Ad Spend Efficiency Metrics

Your Google Ads Metrics Are Lying to You! 🚨 Most lead gen advertisers in India focus on CPL (Cost Per Lead), CPC, and CTR—thinking lower costs mean better results. But in 2025, a ₹500 lead is useless if it doesn’t convert into revenue. If you’re not tracking the right metrics, you might be: ❌ Generating ₹50 leads that never turn into customers ❌ Wasting budget on low-intent clicks ❌ Scaling campaigns based on vanity metrics Let’s fix that. The 5 Google Ads Metrics That You Can Consider for Lead Gen in 2025 1. Cost Per Qualified Lead (CPQL) > Cost Per Lead (CPL) Not all leads are equal. A high-intent lead is worth more than a random form fill. ✅ CPQL = Ad Spend / Sales-Qualified Leads (SQLs) 📊 If a ₹500 lead has a 40% close rate, it’s better than a ₹100 lead with a 5% close rate. 2. Lead-to-Customer Conversion Rate > Total Conversions 100 leads mean nothing if only 5 convert into paying customers. ✅ Formula: (Customers / Leads) * 100 📊 A high conversion rate means your campaigns are attracting the right audience. 3. Cost Per Revenue-Generating Lead > Cost Per Click (CPC) Clicks don’t pay the bills—customers do. ✅ If you spend ₹50,000 on ads and generate 50 SQLs, but only 5 turn into paying customers, what’s the real cost per acquisition? 📊 A ₹1,000 CPL is fine if it generates ₹50,000 in revenue per customer. 4. Pipeline Value > ROAS A campaign that delivers high-value deals is better than one with a high ROAS but small-ticket sales. ✅ Pipeline Value = Sum of potential revenue from all SQLs. 📊 Example: If Google Ads generates ₹5,00,000 in pipeline revenue from 100 SQLs, your ad spend should be based on revenue impact, not just CPL. 5. Revenue Per Lead (RPL) > Cost Per Lead (CPL) Instead of just tracking lead cost, track how much revenue each lead generates. ✅ Formula: Total Revenue from Ads / Number of Leads. 📊 If 10 leads at ₹500 each bring in ₹1,00,000 in sales, RPL = ₹10,000 per lead. That’s the real performance metric. 🚀 In 2025, successful lead gen advertisers in India are not just measuring lead volume, They’re tracking lead quality, conversion rates, and revenue impact. If you’re still optimizing for low CPL and dependent on sales to do most of the heavy lifting, It’s time to rethink your strategy. #digitalmarketing #leadgen #marketing

If you’re running conversion campaigns on Meta for your DTC brand, here’s one key metric you should be looking at regularly—but probably aren’t: Cost Per Incremental Reach. Most brands obsess over CPM and ROAS. But when CPM drops, it’s often because you're hitting the same people more frequently—not reaching new ones. That’s where performance starts to erode. Your frequency goes up, and conversions drop. You end up with inflated spend chasing a shrinking pool of users. To avoid this, here’s a simple routine to add: Go into Ads Manager > Breakdown > By Time > By Month. Add “Reach” and “Impressions” as columns. Compare total reach month over month for your conversion campaigns. Calculate Cost Per Reach = Spend/Reach. Further Track whether you’re getting incremental reach month on month or just spending more to re-engage the same users. For example: April Reach = 120,000 Apr+May Reach = 200,000 Incremental Reach = Apr+May Reach – April Reach 200,000 – 120,000 = 80,000 incremental users reached in May. Cost of incremental reach in May = 80,000/spend If your incremental reach is flat (or shrinking) month over month, it means you’re not reaching to new audience and hence not scaling. Let your lower funnel handle frequency. But make sure your Top funnel conversion strategy still expands your reach at a sustainable cost.

The correlation between 𝐀𝐂𝐎𝐒 and 𝐓𝐨𝐭𝐚𝐥 𝐀𝐂𝐎𝐒 (TACOS) is often debated in our industry. But if we step back and look at what's happening behind the metrics, we can identify the source of confusion and put this debate to rest. 𝐔𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐭𝐡𝐞 𝐂𝐨𝐫𝐫𝐞𝐥𝐚𝐭𝐢𝐨𝐧 🌐 𝐀𝐂𝐎𝐒 (Advertising Cost of Sales) measures the efficiency of your ad spend by comparing your ad spend to the revenue generated from ads. 𝐓𝐀𝐂𝐎𝐒 (Total Advertising Cost of Sales), on the other hand, considers your total revenue, including organic sales, giving a more comprehensive view of your ad efficiency. 𝐒𝐭𝐫𝐨𝐧𝐠 𝐂𝐨𝐫𝐫𝐞𝐥𝐚𝐭𝐢𝐨𝐧: If your ad campaigns are well-structured and driving truly 𝐢𝐧𝐜𝐫𝐞𝐦𝐞𝐧𝐭𝐚𝐥 sales (i.e., driving sales that wouldn't have happened organically), there should be a direct correlation between ACOS and TACOS. Efficient ads boost both metrics. 𝐑𝐞𝐚𝐥-𝐖𝐨𝐫𝐥𝐝 𝐈𝐧𝐬𝐢𝐠𝐡𝐭 🧠 We managed a brand where we saw ACOS double while TACOS decreased 30%. How? The previous management had gross organic cannibalization (~50% of all spend was going to VCPM Sponsored Display retargeting campaigns! 😱) By refining our sales attribution to avoid cannibalization and focusing on truly incremental sales, we made ACOS "real" again. 𝐊𝐞𝐲 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐞𝐬: 1. 𝐀𝐯𝐨𝐢𝐝 𝐂𝐚𝐧𝐧𝐢𝐛𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧: Ensure ads aren’t stealing organic sales. 2. 𝐅𝐨𝐜𝐮𝐬 𝐨𝐧 𝐍𝐨𝐧-𝐁𝐫𝐚𝐧𝐝 𝐊𝐞𝐲𝐰𝐨𝐫𝐝𝐬: Drive new, incremental traffic. 3. 𝐂𝐨𝐧𝐬𝐢𝐬𝐭𝐞𝐧𝐭 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠: Regularly review search term reports to optimize campaigns. By understanding and leveraging the correlation between ACOS and TACOS, you can gain a clearer picture of your ad efficiency and overall business health. Don’t get swayed by the myth that ACOS is just a vanity metric. When campaigns are created properly, ACOS becomes a vital part of the bigger picture. #amazonads #amazonppc #amazonbusiness #fba #ppc #bidoptimization

What’s the best North Star metric for your marketing program? Contribution Margin? MER? LTV:CAC? Literally, none of them. At the executive level, the real North Star is always net profit. That’s what the board cares about. That’s what determines company valuation. But most marketing teams never see that number. They’re asked to "drive profitable growth" while working with data from in-platform dashboards that don’t reflect true business outcomes. So we compromise. We track revenue, but that ignores margin. It rewards you for selling the wrong products. Then we move to MER (Marketing Efficiency Ratio) or Contribution Margin, which are both improvements from platform metrics but a step down from net revenue or profit. But those metrics are reactive. You only see changes after they happen. They tell you what happened, not why. The most effective marketers do something different. They stop looking for a perfect, all-in-one metric. They build a hierarchy of metrics instead. What is a metric hierarchy you may ask? Well, I'll tell you. It’s a layered system where each metric plays a different role. They build on each other. The lower levels help you influence the higher ones. Here’s a simplified version: -> Top layer (True North Star): Net Profit, EBITDA --> Holistic Marketing Program Efficiency: Contribution Margin, MER, GPLTV:CAC ---> Incremental Contribution: Channel-level incrementality like iROAS, iCPO, incremental cost per new customer, CPIA) ----> Ad Channel Performance: Media metrics (CPM, CTR, CVR, ROAS, GPT etc.) Each layer gets more tactical as you move down, but that doesn’t mean it’s less important. These are the levers you can actually pull. CPM, CTR, and CVR are often dismissed as vanity metrics. And on their own, they don’t mean much. But together, they help diagnose performance issues. If CTR drops, your creative might be stale. If CVR is low, maybe the landing page isn’t working. These are your early warning signs. ROAS sits one layer up, but it can be misleading too. Especially when platforms over-attribute conversions or mix in branded traffic. That’s why metrics like GPT (gross profit per transaction) or iROAS (incremental return on ad spend) are more reliable. They help show whether the revenue was both profitable and caused by the ad spend. Let’s say your MER target is 3x. That doesn’t mean every platform needs to hit 3x ROAS. Maybe Meta has an iROAS of 4x and Google is at 1.75x. Now you know to maximize MER you need to set ROAS goals of: ((MER GOAL) / Platform Incrementality Factor = New ROAS Goal) The key is knowing which platform is driving actual contribution. These tactical insights inform smarter ROAS targets. That affects MER, which affects contribution margin, which ultimately impacts net profit. It all rolls up. But you need to start from the bottom and work your way up.

The difference between profitable and failing Google Ads accounts often comes down to one thing: which metrics you're tracking. I've optimized accounts from $10K to $100K+ monthly spend, and the process always starts with setting up the right data columns. Most advertisers focus on vanity metrics while missing the numbers that actually determine profitability. For successful campaign management, you need to configure your Google Ads dashboard to show: conversions, cost per conversion, cost, impressions, clicks, and conversion rate. But there's a critical issue Google doesn't tell you about: conversion reporting lag. Your standard conversions column often shows incomplete data for recent periods (sometimes missing up to 30% of conversions!). This creates a dangerous situation where you might pause or reduce budget on campaigns that are actually hitting your targets. The fix is simple but powerful: create a custom column for "CPA by Conversion Time" using cost ÷ conversions by conversion time. This gives you accurate, real-time cost per conversion data rather than relying on delayed reporting. For e-commerce accounts, do the same with "ROAS by Conversion Time" to see your true return on ad spend as it happens. Also vital: monitor your Search Impression Share to identify scaling opportunities where you can capture more market share while maintaining profitability. If you're hitting your CPA targets with only 20-30% impression share, you're leaving significant growth potential on the table. Setting up these columns takes just minutes but transforms how you make decisions in your account. Comment "COLUMNS" below to get my complete Google Ads metrics setup guide with step-by-step instructions for both lead gen and e-commerce accounts. (Please send a connection request if we're not already connected so I can share it directly!) #GoogleAdsMetrics #PPCOptimization #DigitalAdvertising #PPC #SEA #SEM #googleadscolumns

Are you analysing your advertising efficiency metrics and wondering how to improve? There are four simple changes you can implement today that will transform your business: 🛑 Stop segmenting feeds by product types or brands. 💡 Instead, segment your feeds by profit velocity. The higher the profit velocity, the more budget should be allocated to it. 🛑 Stop bidding in Google Ads for revenue. 💡 Google’s AI is smart enough to incorporate profit data. If you optimise for profit, you'll know it’s profitable. 🛑 Stop upselling solely for AOV. Not all revenue is created equal. 💡 Focus on upselling for gross profit and cash conversion instead. 🛑 Letting browsers click ads to comeback. 💡Turn more browsers into shoppers by improving your identity data back into Klaviyo, reducing wasted ad clicks. 💵 What does ROI look like when you make these changes? 120% higher gross profit on ad spend 130% higher ROAS 20% more revenue attributed to flows, or a 160% uplift 🎙️ PS: We believe inferred consent is not enough. We only operate with explicit consent data.

Q2 Amazon Ad Type Performance 👀 We analyzed quarter-over-quarter performance by ad type, and here’s what stood out 👇 📦 Sponsored Products (SP) → Spend nearly doubled (+97%) → Revenue grew 150% → CVR jumped to 16.4% → CPC slightly increased to $1.35, but the conversion gains more than made up for it ✅ This is what happens when structure, creative, and intent all align. 🧠 Sponsored Display (SD) → Spend dropped 73% → RoAS more than doubled (+124%) → CVR up 51% to 18.7% → CPC decreased slightly ✅ Highly targeted, bottom-funnel strategy paying off as we transition budgets to DSP 🎯 Sponsored Brands (SB) → Revenue up 136% with 113% more orders → RoAS improved to 4.76 → CPC rose modestly, but CVR growth offset the cost ✅ Stronger creative rotation and intent-based targeting are working. 🎥 Sponsored Brands Video (SBV) → Click-through rate hit 1.1% (highest of any ad type) → CVR up to 15.4% → CPC is higher at $1.85, but efficiency remains strong ✅ SBV continues to be a top performer when creative is dialed in. ⚠️ AUTO campaigns → Spend dropped 20% → CVR lagged at 10.8%, CTR flat ✅ Still a valuable source of data - but less effective for scaling without structure. BONUS: 📦 Off-Amazon Placements (Q1 → Q2): → Spend increased 52% → Revenue jumped 93% → Clicks up 125% → CPC dropped 33% → RoAS improved 27% BUT… ⚠️ Conversion Rate dropped from 5.0% to 3.2% 🧠 What this tells us: Off-Amazon is scaling reach and efficiency, but intent is lower—and creative/landing page alignment matters more than ever.