Ayush

Started my journey as a YouTube Thumbnail Designer - Worked with a lot of content creators - Got into Photo manipulation and loved using Photoshop Still felt like I could be more impactful, in terms of my skills and strategy. Was always fond of Meta ads but didn't know how everything works in there! Met Karlo online and joined @ecomtalent since then - Learned the basic marketing fundamentals + how to make ads from scratch and much more - Got my first very big client from the community for whom I worked as a Part-time Video editor - Designed statics which actually converted and got results - Now on the path to be a killer creative strategist by leveraging AI + buyer psychology Did a rebrand from @ash_dznss - @ayush_creates

@kamal_razzak When everything depends on one person it just stops growing the moment they step away

agencies that scale past £1M/year don't hire faster. they document better. playbooks > people. if your best work can't be replicated without you, you have built a job, not a business.

@andrejtumo Making calls that early just messes everything up when the buying cycle is way longer

Most e-com founders check ROAS on Monday and make budget decisions by Tuesday. Their customer takes 60 days to buy. You're reading the wrong month.

@dtcprophet Volume goes up fast but still need someone picking what actually deserves to run

You can pretty easily automate this with Nano Banana 2 right in Claude Code to generate 30-40 very high quality static ad creatives daily Almost every single creative is ready to launch into our account and we can easily 2-3x the volume of it I previously had it as a Claude Project but realized it could be fully automated in code given how good the output ads are To build it in Claude Code, you first need to create or gather all of these assets: - Brand overview/DNA doc - List of ~50 template ad generate prompts - Folder of customer reviews, PPS responses, persona docs, marketing materials, etc - Product source images (product renders, PDP images) - 5-6 existing winning static ads - 5-6 existing losing static ads The output ads you get are a function of the inputs you give it, you should spend a lot of time building these and I highly suggest not defaulting to AI to build them, especially the brand DNA doc Give it bad info and you’ll get bad ads in return For the original ad prompt template sheet, I found it useful to have them be 30 completely different styles and designs (offer ad, big headline, UGC/native, bullet point benefits, comparisons, etc...) Then it’s very simply to build actually. The flow is: 1. Read all source docs 2. Read existing winning/losing ads 3. Load product reference images 4. Load ad gen prompt template 5. Send to gemini text model 6. Gemini builds 30-40 new ad prompts 7. Run through nano banana 2 with reference images 8. Save all assets Below is an image of the step by step automation in Claude code, you can probably just ask it to build this for you The only external thing you’ll need to get is a Gemini API key for the text and image models Then the script will run whenever you schedule it, create 30-40 unique ad generation prompts for you, generate the static ads through nano banana and then save them wherever you want I have everything running on a mac mini so it runs before I wake up and I have 30+ new ads to look at first thing in the AM I also built in our ad naming conventions into the script so that it automatically names our ads in the file name, so I can load them into Adnova and launch them very fast (2-3 mins) The only non-automated step in this is getting the image files from local device into the platform media library or ad launcher tool but that takes like 60 seconds per batch It costs ~$1/day and takes 10-15 minutes

@rokhladnik Things look fine at low spend then everything breaks the moment you push it harder

Scaling doesn’t expose your winners. It exposes your bottlenecks. More ad spend won’t fix: ➡️ weak landing pages ➡️ unclear product messaging ➡️ limited creative variety ➡️ broken attribution Every account looks efficient at low spend. Real marketing starts when you try to scale.

@FedotOff90 Everyone crowding one place while other markets just sitting there ready to convert

Everyone's fighting over the same US customers. CPMs at $11+. CAC up 60% in 5 years. Competition from brands 10x your size. Meanwhile the UK, Australia, and Canada are sitting there. English-speaking. Credit cards out. Proven US ad angles that work almost verbatim. You don't need a new product. You don't need new creatives. You don't need a new offer. You need a new zip code in your campaign settings. Most operators are too US-focused to see it. That's the opportunity.

@antonioventre_ Everyone sees the jump but not the weeks where nothing was working

The $9K to $150K month case study had a backstory nobody sees. Months 1 to 3 were hard. > Below target ROAS. > Client getting anxious. > Pressure to justify the spend. We were testing offers. > Buy 3 get 1 free. > Buy 4 get 1 free. > Free shipping thresholds. Nothing was crushing it immediately. We could have panicked and changed strategy. Most agencies would have. Instead we kept testing. Kept reading the data. Kept iterating. Month 4: $68K revenue. Something was clicking. Month 5: $150K revenue. 4.26x ROAS. Production could not keep up. The difference between a $150K month and a $9K month was not one magic creative. It was three months of discipline, patience, and trusting the process when the numbers were not exciting yet.

@oliverwhudson Most people just react to numbers dropping instead of figuring out where things are actually breaking

@ecombatman First sale is just the entry point the real money comes from what happens after

9/10 customers who buy a $99 product today will spend significantly more with you over the next 30 days. that’s the pattern I keep seeing across $500K/month stores: 1/ ads bring in traffic 2/ a low-ticket product converts them into a buyer 3/ a core offer increases AOV 4/ backend (upsells, email, SMS) drives real profit each step gets easier because the last one builds trust. one product is a transaction. a customer journey is a business.

@benradack You think you’re testing one thing but the setup is changing it behind the scenes

One of the most common mistakes I see is running "audience tests" that aren't actually audience tests. Here's what I mean. Someone sets up a retargeting campaign. They build their audience like normal... But they leave audience suggestions on 🆘 That's not a retargeting campaign anymore. Audience suggestions tells Meta "start here but go wherever you want." Meta takes your audience as a loose suggestion and goes broad. You can confirm this yourself right now: → Go to any campaign where you set a specific audience with audience suggestions on → Check your audience segment breakdowns → You'll see that even if you told Meta to target existing customers, most of the spend went to new customers You're not testing audiences. You're running broad with extra steps. If you actually want to target a specific audience: → Turn off audience suggestions → Now Meta has to stay within the audience you set Check your breakdowns. You might be surprised where your spend is actually going.

@mouss_us People focus on the ad itself and forget the comment section can make or break it

New service is doing numbers Comments under ads are literally overpowering the scaling of some campaigns Same creative and same budget Different comment section → completely different results If you’re running ads and ignoring this layer, you’re leaving money on the table DM to get targeted comments under your ads

Most people see a winning ad and think: “Let’s recreate it.” That’s the wrong move. Here are 10 questions I ask when I find competitors’ winning ads: 1. What proof builds trust? 2. What tone is the ad using? 3. What action is being pushed? 4. What promise is being made? 5. What pain point is highlighted? 6. Who is this ad clearly targeting? 7. What emotion does it trigger first? 8. Why does the hook stop the scroll? 9. What psychological trigger is used? 10. What stage of awareness is this for? Never copy-paste the same ad, Instead analyze why it worked, and copy that framework.

@FedotOff90 After a point building from scratch just looks slower than buying something that’s already working

Spent an hour with a guy who's done $400M in ecom over 10 years. I asked him what he'd do differently if he started over today. He said he'd never build a brand again. He'd just find brands already doing $3-5M/year with subs and good retention, acquire them, scale them to $30-50M, then exit. "I spent 10 years building one brand. I could've built 10 in 5." The best operators I know aren't building from scratch anymore. They're plugging into what's already working.

@williamkast_ Everyone blames the creatives but the way they’re coming up with them is the real issue

Most brands I audit don't have an ad creative problem. They have a process problem. How most teams work: 1. They look at what competitors are running 2. They pick a format that's trending 3. They brief an editor 4. They launch 5-10 ads 5. Maybe one works. They don't really know why. Then they try to make more "like the winner" by changing the hook or the creator. It underperforms. Meanwhile, the 9 losers from the last batch? Nobody analyzed them. That's how you burn money on creatives. The three biggest mistakes I keep seeing: 1) Misunderstanding 'real research' They don't know who their customer really is. They don't know what awareness stage to write for. They don't have real personas built from actual customer data. So every ad is a guess -not a clear hypothesis. 2) No hypotheses They launch ads and hope the algorithm figures it out. There's no structure to what they're testing or why. Every ad should test one specific thing: a persona, an awareness stage, an angle, a desire. So when it works or fails, you actually learn something. 3 split testing versions. 3) Surface-level iterations Finding a winner and changing the hook 5 times is not an iteration. Real iteration means taking a winning angle and repackaging it into completely different formats. Podcast style, founder content, static, native, VSL, etc. Same message, different packaging. That gives Meta something genuinely different to work with. The fix isn't more ads. It's better research, structured testing, and real analysis of what works and what doesn't. Everything else is just expensive guessing.

@benradack Keeping it simple usually beats splitting everything into tiny pieces that fight each other

Today I consolidated our whitelisting ads into one ad set with our brand videos. My CBO performs better with fewer ad sets running. So instead of keeping whitelisting in its own ad set, I merged them together. Now the campaign has: → One ad set for statics → One ad set for whitelisting ads + standard videos The only reason I'm not combining everything into one ad set is because my static ads always eat the spend. Basically like one big black hole So I'm using min spend limits on the video ad set to force Meta to distribute budget more evenly. Keeps the campaign from getting top heavy with one ad set eating 80% of the budget. Fewer ad sets. Min spend limits to control distribution. Simple.

@karlocreates Scroll for a minute and it’s all noise so going back to actual work just makes more sense

Last 3 months: > open X > see everyone spamming random content about AI > close X > go back to the trenches > keep building towards our yearly business goals I feel like 99% of people on this app are distracted with shiny AI tools I can't be the only one who relates to this?

@Camicees Pulling ideas from outside your niche usually works better than copying the same people everyone else is watching

My 5-step process for pulling winning ideas from adjacent industries: 1/ List 5 related categories. 2/ Find their top-performing ads 3/ Extract the transcript 4/ Adapt it to your product with AI + your research doc 5/ Test the remix. Fresh angles. Zero guesswork.

@JustenEcom People celebrate the numbers that look good while ignoring the ones that actually matter

I track only 3 metrics. Revenue, profit margin, customer acquisition cost. Likes? Don't pay bills. Followers? Don't pay bills. Engagement rate? Doesn't pay bills. These 3 numbers tell me if I'm winning or losing. Vanity metrics look good on screenshots. These 3 metrics determine if I eat steak or ramen.

@FedotOff90 Everyone looking for some secret and she just kept showing up doing the boring stuff daily

Met a woman at a Miami dinner last week. Former nurse. No business background. She's doing $3.2M/year selling one skincare product. Started 2 years ago with $8k saved. Her entire growth strategy: she spends 1 hour every morning studying competitor ads in the Meta library. Puts her face on ads. No agency. No media buyer. Just her, a Canva account, and a relentless system for stealing what's already working. Her ROAS is 2.8x after 2 years of consistency. I asked her what most people get wrong. She said: "They want to be creative. I just want to be right." The best ecom operators aren't the most talented. They're just don't overthink and print.

@Idan_Frenkel8 Most people box these into one stage when they can actually work across the whole funnel

Recent observation: Unaware - Problem Aware can only be TOF However Product Aware - Most Aware CAN be TOF, MOF and BOF

@sourfraser They saw the gap and shipped something fast while everyone else still talking about it

More companies need to move like this. 

> See a problem. 
> Solve a problem. 
> Get it to customers.