Ad and Mobile Performance

Meta & Google dont want you to have control anymore - and maybe its a good thing! The two biggest ad platforms have fundamentally changed how ads get delivered. Here's what happened: Google just integrated VEO 3 - its most advanced video generation model - directly inside Google Ads Asset Studio for free. It went from a developer-only tool in May 2025 to being inside every advertiser's dashboard by February 2026. → No shoot → No big production team → Far less budget than traditional video production. You generate the video inside the ad account itself. This combined with the push towards Pmax & Demand Gen, means Search is likely to get really expensive in the coming quarters. At Social Beat, we've already started testing this for clients. The speed is something else. On the Meta side, something even bigger rolled out in late 2024 - and by October 2025, it had gone global. They deployed Andromeda - an AI retrieval system that changed how every ad gets ranked and delivered. Before Andromeda, your targeting mostly decided who saw your ad. Now your ‘creative’ is the main signal that decides who gets to see it. Here's how it works: 📍 Andromeda scans every ad - visuals, copy, and audio - before it enters the auction. 📍 Weak‑quality creative often doesn’t get shown or gets heavily filtered, regardless of budget. 📍 Advertisers who adapted early are seeing upto 22% higher ROAS in many cases. 📍 Those running the same creatives for months are watching CPMs rise and performance drop. Both platforms are sending the same signal. Creative volume and diversity are now your biggest competitive edge. Not budget or targeting. For agencies, this changes what you need to be good at. If you can't produce high-quality creative at speed, your clients will pay more and get less.

Meta just replaced interest stacking with a text box. What Meta Is Really Changing Meta is moving from manual interest stacking → to AI-driven audience interpretation. Before: Select interests manually Narrow by behavior Layer demographics Try to “hack” the perfect combination Now: You describe the audience in natural language Meta interprets intent using AI Algorithm finds matching behavior patterns This is similar to how Google Performance Max shifted targeting from keywords to signals. 🎯 Why This Is a Big Deal for Advertisers 1️⃣ Targeting Is Becoming “Signal-Based,” Not “Interest-Based” When you type: “Startup founders scaling with paid ads” Meta doesn’t just match the word “startup.” It analyzes: Engagement behavior Content interaction Pixel data Video watch patterns Purchase intent signals This means targeting becomes dynamic, not static. 2️⃣ Creative Is Now the REAL Targeting This is the most important shift. If your creative clearly speaks to: First-time home buyers Gym beginners SaaS founders Real estate investors Meta’s AI learns from: Who stops scrolling Who watches 50%+ Who clicks Who converts The system then expands toward similar behavior clusters. Broad audience + strong messaging = scale. 3️⃣ Interest Layering Will Lose Power Over Time Stacking 5–6 interests used to feel “smart.” But in reality: It limited scale It slowed learning It increased CPM It delayed optimization Now Meta wants: Clear audience intent Strong pixel data Strong creatives Broader targeting This shortens learning time. ⚠️ What This Means for Performance Marketers For someone like you (who already tests multiple campaigns and creatives), this is actually an advantage. Your focus should now shift toward: 🔹 1. Message Clarity Instead of hunting interests: Write precise audience descriptions Build ads that speak directly to one persona 🔹 2. Creative Testing Over Audience Testing Old testing: 5 audiences × 1 creative New testing: 1–2 broad audiences × 5–8 creatives Creative becomes the targeting filter. 🔹 3. Better Pixel Data Becomes Critical Meta relies more on: Website conversions Engagement signals High-quality events Poor tracking = poor optimization. 🚀 The Real Strategy Going Forward Here’s what will likely win in 2026 Meta Ads: Broad targeting Strong, persona-specific creatives Clear conversion events Faster creative iteration cycles AI-guided scaling Manual targeting is slowly becoming obsolete. The advertisers who understand messaging psychology + data interpretation will dominate.

Attribution is overrated. Incrementality is what actually matters Every new-age brand wants to know what’s working. Meta ROAS is looking good. CAC is steady. Revenue is growing But here’s the truth: Your Meta ad might get the conversion. But did it cause the conversion? That’s the difference between attribution and incrementality. Most dashboards, attribution tools, and agency reports stop at attribution. But if you’re a brand selling across Amazon, Flipkart, GT, MT, Q-com, and D2C—pure attribution will always lie to you Because the sale might happen on Amazon. But it might have been nudged by a Meta video or a YouTube bumper ad 4 days ago. You don’t need a full-blown Marketing Mix Model to get started. There are simpler, street-smart ways to directionally understand what’s working—and what’s not. Here are 4 that have worked for us at Atomberg: 1. Geo Split Testing Pick two similar markets. Run campaigns in one. Don’t run in the other. Then track: • Branded search volume • Sell-through on marketplaces • Secondary sales from GT counters If the test market moves faster than the control, you’re seeing true lift. That’s incrementality. 2. First-Time Buyer Growth vs Returning Buyer Growth Track whether your growth is coming from first-time buyers or repeats. If your campaigns are just bringing back old customers—you’re not creating net new demand. But if there’s a spike in new buyers across Amazon, Flipkart, D2C—your campaigns are likely working at an incremental level 3. Paid Traffic vs Organic Trend Lines If paid traffic, clicks and spends are going up—but your organic sales or branded search isn’t moving—you’re likely just harvesting demand that already existed. But if organic lifts alongside paid—your ads are creating interest. Not just closing it. Directionally, this is one of the simplest sanity checks most teams ignore. 4. Channel Crossover + Offline Signal Mapping Your Meta ad may not show up in last-click attribution. But it might have nudged the consumer to visit your store or buy on Amazon. You can detect this through: • Post-purchase surveys (Where did you first hear about us?) • Branded search + store footfall spikes in campaign-active cities • And most powerfully—offline signals passed back to Meta At Atomberg, we pass back data from installations and warranty registrations—including pincode and purchase timelines Sometimes, we’re even able to identify this at a unique customer level through their cookies for warranty registration This has helped us understand true incrementality of perf marketing campaigns even for offline sales If you’re only measuring ROAS, you might scale what’s only taking credit for sale about to happen anyway If you chase incrementality, you’ll scale what’s working. For more details, read the full post- link in first comment.

Introducing Insights in Chrome DevTools Performance panel! Many web developers know the power of the Chrome DevTools Performance panel, but navigating its wealth of data to pinpoint issues can be daunting. While tools like Lighthouse provide great summaries, they often lack the context of when and where issues occur within a full performance trace. On the Chrome team we're bridging this gap with the new "Insights sidebar" directly within the Performance panel. Read all about it: https://lnkd.in/gGd3bkPw This exciting feature integrates Lighthouse-style analysis right into your workflow. After recording a performance trace, the Insights sidebar appears, offering actionable recommendations. Crucially, it doesn't just list potential problems but highlights relevant events and overlays explanations directly on the performance timeline. Hover over an insight like "LCP by phase," "Render blocking requests" or "Layout shift culprits" to visually connect the suggestion to the specific moments in your trace. The sidebar covers key areas like Largest Contentful Paint (LCP) optimization (including phase breakdowns and request discovery), Interaction to Next Paint (INP) analysis (like DOM size impact and forced reflows), Cumulative Layout Shift (CLS) culprits, and general page load issues such as third-party impact and image optimization. It's designed to make performance debugging more intuitive by linking high-level insights to the granular data, helping you improve Core Web Vitals and overall user experience more effectively. Check out the Insights sidebar in the latest Chrome versions (it's been evolving since Chrome 131!). It’s a fantastic step towards making complex performance analysis more accessible. Give it a try on your next performance audit! #softwareengineering #programming #ai

The silent killer of Meta Ads performance is repetition. Every advertiser fears audience fatigue, but few measure it properly. Frequency over 4 is often the first warning sign that your ads are wearing thin. Cost per click begins to rise, and engagement drops off. Set up a weekly check in Ads Manager. Look at frequency, creative age, and CTR trend together. If performance is sliding, rotate in new hooks or angles rather than rewriting the entire ad. Even small creative refreshes can reset engagement and protect brand health. Audiences do not mind seeing your ad again. They mind seeing the same idea without evolution. How often are you reviewing your frequency data? #MetaAds #PaidSocial #FacebookAds #DigitalMarketing #MarketingStrategy

More Ad Spend ≠ More Sales Scaling is a trap that no one talks about. Most marketers think scaling is simple: Increase ad spend → Get more customers → Grow revenue. But that’s not how it works. In fact, blindly increasing budget is one of the fastest ways to kill your ad performance. Here’s why: 1. Rising CAC (Customer Acquisition Cost) – More budget means entering higher-cost auctions and reaching less-qualified audiences. If your targeting, creatives, and funnel aren’t optimized, you’re just paying more for worse results. 2. Creative Fatigue – Scaling too fast with the same ad creatives leads to audience burnout. People stop engaging, CTR drops, and suddenly, your winning ad becomes a money pit. 3. Lack of Offer Optimization – If your offer doesn’t convert at a small scale, spending more won’t fix it. It's the classic problem of a poor product/service cannot be fixed with great performance marketing strategy. 4. Misleading ROAS Metrics – A campaign might look profitable at ₹ 10000/day but break down at ₹50000/day due to diminishing returns. If you’re not tracking LTV and profitability, you could be scaling unprofitably. So what should you do instead? 1. Test Before You Scale – Validate your offer, audience, and creatives before increasing spend. 2. Scale in Stages – Increase budget incrementally while monitoring CAC and conversion rates. 3. Optimize Your Funnel First – If your website, checkout process, or backend conversion flow isn’t solid, no amount of ad spend will save you. Scaling isn’t just about spending more. It’s about spending smarter. Have you seen this happen before?

ROAS↓ CAC↑ Most performance marketers know what to do next: check the funnel. But.. Even then, they miss something obvious. Let me explain. Let’s say I ask, “ROAS has dropped by 30%, what do you do?” They jump straight to diagnosing funnel drop-offs. They spot that click to payment has gone down. And now they get obsessed with the landing page or the journey post-click. But here’s the thing: Just because click-to-payment fell doesn’t always mean it’s a landing page problem. It could also mean: → The kind of users landing on the page have changed. → The quality of traffic has dropped. So while fixing that specific funnel step is important… Don’t go blind to the steps before it. Sometimes, the issue isn't in the funnel. It's in the audience that enters it. Diagnose holistically. Not just where the leak is showing but where the leak might be starting. Now, next time if someone says CTR% has gone down Let's jam all the possible reasons other than creative in comment 👇 #PerformanceMarketing #MetaAds #FbAds #GoogleAds

Looking to diversify beyond Meta/Google ads? Start here: The secrets out - Top-performing brands are slowly starting to shift towards a more holistic advertising approach. On top of Meta and Google, they’re layering: - CTV - Mobile app - Display ads All strategically to build a high-performing, full-funnel system. Here’s a break-down of what these look like: 1️⃣ CTV (Connected TV) → Awareness & Brand Lift Think smart TVs, streaming platforms, and premium inventory. We repurpose YouTube content for high-impact placements where audiences are deeply engaged. CTV isn’t about clicks - It’s about planting a brand in a consumer’s mind and making them more likely to convert later. 2️⃣ Mobile App Ads → Engagement & Consideration Mobile users spend more time in apps than anywhere else. We repurpose TikTok & Instagram-style vertical videos to seamlessly fit into app environments. These placements are non-disruptive, high-retention, and drive mid-funnel engagement. 3️⃣ Display Ads → Retargeting & Direct Response Display is the backbone of performance marketing. Static banners are served across the open web, ensuring brands stay in front of potential customers no matter where they browse. We retarget CTV and mobile app viewers to push them down the funnel and drive conversions. The key? Each format compliments the others. Most brands rely on siloed ad strategies - Programmatic brings them together under one roof, tracking user journeys across multiple touchpoints and optimizing holistically. If you’re still relying on Meta & Google alone, you’re playing with blind spots in your funnel.

🚀 𝗚𝗠𝗟 𝟮𝟬𝟮𝟱 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀: 𝗪𝗵𝗮𝘁’𝘀 𝗡𝗲𝘄 𝗶𝗻 𝗚𝗼𝗼𝗴𝗹𝗲 𝗔𝗱𝘀 & 𝗔𝗜 Google Marketing Live 2025 has left us with some game-changing updates. If you’re in the SaaS or growth marketing space, this is BIG. Here’s a quick breakdown of what caught my attention: 𝗔𝗱𝘀 + 𝗔𝗜 → AI Overviews now feature ads (desktop in the US, mobile in select markets). → Ads in AI Mode: Experiments are rolling out for placements directly in AI-powered search. → AI Max for Search Campaigns: Promises 27% better performance than exact match. → Smart Bidding now supports flexible ROAS targets (finally, more control!). → AI Agents (coming soon): Think of them as your co-pilot for campaign creation, optimization, and real-time troubleshooting. 𝗦𝗵𝗼𝗽𝗽𝗶𝗻𝗴 & 𝗖𝗼𝗺𝗺𝗲𝗿𝗰𝗲 → Try-on Shopping & One-click Checkout are rolling out (as teased at I/O). → A/B testing for product titles and shopping experiences is now live. → Video ads are expanding: Search, Shopping, and even Shoppable Ads on connected TV. → Retailers can now sell their 1P data directly to advertisers through the new Commerce Media Suite. 𝗖𝗮𝗺𝗽𝗮𝗶𝗴𝗻 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 → PMax: Over 90 improvements = 10% more conversions (with better reporting). → Demand Gen: 26% better cost-efficiency with 60+ updates. → New Customer Acquisition Goal is on its way. → Channel Performance Reporting (PMax) is now in open beta, so you can finally see how each channel performs. 𝗧𝗼𝗼𝗹𝘀 & 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 → Powerpack bundles PMAX, AI-powered search ads, and Demand Gen into one performance engine. → Google Ads Data Manager now offers tailored campaign recommendations. → Enhanced Attribution in GA4 provides deeper insights across platforms like Search, YouTube, and Display. 𝗧𝗵𝗲 𝗴𝗼𝗮𝗹 𝗶𝘀 𝗰𝗹𝗲𝗮𝗿: 𝗚𝗼𝗼𝗴𝗹𝗲 𝗔𝗱𝘀 𝗶𝘀 𝗲𝘃𝗼𝗹𝘃𝗶𝗻𝗴 𝗶𝗻𝘁𝗼 𝗮 𝘀𝗺𝗮𝗿𝘁𝗲𝗿, 𝗔𝗜-𝗱𝗿𝗶𝘃𝗲𝗻 𝗰𝗼-𝗽𝗶𝗹𝗼𝘁 𝗳𝗼𝗿 𝗺𝗮𝗿𝗸𝗲𝘁𝗲𝗿𝘀. What excites me most? The idea of conversational AI agents transforming campaign management. Imagine fewer manual tweaks and more strategic decisions. Which update are you most eager to try? Curious to hear how you plan to incorporate these into your strategies!

90% PDPs have invisible friction. It's doesn't scream. But it shows up in your metrics. Things like: – Low scroll through images – Low option selection – Low add to carts Silently impacting your revenue and eventually profits. In this post, I'll be sharing 9 small shifts reduce friction, and as a result improve your conversion rate. Here's what I recommend: 1. Keep the product name, description, reviews above the product image. Usually visitors scroll till the image. Making your add-to-cart appear higher up. Also makes your options (like colors) closer to the product image. 2. Add a badge that helps with decision making. You want the visitor to feel this is the right product for their need. So if they're shopping for a "work for home" chair, the badge can reassure them with that. 3. Show image thumbnails under the main image. This helps visitors know the content of your images. Have educational content or lifestyle images? Show the thumbnails. 4. Bullets > paragraphs. Use bullets. Keep the shorter sentences first and make them longer with each point. Makes it easier to read. 5. Instead of just saying "Color", say "Select Color". Add an action verb. This improves engagement rate with the options. If your image changes with the option, make sure they both are in the same fold. 6. Create urgency for color variations. If a few are running low on stock, mention how many are left. This create a natural want for the product as it's low in quantity and that's probably as it's a best selling color. 7. Avoid adding any "extra" options before add to cart CTA. Like accessories. Keep this AFTER your CTA. You wan the add to cart button to show up early and for them to add without a lot of decision making. 8. Show visual features. Do this instead of text blocks. These features can be further explained with supporting content. Do this before your accordions as these are your product's highlights. 9. Add accordions about warranty, returns. Especially if your product is in tech, home products. Check your website to see what % of visitors interact with your images, options and description before they add to cart. If that's less than 10%, you might want to implement the above strategies. Found this helpful? Let me know in the comments.