanding what valuable users look like, not just those who install or convert, but those who spend, engage, and stick around. For performance marketers, this is a big deal. It gives us more control over how Meta defines “success,” allowing campaigns to focus on lifetime value instead of surface-level metrics. Meta has also deepened its integration with Mobile Measurement Partners (MMPs) like AppsFlyer, Adjust, and Singular. That alignment means attribution windows and user definitions now match more closely, improving data accuracy and campaign optimization. Bottom line: Meta’s AI is becoming more business-aware. Marketers who feed it the right data and define value clearly will see the biggest lift in efficiency and ROAS.

Why is no one talking about this huge change? If your ad performance has been struggling since August, you're not alone. Meta just rolled out their biggest algorithm update since iOS 14.5  and most advertisers have no idea what hit them. 🚨 Meta's Andromeda Update is Quietly Revolutionizing Facebook Ads 🚨 What is Andromeda? Think of it as Meta completely rebuilding their advertising engine. To quote Meta: 'Meta Andromeda: Supercharging Advantage+ automation with the next-gen personalized ads retrieval engine.' Instead of scanning hundreds of ads, it now analyzes THOUSANDS in seconds using sequence learning to predict user behavior. The Game Has Changed: ❌ Old way: 3-6 ads per ad set ✅ New way: 30-50 ads with creative diversity ❌ Old way: Multiple campaigns with tight targeting ✅ New way: Consolidated campaigns with broad targeting ❌ Old way: Perfect individual ads ✅ New way: Creative portfolios (testimonials, founder stories, UGC, demos) Real Results: One of our clients saw CPMs drop 20% and CPAs decrease 35% after restructuring from 6 campaigns down to 2, loading every winning creative from the past year into one Andromeda-optimized campaign. ⚠️ Warning: Check your backend data. We've seen cases where Andromeda optimizes for existing customers rather than new acquisition.  Manual exclusions are a must. Action Steps: Consolidate campaigns with CBO + broad targeting Build creative portfolios with 10+ different ad concepts Test 20+ creatives per week (Meta's recommendation) Monitor backend metrics, not just Meta's reporting The advertisers who adapt now will dominate while others wonder why their 2023 playbook stopped working. Are you seeing similar changes in your accounts? Drop your experience in the comments 👇 #andromeda #Metaads

Want to scale your Meta Ads without wasting ad spend? Here’s the framework I use to turn chaos into performance: ✅ 𝟭. 𝗠𝗶𝗻𝗶𝗺𝗶𝘇𝗲 𝗪𝗮𝘀𝘁𝗲𝗱 𝗔𝗱 𝗦𝗽𝗲𝗻𝗱 𝘄𝗶𝘁𝗵 𝗮 𝗧𝗲𝘀𝘁𝗶𝗻𝗴 𝗖𝗕𝗢 𝗖𝗮𝗺𝗽𝗮𝗶𝗴𝗻 • Create a CBO (Campaign Budget Optimization) campaign for prospecting. • Launch ads in packs (4–6 creatives), each as a new ad set. • Facebook will automatically allocate spend to top performers. • If you need to force budget to an ad, use ad set spending limits—but go slow ($10/day max to start). • This creates a competitive testing environment that naturally filters top creatives. ✅ 𝟮. 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁 𝗮 𝗣𝗿𝗼𝗽𝗲𝗿 𝗦𝗰𝗮𝗹𝗶𝗻𝗴 𝗠𝗲𝗰𝗵𝗮𝗻𝗶𝘀𝗺 • Graduate winning creatives into a dedicated scaling campaign. • This campaign should be broad targeting only, minimal to no restrictions. • Do NOT pause the winning ads in the testing campaign - let them run in both places. • Scaling campaigns should eventually have 5–10 top creatives, with growing budgets over time. • Monitor performance and grow budgets methodically. ✅ 𝟯. 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗬𝗼𝘂𝗿 𝗔𝗰𝗰𝗼𝘂𝗻𝘁 𝘄𝗶𝘁𝗵 𝗖𝗹𝗲𝗮𝗿 𝗦𝘄𝗶𝗺 𝗟𝗮𝗻𝗲𝘀 • Segment your campaigns into: • Prospecting (100% net-new customers) • Retargeting (site visitors / add to carts who haven't purchased) • Retention (existing customers / purchasers) • Use custom audience exclusions and CRM lists (e.g., from Klaviyo) to enforce clean segmentation. • Each lane should have distinct budgets, KPIs, and expectations. ✅ 𝟰. 𝗦𝗽𝗲𝗻𝗱 𝗠𝗼𝗻𝗲𝘆 𝗪𝗵𝗲𝗻 𝗬𝗼𝘂’𝗿𝗲 𝗠𝗼𝘀𝘁 𝗟𝗶𝗸𝗲𝗹𝘆 𝘁𝗼 𝗠𝗮𝗸𝗲 𝗠𝗼𝗻𝗲𝘆 • Analyze performance data by day of week, platform, placement, age, and landing page. • Use data from Meta Ads, Google Ads, and Shopify together. • Increase weekend spend if data shows higher conversions (e.g., Fri–Sun). • Rebalance weekday budgets downward accordingly. • Re-assess performance every 4 weeks. 🔁 𝗕𝗼𝗻𝘂𝘀 𝗧𝗶𝗽𝘀 & 𝗥𝗲𝗺𝗶𝗻𝗱𝗲𝗿𝘀 • Never pause a working ad - always duplicate into new campaigns. • Data-led decision-making beats intuition. Let Meta do the heavy lifting. • Use Shopify data to validate ad platform insights. • Track graduation timing and only assess ad success from that time onward. #PerformanceMarketing #MetaAds #GrowthMarketing #EcommerceMarketing #CustomerAcquisition #ROAS #Meta

I've run 20,000 ads and spent $150M on Meta. Benchmarks I've found over 6 years: 1. 1 new creative concept per $10k in monthly spend. At $500k/month that's 50 concepts (~3 ads per concept, more for static-heavy). 2. At $100k/mo, aim for 70% new concepts and 30% variations. As you scale past $1m/mo, max out at 50/50. But never drop below 50% new. 3. 70% of your creatives should be cut before week 2. Only 10-20% will ever hit your performance threshold. If you're keeping most of your ads alive, you're probably losing money. 4. Your top 1-2% of ads should drive 50% of total spend. If they don't, you haven't found real winners yet or you haven't utilized them well enough. 5. Big swings have lower hit rates (5-10%) but higher total potential. These are the ads that can scale to $1m+ in spend. 6. 70% video, 30% static for most ecom brands. New brands need more video (more education, less BOF audience). Clothing should lean heavier static (lots of SKUs to show). 7. 15-20% of budget goes to testing. Under 10% and your creative pipeline dries up. Over 25% and you're burning cash without enough scale behind winners. 8. When you 2x spend, expect 20-30% ROAS decline. A $30 CPA at $50k/month might become $40 at $200k. Scale requires better ads, better optimization, better structure, or lower targets. 9. Limit bid and budget changes to 25% max. For 90% of changes, smaller and more frequent changes outperform bigger ones. 10. Meta always targets returning customers. Aim to keep returning conversions under 15-20%. Accept it and plan around it. 11. Ad copy can improve performance up to 50%. But a great ad outperforms by 500%. Copy matters, but the creative itself is where the real leverage is. 12. A great media buyer improves ROAS 100%+ vs a bad one. Creative strategists make better decisions when they're working off clean data and with better media buyers, because the scaled ads are actual winners. Hope this helps. What others have I missed?

When brands talk about poor Meta performance, nine times out of ten the root cause isn’t targeting or creative or even budget. It’s instability. Meta’s algorithm learns who converts based on consistent signals. When you change core elements like targeting, budgets, forms or creative every few days, the system can’t hold onto those signals. It keeps re-entering the learning phase. It loses its footing. And it has to rebuild the entire audience understanding from scratch. The result is predictable: 🔺 Higher CPLs 🔺 Lower volume 🔺 Erratic day-to-day performance 🔺 Inconsistent data that makes it impossible to scale Most of the time, the issue isn’t the campaign. It’s the constant tinkering. Here’s the part most teams underestimate: Even strong campaigns can’t stabilize if they get reshaped every week. Budget swings that jump from thousands per day overnight. Targeting changes that reset delivery. Form updates that alter conversion behavior. New creative structures introduced before the system has even finished learning the last batch. Every one of those resets forces the algorithm back to zero. What actually works is simple, but it requires discipline: 1️⃣ Plan changes deliberately 2️⃣ Implement them gradually 3️⃣ Give the campaigns 2–3 weeks of uninterrupted time to stabilize 4️⃣ Let Meta collect new learnings before making the next structural shift When you operate with stability, CPL comes down, volume smooths out, and scaling becomes far more predictable. When you operate in reactive mode, the platform is permanently stuck trying to relearn what you’ve just changed. Great media isn’t just about strategy. It’s about respecting the operating system you’re playing inside of. If you want predictable performance, you need predictable signals. Stability isn’t optional. It’s the entire game.