Shamanth M. Rao’s Post

WTF Does “Fix the Product” Even Mean? 6 Questions to Assess Your App’s Readiness for Paid UA It’s frustrating to hear, “Fix the product before running user acquisition” - because it is unclear and amorphous. While that makes broad sense, what does that really mean for early-stage apps? After talking to hundreds of apps, we’ve put together a 6-question checklist to help assess if your product is ready for paid UA: 1️⃣ Is your activation rate strong? • Measure registration completion, FTUE completion, and free trial rates to see if users engage early on. 2️⃣ Is your organic traffic engaged? • Look at metrics like session length, session frequency, and daily session time to understand user engagement. 3️⃣ Are you hitting retention benchmarks? • Track your D1, D7, D30 retention for games, or monthly retention for subscription apps. 4️⃣ Are your monetization metrics solid? • Look at D7/D30 ARPU to ensure your monetization supports profitable UA. 5️⃣ Are your ratings and reviews strong? • Aim for a 4+ star rating to show users find real value in your product. 6️⃣ Is your app free from major bugs or tech issues? • Keep your crash rate below 1% to ensure a stable user experience. Key takeaway: Before you spend on paid UA, make sure your product is strong. If you’re not hitting these benchmarks, take time to fix the product first.

✅ Pika 1.5: Unleashing killer visual hooks for Performance Marketing ads 🎨 I’ve been exploring Pika 1.5, and the possibilities for ad hooks are mind-blowing. ✅ What’s possible now with Pika 1.5: • Effects like exploding, melting, and cake-ifying. • Build hooks based on prompts or images. • Thumbstopping visuals and effects. In this quick video, I walk you through a quick demo of how we’ve been using it on our team.

Are your incrementality tests leading you astray? (After $100mm in ad spend, here are the risks I see). “Dont trust the platforms. Measure incrementality.” - they say. Very valid, especially in the post-ATT world. But incrementality is not a silver bullet. Non-deterministic methods come with their own set of challenges. And if you arent careful, these can often lead to wasted spend or missed opportunities. Here’s what to watch out for: ❌ Hard to isolate impact of multiple sources/campaigns. ↳ If you run multiple campaigns/sources/geos at once, it’s not always easy to tell which one is driving the results. ↳ Be cautious about drawing conclusions too quickly. ❌ Creative impact is hard to isolate ↳ Incrementality analyses often struggle to account for smaller, creative changes. ↳This can skew your understanding of what’s really working. ❌ Platforms need time to learn ↳ Platforms need to accumulate data during their learning phase. ↳ Early results might not reflect the long-term performance. ❌ Results can be inconclusive ↳ Sometimes, incrementality testing doesn’t give you a clear answer. ↳ You might see positive results for installs, but negative ones for purchases. Key takeaway: Incrementality testing is crucial, but it’s not perfect - and nor is it for everyone. By making sure you account for these pitfalls, you can make smarter marketing decisions.

Stop spending $$$ on contextual ads(Twitter, Reddit, native ads, some DSPs) until you’ve seen this. Contextual targeting in mobile ad networks sounds great in theory. - Your ads show up in apps that seem relevant to your audience. - Some DSPs and native content networks tout this as a USP. - Surely this leads to great performance? But here’s the truth: ❌ Context is a poor predictor of performance. - Related content doesn’t mean users will purchase. - The connection between context and conversions is weak. - Any non-purchase thing is a poor predictor of performance. ✅ What really works? - Past purchase behavior is the best predictor of future performance. Why? - Because while context captures interest…. - Past purchase behavior captures the ability and willingness to spend. I may be interested in something but unwilling to spend on it. You want a user that is willing to spend $$$. Key takeaway: Look at contextual traffic(some DSPs, Twitter, Reddit, native content ad networks) ONLY after you’ve tapped out networks leaning on purchaser data.

Early stage apps: stop asking “what channels should I run ads on?” Many early stage founders ask this question. Their reasoning? - The more channels they run on, the lower their risk. - They get to target different types of users by targeting different channels. The catch? - Each channel needs a minimum number of conversions. - The more the conversions, the faster the algo ‘learns’ and performs. Multiple channels = none of them gets enough conversions, making them all perform worse. ✅ What works instead: 1️⃣ Focus on 1-2 SANs to concentrate your spend and provide enough conversions for the algorithms to perform. 2️⃣ Only diversify after you’ve fully maxed out these channels and have the budget to support further growth.

😓 The #1 reason why you might be working all day but getting nothing done(and how to kill this meeting-creep). 📆 We’ve all had those days: ↳ A 2 PM meeting for 30 mins. ↳ Then a 3 PM 'quick catch up' for 30 mins. ↳ And another 'deep dive' at 4 that makes you want to drown yourself. You finish one call and there's barely any time to focus. By the end, you’ve lost 6+ hours to fragmented tasks. Where the HELL did your entire day go? Not even talking about personal time. What is scary is that it's SO easy to let meeting-creep take over your calendar. Until it is a massive snowball ready to destroy everything in its sight. All it takes is a thoughtless yes. Which is why I recommend a level of ruthlessness in how you schedule meetings. The key? ✅ Batching meetings: ↳ Grouping leaves rest of your day free for deep work. ↳ Regain control of your time and mental space. ↳ And make time for personal life. In this quick video, I share some quick feedback with my team to help them(and myself) clean up some insane meeting creep.

😓 The #1 reason why you might be working all day but getting nothing done(and how to kill this meeting-creep). 📆 We’ve all had those days: ↳ A 2 PM meeting for 30 mins. ↳ Then a 3 PM 'quick catch up' for 30 mins. ↳ And another 'deep dive' at 4 that makes you want to drown yourself. You finish one call and there's barely any time to focus. By the end, you’ve lost 6+ hours to fragmented tasks. Where the HELL did your entire day go? Not even talking about personal time. What is scary is that it's SO easy to let meeting-creep take over your calendar. Until it is a massive snowball ready to destroy everything in its sight. All it takes is a thoughtless yes. Which is why I recommend a level of ruthlessness in how you schedule meetings. The key? ✅ Batching meetings: ↳ Grouping leaves rest of your day free for deep work. ↳ Regain control of your time and mental space. ↳ And make time for personal life. In this quick video, I share some quick feedback with my team to help them(and myself) clean up some insane meeting creep.

🔨 How to hammer down your Meta CPMs to improve performance(insights from a Meta Biz Partner w/ $100mm ad spend). 🤑 Many marketers think they’re running ads in isolation… → Believe algos evaluate ads in a vacuum. → They focus only on their performance metrics. → Think that focusing on their own ads drives performance. But the reality is, → you’re always competing against tons of other advertisers. → even though you don’t see their ads next to yours. → cos there are only a finite number of ad slots. Right: so how does that impact your day to day operations? → Given you’re competing with other advertisers, you want to focus on the way the algorithms ‘grade’ you. → How? ✅ What actually drives performance: Expected Action Value What is Expected Action Value? Meta’s ad auctions don’t just look at your ad in isolation. They calculate an Expected Action Value, predicting how likely users are to engage with your ad compared to other advertisers. Here’s what matters most: 1️⃣ Upstream metrics ↳ Ads that users engage with more (likes, comments, shares - and yes purchases) are seen as higher quality, boosting your Expected Action Value. 2️⃣ Relevance to Your Audience ↳ The more relevant your ad is to the target audience, the higher your Expected Action Value. 3️⃣ Downstream Engagement ↳ Ads that result in stronger downstream engagement(purchases, trials etc.) are weighted much more strongly in the expected action value calculus. ↳ So what happens downstream of the ad(your landing page, or app onboarding) matter as much as the ad itself. How to improve Expected Action Value: 🔹 Focus on creating ads that resonate deeply with your audience—solve their problems, speak their language. 🔹 Ensure your creative is tailored and speaks directly to your target audience’s needs, behaviors, and emotions. 🔹 Continuously test and optimize for downstream engagement - purchases and trials. The result of improved expected action value? Massively lower CPMs - and wayy stronger reach, unlocking ROAS and CPA improvements.

Stop measuring the impact of ASO keyword optimization all wrong. Here is the right way to do it. App Store Optimization (ASO) is often touted as a way to boost organic installs, but the question remains: How much impact does it really have? Something I see all too often is that keyword ranking improvements do NOT lead to more installs. Why? - You might improve rankings for a keyword, but the keyword has very low search volume. - The result? No organic uplift in your installs. This is all too common - and I often see: - Treating ASO as a set-it-and-forget-it strategy. - Relying on keyword optimization without tracking its actual impact on organic installs. - Expecting ASO to be a scaling strategy rather than an incremental improvement. ✅ Here is what truly works: 1️⃣ Track keyword performance over time ↳ Monitor the rankings of your app for specific keywords and track how these rankings change with each update. ↳ Identify which keywords drive the most visibility and traffic. 2️⃣ Measure the lift in organic installs ↳ Compare your organic traffic before and after ASO changes. ↳ This helps you understand the real impact keyword optimization has on organic installs. 3️⃣ Understand ASO’s limitations ↳ ASO can boost visibility, but it won’t single-handedly scale your app. Treat it as a complementary strategy, not a primary growth driver. Key takeaway: Keyword optimization can help improve visibility, but it’s crucial to track and quantify its impact to understand its true effectiveness. Remember, ASO can provide a solid baseline, but it isn’t a standalone strategy for scaling your app.

Sometimes we see ratings of apps plummet(we recently saw one go from 4.4 to well under 4). Scary. Here is how we turned things around. Oftentimes: - Marketers dont know where to begin addressing the problem. - Others try and run a barrage of prompts to incentivize better ratings. - Some drop money into ads, hoping that new users will rate their app better. ✅ Here’s what we did: 1️⃣ Stopped paid marketing and focused on fixing the app’s issues. 2️⃣ Identified highly engaged users and targeted them with rating prompts. 3️⃣ Ran small tests on user segments before scaling the successful strategies. The result? Ratings crept back up slowly but steadily - and started to approach their earlier baseline.