Founder-led content and building in public
Personal brands on X and LinkedIn, build-in-public updates, SEO/content marketing and authentic posting as distribution channels.
30%
Best tweets about Growth Hacking
50 Best Tweets About Growth Hacking (2026)
A curated collection of the sharpest, most-shared X posts about growth hacking—saved so you do not have to dig through the timeline yourself. Updated every two weeks.
Unconventional tactics that actually moved a metric, told by the person who ran them.
- Creators
- 44
- Updated
Original Xholic analysis
What 50 top Growth Hacking posts reveal
A largely supportive conversation (76% supportive stance) in which operators share self-reported tactics: engineered launch videos, manual first-customer work, creative-volume paid ads, and retention fixes. Viral launches and short-form video carry the highest theme median score (21.28). A minority strand argues that growth only works on top of a product people want and that spend must be proven incremental.
- Dominant tone
- Positive
- Median score
- 10.0
- Leading format
- Opinion
- Recent posts
- 16%
74% of posts
All-time engagement
24% of posts
Published in 90 days
Conversation map
The themes creators return to
Growth philosophy and AI-era shifts
Views on PMF vs growth, rapid experimentation culture, unconventional GTM, AEO/LLM influence and how AI reshapes growth teams.
30%
Scrappy tactics for first customers
Manual outreach, Reddit and community replies, competitor-mention hijacking, doing things that don't scale, ICP discovery and pricing tactics.
26%
Paid acquisition and creative testing
Running Apple, Meta, TikTok and Google ads: creative volume, budget scaling rules, ROAS targets, campaign structure and channel dependency.
20%
Growth loops, flywheels and referrals
Self-reinforcing systems like case-study flywheels, creator-driven loops, referral and affiliate programs, and word-of-mouth compounding.
18%
Incrementality and attribution measurement
Holdout and geo tests, MMM, UTM tracking, dashboards, LTV and new-customer metrics to prove spend drives real, attributable growth.
18%
Retention and churn as growth lever
Cohort analysis, post-purchase flows, churn and monetization showing that keeping and monetizing customers beats chasing new ones.
12%
Viral launches and short-form video
Engineering viral launch posts, TikTok/Reels creator programs, cloning proven formats and hooks, and posting volume to drive organic reach and installs.
12%
Tone and stance
SentimentPositive leads
Author postureSupportive leads
Performance benchmark
- Median likes
- 20
- Median reposts
- 1
- Median replies
- 7
- Median views
- 1.8K
Posts with media make up 40% of this collection. Their median all-time score is 10.3, compared with 8.58 for text-only posts.
Format mix
- Opinion24% · score 10.4
- Tutorial20% · score 11.4
- Case Study18% · score 9.87
- List18% · score 3.21
Consensus and debate
Where creators agree, and where they do not
Shared view
Manual, unscalable work wins the first customers
Several posts describe hand-built early traction. Finn Mallery lists YC-style tricks such as Collison-style on-the-spot installs and being the product manually. Omar Ghandour DMs 10–20 ICP matches with no templates. Germán Merlo does five 'embarrassingly hands-on' onboarding calls. Harshil Tomar relays a Reddit founder who called almost every trial user.
Shared view
Clone proven formats instead of inventing them
Launch and short-form playbooks converge on copying formats that already perform. Finn Mallery searches viral X launches from the last 60 days to replicate opening lines and formats. Alex Nguyen advises cloning viral formats with a strong 3-second hook and doubling down on one format until it dies.
Shared view
Retention fixes can outperform more acquisition
Ecom Mike tells two stories in which cohort data showed flat repeat purchase rates. In a friend's store, rebuilt post-purchase flows lifted repeat rate from 13% to 29% with no ad-spend increase. In his own store, the rate went from 15% to 31% and CAC dropped. Mehul Fanawala frames churn as the real growth engine. Sarah Carusona says post-purchase experience moves LTV.
Shared view
Track sources down to paying users
AdrienBrb added UTMs to every link via PostHog to learn which platform brings paying signups. Alex Nguyen tracks UTMs through views, clicks and installs. Frederick James uses RevenueCat or Superwall for attribution and gives ad spend and transaction data to Claude to find winners.
Open debate
Is growth skill or a byproduct of PMF?
Clara Gold says heading growth at Rappi with PMF made everything work, and calls building a wanted product the only hard growth problem. By contrast, Finn Mallery argues that with 100+ competitors, getting off the ground takes every trick in the book. Gagan Biyani predicts a growth hacking comeback enabled by AI tools.
Open debate
Paid ads versus organic-only distribution
Harry Stebbings relays Matt Swulinski's view that paid acquisition is the fastest way to validate PLG. Viktor Seraleev calls paid a reliable, controllable channel. On the other side, Harshil Tomar credits his agency's growth to organic content and referrals with no ads. Fraser relays a founder's niche design tool reaching $23.4k/mo on organic X and Reddit with no ads.
Open debate
Post volume versus posting only when real
Leon Abboud says doubling his output doubled reach and follower growth. Louis Gleeson argues daily Instagram posters outgrow weekly ones. Ricky advises posting only when you have something real to say. Jonah Lau warns that content without a funnel generates noise that looks like traction.
Open debate
Free trials or hard paywalls
AdrienBrb credits a hard paywall from day one, noting a free tier meant $0 revenue for weeks. Viktor Seraleev says you can grow without hard paywalls and that letting customers try the product works surprisingly well.
What performs
Patterns behind standout posts
A launch-video playbook is the top outlier
Finn Mallery's step-by-step launch video guide scored 800.02, 80x the 10 median. His YC first-100-customers list scored 486.91 (48.69x). His 643.46 median is far above every other top voice.
Viral and video themes score highest
The viral launches and short-form video theme has a median score of 21.28. Retention scores 3.72 and founder-led content 4.692, even though retention posts include some of the most concrete before/after numbers.
Tutorials beat lists on median; one prediction stands out
Tutorials post a median of 11.37 against 3.205 for lists, though a list (Finn Mallery's YC tricks) is still the second-highest outlier. The single prediction post, Gagan Biyani on a growth hacking comeback, scored 35.525.
Media gives a modest edge
Posts with media (40% of the set) have a median score of 10.26, versus 8.58 for text-only posts.
Paid-ads tutorials rank among top outliers
Frederick James's mobile ads breakdown, framed around hitting $7.8k/m and including explicit budget and scaling rules, scored 240.96 (24.1x median). Alex Nguyen's TikTok playbook scored 139.16 (13.92x).
Statistical standouts
- View standout post 1Score 800.0 · 80× median
- View standout post 2Score 486.9 · 48.69× median
- View standout post 3Score 241.0 · 24.1× median
- View standout post 4Score 201.1 · 20.11× median
- View standout post 5Score 139.2 · 13.92× median
Creator landscape
Who shapes this conversation
The five most represented creators account for 20% of the selected posts.
1. AdrienBrb
@adrien_brbr
2 posts
2. Germán Merlo 💻 🇦🇷
@elgermerlo
2 posts
3. Finn Mallery
@fin465
2 posts
4. Harshil Tomar
@Hartdrawss
2 posts
5. Sasha Sage
@SSage38676
2 posts
6. Ecom Mike
@TheecomMike
2 posts
Fragmented field with one dominant voice
The 50 posts come from 44 creators, and the top five hold 20% of placements. No one posts more than twice. Finn Mallery is the clear engagement leader by median score.
Operators cite results from roles they held
Clara Gold draws on her time heading growth at Rappi. Carles Reina self-reports ElevenLabs at +$500m ARR with 50% of revenue from outside the US. Ayman Al-Abdullah says a switch to cash referrals at AppSumo became an 8-figure channel.
Measurement specialists push incrementality
Ad and measurement practitioners stress holdouts and geo tests. Collin Schmelebeck describes Google intercepting Meta-created demand. Nate.Google describes matched-DMA holdouts. MarketingOperators outlines HexClad's testing process. Olivia Kory reports that in a Haus simulation, acting on noisy results left businesses worse off than doing nothing 38% of the time.
Since the previous snapshot
What changed since Aug 24, 2026
- 72% of the selected posts remained.
- The creator count changed by +3.
- The leading sentiment remained stable.
How this analysis was made
Themes, sentiment, stance, and post format are classified per tweet. All counts, shares, medians, creator concentration, freshness, and performance comparisons are then calculated directly from the published snapshot.
Xholic's all-time score compares engagement while accounting for reach, post age, and creator consistency. It is used for relative comparisons within this collection.
This report analyzes the exact 50-post snapshot shown below. AI identifies editorial categories and drafts explanations; all statistics are calculated from the snapshot, and every narrative claim is checked against cited posts before publication.
Best Growth Hacking tweets
Top Growth Hacking tweets from 44 creators
Ranked 01–50
- 01
@fin465 ·
I might regret posting this cuz it's one of our best growth hacks and anyone can do it, BUT here's how to get 250k-5m+ views on your launch video its OP cuz if you crack the formula, you can ship a new vid each month and drive insane inbound. We make 1/month and clear 200k+ views every time 1. make a launch video. either record it yourself with a screen-capture tool like Borumi or find good editor to put it together for you (i use @flowjamhq ) 2. open your tweet with a hook that kills the scroll. think "the first ever ___" or "today we're replacing ___." 3. personally, I do a search for viral X launches in the last 60 days on @origamichat and try to use the same formats (bc these formats are already proven by the algo, so you’re not guessing) 4. After finding these super viral launches (10m+ views) try to replicate the X post opening line, video format, quote tweets that worked best, etc. when you launch 5. ping your network (investors, friends, people you used to work with). give them the exact date and time you're going live. 6. once you're live, blast an email to everyone who agreed to help. drop in your launch tweet plus clear directions on what you want from them. 7. in those directions, spell out your core message and show sample quote-tweets you'd love them to mirror. (follow X's rules on disclosed posts) 8. push everyone to interact with the post inside the first hour if they can. 9. You can also run paid ads on the video after the first day or so to boost engagement 10. launch every time you make a big new feature that could be framed as a standalone product ------ the best part is that if you flop, it means no one saw it anyway. So swap the hook and relaunch the next week. ppl will literally ‘launch’ 3-5x/month and it works Hoping to see more great launch vids on X Will be posting more playbooks to go viral every week on here
- 36Replies
- 23Reposts
- 712Likes
- 56.5KViews
Rewrite this post in your own voice and angle.See the hook, structure, and reusable template behind this post. - 02
@fin465 ·
The “unfair tricks” YC tells every founder on day 1 to get their first 100 customers ASAP: 1/ When someone says "sure, I'll try it," average founders say "great, I'll send you a link." Stripe's founders said "give me your laptop" and set it up on the spot (the infamous Collison installation) 2/ If someone won’t adopt your tool, be the product manually (even fake it). When merchants wouldn't build their own stores, @paulg (Viaweb) built them by hand using their own software. 3/ Charging less will often lose you the deal. Early adopters aren't price sensitive - they care more about beating competitors. Price too low and they assume something's wrong with you 4/ Price off value, not cost. The gap between your price and the value delivered is literally the customer's incentive to buy. Widen it on purpose 5/ Every discount you give trains the customer to devalue you. One-off "just this once" pricing becomes the permanent expectation 6/ A fast "no" is almost as valuable as a "yes." Early on, optimize for speed of decision, not size of logo. The prospect dragging you through 4 calls costs you the bandwidth to find 4 real buyers 7/ You're not targeting your entire market. You're hunting the top ~1% of companies who are "innovators." Your job is to sift fast enough to find them. You can use tools like Origami or Clay to build hyper targeted lists of these 1% adopters 8/ Your only 2 unfair advantages as a founder-seller are passion and domain expertise, not technique. You will never out-technique a real salesperson, so lean entirely on the two things they can't fake People on X love to dunk on these "hacks" But when anyone can build anything and you've got 100+ competitors, getting off the ground takes every trick in the book
- 23Replies
- 28Reposts
- 725Likes
- 60.2KViews
Rewrite this post in your own voice and angle.See the hook, structure, and reusable template behind this post. - 03
@frederickjames ·
My app just hit $7.8k/m in revenue. This is how I'm running ads for mobile apps. To hit 10k/m before I quit my job & fly to Vietnam 🇻🇳 Part One: Apple Ads (First $1k/m). • Repeated this a lot so to summarise: 1. $100 free ad credits, ez mode. 2. Run strict keywords on competitor names. 3. Split into tiers for countries & scale the max bid. 4. Use @RevenueCat or @Superwall for attribution. 5. Give ad spend & transactions to claude: find winners. 6. Measure the onboarding: tighten funnel. 7. Daily budget can be low at first, like $20. 8. The max bid is the important variable here. 9. This will get you to $1k/m. Part Two: TikSl0p Ads ($1k to $10k) • This is much harder to make profit. • But when you do, it's exponential. • Read @carlmonkft's guide on this first. 1. Make ~6 formats, ~12 creatives. 2. Leave campaign targeting super broad. 3. I do $70/day of campaign budget spend. 4. No demographic or interest settings. 5. Let the algorithm find your perfect user. 6. Give each creative $50 of ad spend. 7. After $50, if (close to) profitable then scale. 8. If no profit, then stop the posts. 9. Use realised LTV to begin with. 10. Simple: revenue / paid customers. 11. 400 IQ chad: aim for profit on initial transaction. 12. Ask Rico for unrealised LTV. Can be hard to calculate. 13. Expect to burn a few hundred $$ to find profit. Notes: If you none of your creatives are profitable, then go back to the drawing board and try again. You're taking $50 gambles each time. When you find a winner, it'll repay the initial investments 100x! This is a game of pain tolerance. You need to be able to stomach losing hundreds of $$$ without seeing any returns. Part Three: Scaling. 1. If you're consistently getting > 2x ROAS. 2. Up your campaign budget by 15%. 3. Do NOT increase more than 30%. 4. Otherwise I will be very very cross with you. 5. You'll kill performance. 6. Performance can be volatile. • Measure ROAS over weeks, not days Notes: When you've found a winning creative, create multiple variations of it. We're talking 100 different kinds. I'm being lazy and need to do this more!! Part Four: Experimental Ad Spend ($10k +). • This is the next level: I've gone 0-1. • I've not seen much sauce on X about scaling past this. • So, this is where I'm at now. I'll share it with all of you. My current position is: 1. Trying out other platforms: Meta, IG, etc 2. Continue reinvesting the profits from previous ads. 3. I'm trying multiple new avenues right now: • Paid influencers, UGC, slideshowmaxxing, etc. Keep pushing, we're all gonna win.
Watch video- 37Replies
- 10Reposts
- 237Likes
- 14.7KViews
Rewrite this post in your own voice and angle.See the hook, structure, and reusable template behind this post. - 04
@Clara_Gold ·
The easiest job in tech is Head of Growth at a consumer company with PMF. I did it at Rappi and thought I was a genius. Everything you try works. Tweak onboarding → conversion jumps. Unlock referrals → growth explodes. Turn on paid → infinite scale. And if something fails… it was an “experiment.” But that’s a fallacy. It’s like losing weight on GLP-1 and thinking you mastered discipline. Because when you become a founder, you realize the only hard growth problem is building a product people actually want. I’m a growth person, but I have infinitely more admiration for 0→1 product people than 1→100 growth people.
- 69Replies
- 43Reposts
- 1.1KLikes
- 89.7KViews
Rewrite this post in your own voice and angle.See the hook, structure, and reusable template behind this post. - 05
@alexcooldev ·
This is my TikTok growth playbook every B2C founder should know 👇 What actually works (with me) in 2025-2026: > TikTok first. The algo is totally different from IG or YT Shorts. Small accounts can still go viral → distribution is real. > Quantity > perfection. Work with 25–50 micro creators (<10k subs). Post 1–2 videos daily. Test fast. > Cross-post everything. TikTok → IG Reels → FB → YT Shorts. Same content, more surface area. > Don’t reinvent formats. Clone what already goes viral. Strong 3-second hook or you’re dead. > Find 1 viral format → double down. Post it repeatedly until it dies, then move on. > Hook + CTA must align. Otherwise you’ll get millions of views and 0 downloads. > Pay for views, not upfront. Align incentives. Keep only creators that convert. > Track everything. UTMs → views → clicks → installs. Cut fast. Scale faster. > Warm new accounts. Seed them with non-marketing content first before pushing ads or product videos. > Reality check: Not every product works on TikTok. Best way to find ideas? Search viral pain points on TikTok / IG / YT → then build an app that solves that exact pain. Marketing > coding. Test fast. Learn faster. Ship what converts. 🚀
- 25Replies
- 17Reposts
- 248Likes
- 22KViews
Rewrite this post in your own voice and angle.See the hook, structure, and reusable template behind this post. - 06
@HarryStebbings ·
I have interviewed 100 of the best growth leaders in the world. @MattSwulinski is easily top 3. (alongside @alexschultz and Brian Hale) He scaled Wispr Flow to over $100M in ARR and built a UGC machine. He scaled Superhuman from founder personally onboarding every customer to a growth machine with $50M ARR. If you are an early stage founder or growth leader, this will be the best episode you will listen to this year! I condensed my biggest lessons from the discussion below: 1. The E-Commerce Playbook Is the Right Playbook for SaaS The e-commerce playbook, where every dollar spent ties directly to a purchase or conversion, is the right model for modern SaaS. With distribution becoming a critical moat in a crowded AI market, SaaS companies should deploy UGC creators, constantly test new creative, and diversify channels to build their brand. 2. Paid Acquisition Is the Fastest Way to Validate PLG Relying solely on organic content and word-of-mouth takes too long to validate product-market fit. Paid acquisition creates the fastest feedback loop for proving a PLG funnel works, allowing teams to test positioning, refine messaging, and optimize conversion within a single week. 3. You Only Need Three Core Channels to Scale to $10M ARR Startups often ruin their acquisition engines by trying to run ten channels poorly at once. Reaching the first $10M in ARR only requires mastering three core channels: video intent on Meta, search intent on Google, and lifecycle retention through email and SMS. 4. Scaling Paid Ads Requires 500 New Creatives Every Single Month On platforms like Meta, creative increasingly acts as the targeting algorithm. Scaling spend without hitting audience fatigue requires 400 to 500 new creative assets every month, produced through UGC revenue-share programs, specialized agencies, and internal teams. 5. How the Best Growth Leaders Test for True Spend Incrementally Blindly increasing ad spend wastes money on conversions that may have happened organically. The best growth leaders measure spend elasticity against ARR growth and run strict holdout tests to determine whether each additional dollar generates genuinely incremental revenue. 6. In Three Years, Companies Will Operate Like a Board of Directors Tech organizations are shifting away from manual execution. Within three years, lean human teams could operate more like boards of directors, spending 20% of their time on strategy while autonomous AI agents handle 80% of operational execution. 7. Fire Your Marketing Team if They Aren’t Systems Thinkers Marketers focused on repetitive manual tasks are becoming increasingly replaceable. High-performing teams need systems thinkers who can break their work into inputs and outputs, then build self-improving AI workflows that multiply their personal leverage by 10x. (links in comments)
- 49Replies
- 27Reposts
- 463Likes
- 325.3KViews
Rewrite this post in your own voice and angle.See the hook, structure, and reusable template behind this post. - 07
@Carles_Reina ·
Over the past 3.5 years at @ElevenLabs, I've done unconventional things in GTM. Let me tell you why: - I hate hiring people that come with playbooks. In interviews, when someone tells me about their "playbook", I reject them immediately - Each company is different. Entering a market selling support agents is different from selling legal tech or ERP replacers. - Each market & product requires a unique thesis and approach. If you don't understand the market, you can't craft a narrative that will be sticky - AI has changed all dynamics. Experimenting is the only path forward - Thinking big and placing bets yearly delivers outsized returns. I only need 1 bet to work to smash the target for the year - Aligning the team in a Vision is the glue. Not many companies have a crazy Revenue Vision each year; mostly because leaders fear getting fired if something doesn't pan out. I can't be bothered - You build a startup to do impossible things. Unconventional leads to making possible the impossible Doing things unconventionally isn't easy - you face rejection internally & externally. But, hey, "this is the way". An example: I came up with the "Global hyper-local" concept in 2024. Let me tell you that most people didn't want to open markets, have teams on the ground, adapt product (incl translations) or stop being US-first, amongst many things. Today, we are global, +$500m in ARR, 50% of revenues come from outside the US, Enterprise is larger than Self-service, I have teams in +25 countries and have cracked the most difficult markets. Being unconventional works. Just be creative, driven, hands-on, pushy and jump through obstacles. But don't be silly; if a company doesn't value it, find a new challenge. We are lucky to live the best period in history to build companies.
- 34Replies
- 18Reposts
- 387Likes
- 63.4KViews
Rewrite this post in your own voice and angle.See the hook, structure, and reusable template behind this post. - 08
@seraleev ·
I’m taking a break from X. I don’t know how long it will last. I’m a bit tired of the constant focus on reach, monetization and being public all the time. I want to spend some time in silence, focusing on my business. Over the last 2.5 years of my build-in-public journey, I grew from $0 to $100K/month. Here are 10 short lessons I’ve learned: 1. If you want to build a personal brand, X is the perfect place to start. Some of the most well-known people in tech might end up reading your posts. I was shocked that people I looked up to not only read my posts, but also replied and supported me. 2. X is the perfect place to bring attention to a problem. Things can go viral and even large corporations may start responding. I’ve experienced this firsthand. 3. If you’re building products for developers, X is an amazing launch platform. Your audience can help you with Product Hunt launches and be your first supporters on Reddit. 4. If you’re a mobile developer and become popular on X, be prepared for a lot of copies. And I mean a lot. Names, icons, screenshots, internal models, UX, paywalls. Accept it early and understand that it’s simply part of the journey. 5. You can grow without hard paywalls. You can let customers actually try your product. This approach works surprisingly well. 6. Filter all advice. Seriously, filter everything. Some of the advice you read on X can get your developer account terminated. I’ve helped many developers who shared harmful advice on X, gained huge reach, and later ran into serious issues with Apple themselves. 7. Design matters. People have learned to distinguish AI slop from products built with care. Don’t be afraid to put a piece of yourself into every app you create. 8. Learn paid acquisition. It’s a reliable and controllable growth channel. I’ve been growing this way consistently for the last 2.5 years. 9. If you don’t have a budget, learn ASO, localize your app and pricing, create videos about your products, and publish them on Reels, TikTok, and Shorts. You can grow without money too. 10. Stay true to your principles. That’s something I’ve carried throughout this entire journey. Sometimes people will hate you for it (and that’s okay). It’s still better than changing your beliefs every single day. Thank you to everyone who followed my journey. See you soon ❤️
- 31Replies
- 7Reposts
- 259Likes
- 10.8KViews
Rewrite this post in your own voice and angle.See the hook, structure, and reusable template behind this post. - 09
@SinaSinry ·
Finally I built the best CMO dashboard for my app growth. App Store Connect + RevenueCat + Superwall + AppsFlyer + Amplitude + TikTok Ads Manager I was looking to hire an app data analyst to help me analyze my app data, which would have cost me at least $2k a month. But with Claude, after 8 hours of co-working and explaining exactly what I need as an app founder, it built something I had always wished for. One dashboard for all my data. And most importantly, its someone that can analyze this data and help plan the app growth and user acquisition journey. I don’t have much experience in user acquisition or app growth, and I’m not a developer either. So I’m not sure if this is exciting for others, but for people in my position, I think it could be really helpful. Let me know if it is, and I’ll share fully how I built it with Claude co-work so you can do it too.
- 18Replies
- 2Reposts
- 92Likes
- 9KViews
Rewrite this post in your own voice and angle.See the hook, structure, and reusable template behind this post. - 10
@gaganbiyani ·
Growth marketing was perhaps the most important trend in tech in 2010. Chamath literally got 1% of Facebook and became a billionaire for starting the first ever growth team at Facebook. I ran a conference called “Growth Hackers Conference” and it was sold out multiple years in a row. By 2020, growth marketing was practically dead. Nobody was talking about it and most growth teams folded fully into product orgs. In 2026, I believe growth hacking will make a strong comeback (likely without the cringey name). Growth used to be a cool art where super high IQ and high EQ practitioners leveraged consumer insight, data and product to create unique ways to grow their products. They built crazy referral loops using Facebook or LinkedIn connect, created SEO-friendly pages en masse for marketplaces, and built spammy viral apps as customer acquisition tools. Eventually, most of those acquisition channels closed up - and so most growth marketers became "user acquisition" or product managers. With a new disruptive force like AI, growth opportunities have opened up again. We have at our fingertips an extremely broad set of new tools that are still developing: - Vibe coding allows you to build micro-products and micro-workflows from scratch, without having to suck up engineering resources. Experimentation can explode, if you figure out how to pull it off. - AI can ingest massive amounts of data and therefore help create new insights. - AEO will become a massive growth opportunity that will require inventive solutions to trick LLMs into recommending your product. And I’m fairly confident OpenAI/Anthropic will offer an “App Store” for ChatGPT and Claude. (The current version OpenAI released is just the beginning). - Content marketing will look totally different in the age of unlimited creativity (and productivity) from AI-generated content. There are tons of fresh opportunities for growth marketers to play with and innovate on. The intersection of data, product, and marketing is going to have a rebirth. Game on.
- 20Replies
- 18Reposts
- 170Likes
- 20.3KViews
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- 11
@JosephKChoi ·
peptides is probably the fastest growing category in consumer apps rn this one just made $100,000 in its first 70 days, then $200,000 in the next 30 days. and still growing got @Cedric_Roberge to share the entire marketing strategy on the pod. full video 👇 0:00 - The $100K Strategy: Achieving Six-Figure App Revenue in 70 Days 1:12 - Growth Engine Alpha: Inside the Consumer Club and Developer Tech Stack 2:25 - Market Positioning: Solving the Tracking Gap in the Exploding Peptide Space 3:57 - Pioneering a Trend: Navigating Early Concept Phase to Product Launch 5:30 - Organic Amplification: Building a High-Engagement Influencer Retainer System 6:35 - Performance Optimization: Transitioning Organic TikTok Winners into Paid Meta Ads 7:55 - Tracking Metrics: Acquisition Costs and Analyzing Dashboard Conversion Rates 9:33 - High-Converting Formats: Analyzing Organic Slideshows vs. Traditional Talking Head UGC 11:31 - User Journey Architecture: Mapping the Flow from For You Page to App Store Downloads 13:38 - Residual Traffic Networks: Monetizing Link-in-Bio Real Estate via Private Creator Communities 15:08 - Influencer Deal Frameworks: Retainers, Contract Logistics, and Milestone Bonuses 18:11 - Low-Risk Testing: Getting 20,000 Total Views for $200 Monthly Retainers 18:36 - Creative Freedom Guide: Structuring Asset Briefs Without Restricting Creators 20:04 - Operations Architecture: Standardizing Outreach Playbooks for Rapid Team Delegation 21:31 - Affiliate Incentive Systems: Boosting Content Output with Strategic Revenue Splits 22:58 - Interface UX Audit: High-Converting Paywalls, AI Insights, and Onboarding Flows 26:33 - Finding the Pain Point: Understanding Why Users Will Pay for Convenience and Safety 28:36 - Age-Gated Conversion: Customizing User Journeys for Gen Z vs. Mature Audiences 31:16 - Listening to the Market: Rapid Iteration of Syringe Calculators and Core Tracker Features 32:22 - Product Pruning: Knowing Which Underutilized Features to Remove 33:48 - Automated Feedback Loops: Collecting Multi-Channel User Insights Weekly 34:59 - Structuring the Company: Scaling Outreach Hires and Marketing Manager Positions 36:29 - Quality Control Framework: Vetting Creator Content Before It Goes Live 36:50 - Founder's Background: Translating High School Esports Management into App Growth 38:42 - Bootstrapping & Equity: Securing Angel Investment and Insane Tech Talent 41:17 - Scaling Up Spend: Static Creative Strategies, Meta Compliance, and Breaking Top 100 Rankings 44:33 - Fraud & View Bot Auditing: Vetting Real Engagement Against Fake Metrics 46:50 - Paid Ad Deep Dive: Why a Cluttered Static Graphic is Beating Clean Video Ads 50:06 - Platform Constraints: Why TikTok Rejects Peptide Ads While Meta Succeeds 51:29 - Outro: Post-Launch Plans, Future Hiring, and Final Growth Alpha Breakdown
Watch video- 13Replies
- 2Reposts
- 57Likes
- 5.7KViews
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@omarships ·
Distribution is where most startups quietly die. Everyone talks about it like it’s some growth hack. Almost nobody does it right. People ask me: “How did you distribute Agently?” It's Simple. Unsexy. Boring. No playbook. No magic channel. Here’s what actually works: 1) Before you even think about picking a channel → Draft who your ideal customer might be (don’t overthink it speed > perfection) → Make sure your landing page speaks directly to their pain and outcome (nothing else matters) → Find 10–20 real people that match this profile (LinkedIn is easiest) → DM them manually: no templates, no automation, just real conversations → Pay attention to which conversations actually convert and why Now you have your first real ICP signal. 2) From there: → Figure out where these people actually spend time (Discord, Reddit, X, Hacker News, etc.) → Double down on the one place that shows the most engagement → Keep it manual: you’re still learning, not scaling → Once you start seeing consistent conversions, you’ve validated a channel 3) Now it gets interesting: → Test 3–4 different approaches within that channel → Let them run long enough to matter → Kill what doesn’t work, double down on what does At this point, you have: → A real ICP → A proven channel → A strategy that converts Now you can scale. Content, automation, growth loops: all of it works after this. Most people try to skip this and distribute to 10 channels at the same time and wonder why it isn't working. That’s why most people never crack distribution. No playbooks. No gated threads. No “10 hacks”. Just what actually works.
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@brodieseo ·
AEO Tip: I've been increasingly experimenting with trying to influence ChatGPT output for my eCommerce clients. Particularly for queries where I'm comparing my client against competitors for basic 'buy' and 'sell' queries for them as a business. The balance that we're trying to strike within this experimentation is ensuring that we're staying within the confines of their branding and not outright mentioning competitors – something that is far more common within the SaaS space. For this client, a lot of their competitors are considered to be "marketplaces", whereas my client holds all stock on-site (a major point of difference) and does the buying and selling of the stock itself. The major benefit to this approach is that they can maintain the quality of the product through their own authentication processes, being a clear advantage over the classic marketplace model. Within this experiment, we published a comparison page that compared them against "marketplaces" across various metrics in order to influence the output, and our new page was used as a core source in ChatGPT within a day. And we're already starting to gain more control over how they're being represented, making a clear argument for why both buyers and sellers should choose them over key competitors, without mentioning them directly. In my opinion, this type of approach is the way forward when doing these types of experiments, rather than creating content that goes outside of company guidelines for the sake of AEO. It is a fine line for this type of work, but clear benefit when it is executed correctly.
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@Hartdrawss ·
Dreamlaunch recently hit $100k milestone A few months ago, DreamLaunch didn't exist. In this time, a lot has changes Today we've crossed $100K revenue, 50+ MVPs shipped, clients across India, US, Dubai, Saudi Arabia. Here's exactly how we did it, so you can do it too. The core principle that changed everything : We made the work good enough that clients became our distribution. No ads. No cold outreach. No marketplace. Just work that was worth talking about. Here's the breakdown : 1. Pricing (the ladder) Simple rule : after 3 clients said yes without flinching, raise the price. - $500 x 3 clients - $1,000 x 3 clients - $2,000 x 3 clients - $3,500 x 3 clients - $5,000 x 3 clients Every time 3 people said yes, we knew we were still underpriced. Not 10x overnight. One step at a time. 2. Acquisition (what worked) Organic content. Always. Only. - No paid ads - No cold email sequences - No growth hacks Our first $5K client came from a referral. Saudi-based founder. We built their MVP. They were happy. They sent us the next one. That single referral paid more than 6 months of trying every freelancing platform combined. 3. The work itself One client wanted to automate their entire RFP document filing process. 10-15 hours of manual work every month. We built the pipeline. Eliminated the hours. They used that time to close a $40K contract in month one. That was the shift : You don't get paid for the work. You get paid for the value the work creates. Not your hours. Not your effort. The outcome. 4. What didn't work Freelancing platforms. Every single one. - Fiverr : couldn't figure it out - Upwork : same - Contra : closest, but payment friction with Indian clients broke it every time We wasted months trying to force these to work. In hindsight, high trust + high ticket work doesn't come from a listing. It comes from someone seeing your work and deciding they want exactly that. What actually worked : → Delivering so well that referrals came without asking → Raising price after every 3 yes's — not before, not after → Building in public so inbound replaced outbound → Saying no to scope creep early — protected quality, protected reputation → Organic content as the only acquisition channel we actually doubled down on What's not working yet : Outbound is still unstructured. Every client still comes from referral or inbound content. That's great until you have a slow month. Building a proper outbound system now. The path from $500 to $5,000 isn't glamorous. It's lowball clients you deliver for anyway. Watching them win with what you built. And knowing exactly what to charge the next one. Do the right things consistently : Good work. Real referrals. Honest pricing. It compounds. One day you're not the cheapest option in the room anymore. Goal now : $500K revenue by end of 2026. LFG. PS : What's the price you're charging right now that you already know is too low?
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@emilylai ·
Thinking about how crypto incentives on retail apps skew user behavior. This makes traditional metrics like LTV more difficult to measure and affects user acquisition marketing downstream When targeting new users on CT, there’s two distinct user types: 1. Those who actively use your product for its main use-case (e.g. want to trade gold and think you’re the best venue to do it, so continually trade on your platform) 2. Those who only use your product to farm it for a potential airdrop (may drive revenue but out of speculation) LTV and payback period are common metrics used in traditional marketing. If you know the average revenue a user drives, you have a cost you’re willing to pay to get a new one - this helps give you a benchmark for CPA targets To get “real” LTV in crypto retail products when incentives are involved though, you have to cohort “top” users based on retention and revenue, and measure it there Even that doesn’t feel fully accurate though; I find LTV in crypto a lot more elastic as the audience size is small whilst new competitors pop up and vampire attack each other through incentives - it makes metrics like LTV less durable Downstream from all this as well, LTV from a high-revenue-over-time type quality user captured from CT also may not be comparable to non-crypto native users you capture on other channels, so you a margin is needed to have a target CPA when running growth experiments What does this mean for crypto apps? For one, I particularly would want to build or work somewhere with a mission bigger than CT. To get there most quickly means: 1. Focus on retention and lifecycle, crypto-native TAM is small, maintain easiest targetable revenue 2. Product teams should focus on new features and baseline being competitive to crypto apps (helps with retention and UA) 3. Onboarding and onramp flows optimizing for conversion rate for non CT users, can even segment these based on different channels 4. Measurable experiments that growth teams can quickly scale, cut, and optimize
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@leonabboud ·
X growth hack: Double how much content your publish. Last year, I ran an experiment. "What would happen if I doubled my content output?" I tried it. The results? My account doubled in reach and follower growth. Do it, the algo does not nerf you for volume.
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@danmartell ·
growth hacking isn't a tactic. it's one question: who already has my customers? here's how it plays out: wealth manager friend: "my best clients have jets." ok.. who sells the list of every private plane at an airport? turns out, someone does. that was his whole channel. payroll software client burning cash on cold dials. i asked what was true about his 100 customers. "they all use google apps for domains." that meant early adopters. so instead of dialing 300k businesses, he filtered to the 20k that matched. done. find the unique angle nobody else sees. that's the moat. if everyone knew it, it'd stop working.
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@HappyfulofWeb3 ·
Was talking to a founder of a Web3 product with 220M users. I shared a bunch of growth ideas. He replied with one line: “Cool. How to monetize?” That question hit harder than anything else. Because it exposes a truth most people in crypto avoid: If your growth strategy doesn’t drive revenue, it’s just noise. We’ve normalized: > Vanity metrics > “Community building” with no value capture > Campaigns that look good but don’t pay But real operators think differently. They’re not asking: → “Will this go viral?” They’re asking: → “Does this increase revenue per user?” Every growth idea should map to: Acquisition → Activation → Retention → Monetization If you can’t clearly answer: > What user action increases? > How that action makes money? > How often it repeats? Then it’s not a strategy, It’s fluff. If you’re a founder or operator, change how you think about growth; > From: “Let’s get more users” > To: “Let’s get more valuable users doing profitable actions” Different game entirely.
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@mynameisyahia ·
The talk that completely changed the way I think about growth was @nathanbarry at the OOO conference in NYC a year ago He talked about flywheels The premise is: You do something really hard that makes the next time you do it a tiny bit easier You repeat this over and over until it becomes super easy to keep the flywheel going I have a super simple flywheel that changed my business > I ask customer for case study > I use case study to get new customer > repeat At first, it was VERY hard since no one trusts you to become a customer, and you have no customers to land other customers with But i managed to get a case study after a few months of asking, and then used that to get another, and now my entire outbound is basically just this message "Hey, these 250+ companies trust us, here's proof, do you wanna give us a shot?"
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@ToriiRowe ·
Meta is combining awareness and sales into a single campaign type in Q2, and I think it’s the most significant structural change to paid social prospecting in the last few years. This is different from Customer Lifecycle Strategy! Here’s what’s actually happening. The new campaign runs sales optimization as the primary objective while simultaneously pulling in reach optimization to expand into new audiences at lower CPMs. You’re not running two campaigns anymore. You’re running one that does both, and Meta is handling the allocation. The reason this matters for brands spending $100K or more per month isn’t the CPM drop. It’s what this signals about where Meta’s entire ad system is heading in 2026. Every tool they’re building right now points in the same direction: new customer acquisition percentage is becoming the primary metric the platform is optimizing toward at the infrastructure level. Not ROAS. Net new buyers as a percentage of total purchases. Most brands in the $5M to $50M range are running prospecting and retargeting in silos and measuring everything through a blended ROAS number that makes the account look healthier than it is. What that blended number is hiding is how much of your “acquisition” spend is actually just recycling warm audiences you already paid to build. Meta is building a system that makes that problem visible whether you want to see it or not. We’re in beta on this at DREAMLABS. What I’m watching isn’t ROAS. It’s the new customer rate inside the purchase mix. If that number isn’t climbing, the campaign isn’t working, full stop, regardless of what the dashboard shows. The brands that come out ahead in this environment will be the ones with the margins and the CLTV to absorb a higher CAC on new customers and let those customers compound. The ones that don’t will be the ones who realize too late that they’ve been running retention campaigns with acquisition budgets. Q2 is going to make that distinction very clear
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@SchmelebeckPPC ·
If you're spending $200K/month on Meta and $30K on Google, you're not diversified You're exposed Here's the test that proves it: Go to GA4 → Acquisition → User Type (New vs Returning) (or Triple Whale, Northbeam, Wicked Reports, etc) Filter by Google Ads traffic What percentage is NEW traffic? If it's under 75%, your "second channel" is a lie You're running two channels but getting new customers from ONE Here's what's actually happening: Meta drives awareness → Person doesn't buy → Googles your brand 3 days later → Clicks your Google ad → Converts Google credits itself with the sale Your dashboard shows: Meta: 250% ROAS Google: 700% ROAS Total: "We're killing it on both channels!" But the reality: 95% of NEW customers came from Meta Google intercepted the conversion Meta created You have ZERO acquisition independence THE REAL TEST: Turn off Meta for 7 days (I know, terrifying) if you cant stomach that, just watch next time you pullback on Meta then watch what happens to Google revenue In accounts I audit before we setup true TOF prospecting campaigns, it's not far fetched to see Google revenue drops 40-60% when Meta gets pulled back Why? Because Google was just catching what Meta threw When Meta stops creating awareness, Google has nothing to harvest That's not diversification...it's just dependency with extra steps. THE FIX: Separate your Google campaigns into three buckets: BUCKET 1: DEFENSE (Branded Search) Keywords: [Your brand], [brand] reviews, [brand] discount Purpose: Protect your house (cheap CPCs, block competitors) Budget: 5-10% of total Google spend Expectation: 10x+ ROAS BUCKET 2: SUPPORT (Retargeting) Audiences: Website visitors, cart abandoners, subscribers Purpose: Close people Meta warmed up Budget: 10-20% of total Google spend Expectation: 200-400% ROAS (still mostly Meta's work) BUCKET 3: OFFENSE (Cold Acquisition) Keywords: Category terms, competitor alternatives, problem searches Audiences: Lookalikes, In-Market, ZERO overlap with existing customers Purpose: Find people who've never heard of you Budget: 70-80% of total Google spend THIS is diversification. THIS is what protects you when Meta has a bad week or if your creatives start dying off but here's what I see in 90% of accounts I audit: Bucket 1: 60% of spend (massive brand tax) Bucket 2: 30% of spend (retargeting Meta's work) Bucket 3: 10% of spend (barely testing cold) Then brand owners who i talk to wonder why turning off Meta kills the business You should only care about ONE question when diversifying: What happens to overall revenue when Channel A goes to zero? If the answer is "Revenue drops 90%," you don't have two channels. Check your New visitor % If you don't like the number, DM me. I'll show you the exact account structure that fixes it
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@LoganTGott ·
Saw this post as I was scrolling the other day So I went and broke down their LinkedIn strategy for driving over 6 figures in pipeline from LinkedIn last month. Here's what's actually driving it: 1. He's got a head start. Around 30k followers. A decent following isn't the whole game, but it definitely doesn't hurt. 2. His profile is barely optimized. No link to the company in his featured section, nothing to book a call, nothing like that. His posts are carrying almost all the weight, which means pipeline is leaking everywhere. 3. The content is obviously human. Behind the scenes of building the company, live videos, podcasts, actual photos of the team. You can tell a person is writing it, and that's a big reason it converts. 4. His hooks make you stop. One of the best is about giving every new hire a $5,000 company card on day one, with one rule: spend it like it's your own. You read that and go "wait, what?" and then he explains why. That's how he pulls attention to the product and holds it. 5. He stacks proof. Featured on Business Insider, stuff like that. That kind of authority does a ton of the selling for him before he ever asks for anything. 6. Distribution is where the leverage is. Every post clears 100+ likes, and his team is posting and commenting to drive early engagement. Combined, that's a machine probably pulling a few million views a month across all their accounts. 7. It all rides on a good product. Bad product and none of this works, nobody cares. An interesting product plus an interesting founder makes it easy to go behind the scenes and talk about it every day. The part most people miss is that he's winning on content and distribution alone, with basically no funnel behind it. Build the funnel on top of what he's already doing and it's a completely different number. @vitaliidodonov anything I missed?
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@jonahlau_ ·
Most companies mistake content for growth The result is budgets spent on people who can build an audience for themselves but not for a product. Those are different skills, and almost nobody talks about the gap. Real growth is picking two or three channels that can reach the right users, running them at a volume that feels unreasonable, and tracking what moves until something does. Most of that work happens in spreadsheets, not on timelines. Social presence and viral content are real channels, but they sit on top of a working funnel. Without the funnel, they generate noise that looks like traction. The companies that grow fastest this year will probably be the ones whose growth people nobody has heard of.
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@natiakourdadze ·
I recently discovered a new growth hack that SaaS startup founders use on X, Product Hunt, Hacker News and Reddit: 1. They set up Google Alerts, F5bot, ReplyGuy or BrandWatch for the competitors' products 2. Then, using these social listening tools, find discussions that mention their competitors 3. And leave comments that follow this framework: "Any reason why not using X instead of Y (competitor’s product)? Way better if you do not want to {problem agitation and/or unique selling proposition}" 4. People get curious and start googling the alternative 5. As a result, this improves SEO, gets them mentions, backlinks and customers
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@MarketingMax ·
Growth hack #472: Ask your best customers how they would explain your product to friends, then test that language everywhere Bad marketers never speak to their customers
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@ericdjav ·
My app went from 859 to 2,223 new users in one month. No ads. No VC. No Product Hunt launch. Here's the exact growth loop. → Lewis posts a video → Viewers download the app → App sends a streak notification → Users come back daily → Lewis posts again The creator x builder model is the cheat code.
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@adrien_brbr ·
Things that actually moved the needle for my SaaS: - Hard paywall from day one (free tier = $0 revenue for weeks) - Affiliates at 40% commission (beat all my own marketing combined) - Reddit 3x/week in niche subreddits (not r/startups) - TikTok 2x/day, reverse-engineered from viral trends - IndieHackers website 3x/week Things that wasted my time: - Product Hunt - Generic startup subreddits - Posting on 5 platforms at 20% effort each What's working for you that nobody talks about?
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@iamfra5er ·
THIS GUY NICHED DOWN SO HARD HE WENT FROM $0 TO $23K/MO IN ONE VIRAL POST stefano spent a year pivoting his design tool 3 times and barely made any money then he noticed something weird: the only people actually happy with his product were the ones designing mobile apps so he said screw it, deleted everything else, and rebuilt the entire tool to do ONE thing: generate mobile app designs with AI posted a demo to reddit. got some conversations going. then dropped it on X with a simple hook: "comment sleek for early access" that post hit 1M views their AI costs went so high during the launch they panic-deployed a paywall. conversions died instantly. they had to roll it back within hours day one revenue: $2,500 that was already more than the previous product made in an entire year the unfair advantage wasn't the tech or the AI, it was that he stopped trying to optimize a mediocre product and just found a problem people actually cared about solving most founders keep adding features to products that don't matter. stefano just started over and picked the right problem now they're at $23.4k/mo with 90% margins because acquisition cost is basically zero all organic. all X and reddit. no ads goal: $200k/mo in 12 months
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@M__Operators ·
Where is our next dollar best spent? In paid media, that’s your north star. @connorrolain (Head of Growth, HexClad) answers that question with a 3-step testing process: 1️⃣ Channel Holdout Split your audience into two groups. One keeps seeing your ads as normal. The other gets nothing from the channel you’d like to test. If the dark group buys just as much, those customers would have bought anyway. The channel was taking credit for sales it didn't cause. Every ad platform does this (they all have an incentive to overclaim). A holdout bypasses all of it and asks: does revenue drop when we turn this off? 2️⃣ Scale-Up Test Great, it's incremental. But at what spend level does it stop being incremental? Run three cells. One cell at normal spend, one at +50%, one at +75%. The cell where incremental returns drop off — that's your ceiling. 3️⃣ Optimize the Channel Now you're testing inside the channel itself. - Brand videos vs. direct response - View content vs. purchase Which tactic gets you the best cost per incremental order? Not the best in-platform ROAS, but the best real-world result … As Connor Rolain puts it: “That's all incremental really means. It's additional. You would not be getting that outcome — or that audience, or that conversion — if you were not doing that tactic.” Check out episode 103 of Marketing Operators where Connor Rolain (Head of Growth, HexClad), @codyplof (CEO, Jones Road Beauty), and @couuor (CMO, Ridge) break down their entire incrementality playbook.
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@adrien_brbr ·
Added UTM tracking to every link this week. Every tweet. Every Reddit post. Every IndieHackers article. Every bio link. utm_source on all of them. Took 20 minutes. Used PostHog. Now I know exactly which platform brings real signups. Not views. Not clicks. Actual users who create an account and pay. Before this, I was posting on 7 platforms and guessing which ones worked. That's not a strategy. That's hope with a spreadsheet. PostHog is powerful. Maybe too powerful. I use maybe 10% of it: session replays, event tracking, web analytics. That's enough. You don't need 47 analytics tools. You need one that answers: where did my last customer come from?
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@oliverbrocato ·
Something I taught myself founding and scaling Tabs to $11M at 21: Growth in ecom is NEVER clean. Sometimes u even catch a RUN of steps back: Week 1: Spent $20k, made $90k (5x ROAS) Week 2: Same ad dies, CPA up by $25 (1.4x ROAS) Week 3: Burn $15k testing, nothing hits Week 4: Random UGC we almost cut does 10x If u zoomed in on Week 2–3, u'd think ur cooked. But zoom out to 90 days? Net positive. The problem: most founders judge progress in 7-day windows. They hit a run of bad weeks and think they're failing when they're just catching variance. U need a window big enough to see the actual trend. That's what separates quitters and winners.
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@TheecomMike ·
a friend’s store was stuck at $180k/month. for months, he couldn’t push it past it. ads were healthy. product was strong. team was solid. so he told himself what everyone tells themselves: “it’s a creative problem.” his solution? new angles. more UGC. different hooks. he spent ~$55k trying to prove it. didn’t move. one day we sat down at a cafe and pulled up the numbers. cohort data by acquisition month. 18 months. repeat purchase rate: 13%. flat. didn’t matter what he did on ads. 87% of customers bought once… and never came back. he was spending ~$42k/month acquiring customers and losing almost all of them after the first order. every month was a reset. same bucket. same leak. we looked at the post-purchase experience: thank you email. shipping notification. review request at day 30. that’s it. no reason to come back. no timing. no path to the next product. we rebuilt retention from the ground up: – post-purchase flows by SKU – winbacks based on actual repurchase behavior – SMS that felt human – cross-sells based on what customers actually bought next repeat purchase rate went from 13% → 29% in a quarter. that $180k ceiling disappeared. he hit $260k within 60 days. no increase in ad spend. he thought the problem was acquisition. it wasn’t. the growth was sitting in retention the whole time. untouched.
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@TheecomMike ·
about 2 years ago i was sitting in a café in Porto going through my own store numbers. it was a tuesday morning. good coffee. no calls until the afternoon. my store was doing well. solid 7 figures. but something had been quietly bothering me for months that i couldn't name. nothing obviously wrong. every time i tried to scale ad spend past a certain point the returns would soften. CAC would creep up. margins would thin slightly. i'd pull back. stabilise. try again. same thing. i'd convinced myself it was a paid media problem. tested new angles. brought in a creative consultant. restructured campaign architecture twice. nothing changed the pattern. i ordered another coffee and just sat there staring at the numbers with no agenda. then almost by accident i pulled up something i hadn't looked at properly in a while. customer cohort data. specifically repeat purchase rate by acquisition month going back 18 months. what i saw stopped me. month after month. regardless of which campaigns were running, creative performance, anything i'd been optimising. repeat purchase rate was sitting between 14% and 17%. completely flat. 18 months of customers, acquisition spend. and roughly 85% of every customer i'd ever paid to bring in had bought once and left. i sat with that number for a long time. the problem wasn't the ads. i'd been trying to fix a retention problem with acquisition solutions for 18 months. every time CAC crept up i'd optimise the ad account. but CAC was creeping up because i was replacing lost customers instead of keeping them. i was filling a leaking bucket and calling it scaling. went back to the store that afternoon and looked at the post purchase experience properly for the first time. thank you email. shipping update. review request at day 21. that was it. 18 months. millions in revenue. and virtually nothing built to bring a customer back after the package arrived. spent the next 6 weeks building a real retention system. segmented post purchase flows. winback sequences properly timed to actual repurchase behaviour. SMS that felt like it came from a person. a cross sell architecture based on what my best customers were actually buying in sequence. repeat purchase rate went from 15% to 31% over the following quarter. CAC dropped without touching a single ad. i think about that tuesday morning in Porto a lot. i'd been optimising the most visible part of the business for 18 months. while the real problem sat quietly in a cohort report i hadn't opened in over a year. the answers are almost always already in the data. you just have to slow down long enough to actually look.
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@sarah_carusona ·
In 2026 my team will oversee almost $100M in revenue for 𝐬𝐮𝐛𝐬𝐜𝐫𝐢𝐩𝐭𝐢𝐨𝐧 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬. I've seen the good, the bad, and the ugly. And at this point, we know exactly what works. While I'm not launching my own brand anytime soon (one day....) But if I did, here's exactly what I'd do 👇 1. 𝐌𝐚𝐤𝐞 𝐬𝐮𝐫𝐞 𝐭𝐡𝐞 𝐩𝐫𝐨𝐝𝐮𝐜𝐭 𝐢𝐬 𝐚𝐜𝐭𝐮𝐚𝐥𝐥𝐲 𝐬𝐭𝐢𝐜𝐤𝐲. Dog food = sticky. Pasta subscription = not so much (unless it's really good pasta). You've got to be honest with yourself >> Is it likely the consumer will cancel because they can find an easier/cheaper/better alternative? How long will the consumer get benefit from the product? Is there a layer of belief in what the product does (think supplements) that needs constant reinforcement? 2. 𝐁𝐞 𝐩𝐫𝐞𝐩𝐚𝐫𝐞𝐝 𝐭𝐨 𝐥𝐨𝐬𝐞 𝐦𝐨𝐧𝐞𝐲 𝐨𝐧 𝐚𝐜𝐪𝐮𝐢𝐬𝐢𝐭𝐢𝐨𝐧 >> 𝐨𝐧 𝐩𝐮𝐫𝐩𝐨𝐬𝐞. Subscription brands are built on acquisition volume and LTV. If you have real confidence in your product, give yourself room to break even or even lose 5-10% on that first order. It opens up your ability to test creatives, messaging, and offers at a pace you can't afford otherwise. 3. 𝐎𝐛𝐬𝐞𝐬𝐬 𝐨𝐯𝐞𝐫 𝐭𝐡𝐞 𝐩𝐨𝐬𝐭-𝐩𝐮𝐫𝐜𝐡𝐚𝐬𝐞 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞. Not just the email series. The unboxing. The insert that educates them about what your product does. The little things that make them feel like a part of something. Those are the things that move LTV beyond just product stickiness. 4. 𝐋𝐞𝐚𝐫𝐧 𝐟𝐫𝐨𝐦 𝐜𝐚𝐧𝐜𝐞𝐥𝐥𝐚𝐭𝐢𝐨𝐧𝐬 𝐟𝐚𝐬𝐭. If you're betting on losing money upfront, you better know exactly why people are churning. What are they telling you on the way out? How fast can you use that to tighten the experience or improve/adjust the product? The strategy is simple: sticky product, calculated risk on acquisition, obsessive post-purchase. Execution is where it gets hard 😉
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@aigleeson ·
The most followed accounts in every niche figured something out that nobody is teaching. They post every single day. Sometimes twice. I spent 3 weeks going through the top 50 accounts in 6 different niches on Instagram. Not to scroll. To study. I tracked posting frequency, caption length, content format, and engagement rate across every single account. What I found broke everything the "post less, post better" crowd has been telling people for years. The accounts with the highest follower growth were not the ones carefully curating one perfect post a week. They were posting every single day. Some of them twice. And the growth gap between them and the weekly posters wasn't small. It was embarrassing. So I went deeper. The algorithm has one job: keep people on the app. And it does that by showing people content from accounts they already engage with. The more you post, the more chances you give the algorithm to put you in front of your own audience. The more chances it puts you in front of your audience, the more chances they engage. The more they engage, the more it pushes you to new people. Frequency is not the enemy of quality. Disappearing for a week is. The second thing I found was about what daily posting actually does to your skill. The accounts posting every day were not just growing faster. They were getting visibly better every month. Their hooks got sharper. Their captions got tighter. Their content sense got stronger. You cannot think your way to better content. You have to post your way there. The weekly posters were treating every post like a performance review. The daily posters were treating every post like practice. And practice compounds in a way that careful deliberation never does. The third thing was the hardest to accept. Consistency is not just a growth strategy. It is a trust signal. When someone finds your account and sees you posted yesterday, and the day before, and the day before that, they follow you because they know you will show up tomorrow. When someone finds your account and your last post was eleven days ago, they keep scrolling. The most followed accounts are not more talented than everyone else. They just never gave the algorithm a reason to forget them. Volume without quality is noise. But quality without volume is a secret. Post like you mean it. Post like tomorrow depends on it. Because on Instagram, it does.
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@aymanalabdul ·
The 80/20 Growth Rule: - 80% of your resources on what’s already working - 20% on new experiments At AppSumo, one small test (switching from credits to cash payments for referrals) became an 8-figure revenue channel Test small. Scale what works
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@oliviaakory ·
We simulated a year of marketing decisions 36 million times, and we are now sharing everything we found. I thought about not posting this on a Saturday but no need to pretend that we aren't thinking about causal inference 7 days a week over here at Haus... First, why do we invest so much in our estimators and improving experiment precision at Haus? Because an experiment doesn't create value just because it produces a lift estimate. It creates value when that estimate leads to a better decision – scale the channel, pull back, hold, retest. If the signal behind those decisions is noisy, doing more of them doesn't average you toward the truth, it means you make more wrong turns, faster. We've watched this play out anecdotally for years. But anecdotes aren't numbers. So Patrick Hillery built a simulation that modeled a full year of experiment-driven budget decisions, varying only the two levers a team actually controls: how precise their measurement is, and how often they test. What we found: - Acting on noisy results left the business worse off than doing nothing 38% of the time, more than twice as often as the precise approaches. - You can't test your way out of noisy signals with higher testing volume. Brands running noisy experiments finished ahead no more often at 15 tests a year than at 6. - A strong experimentation program is worth double digits. The precise, high-cadence approach delivered a 13.2% average revenue lift, more than double the noisy approach's payoff (5.6%) at the same cadence and limit. - A tight confidence interval can be manufactured. Some methods look precise by hand-picking a few well-matched markets, but the result only holds for those markets. In these cases, precise results aren’t necessarily accurate ones. I'm linking in thread the full article, methodology walkthrough and companion spreadsheet we are calling Monte Carlo, and we are making it available to all.
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@Hartdrawss ·
This reddit user SaaS hit 0 → $25K MRR and exit in < 2 years his advice? painfully simple. here's the breakdown : 1/ PLG didn't get him from 0 to 1 >clean signup meant nothing without buying intent >he called almost every trial user early >most calls were awkward and useless >a few completely changed his positioning 2/ demos became the learning loop >self-serve didnt mean skipping the call >demos dont scale, but learning does >confused users exposed hidden product gaps >live objections made the product sharper 3/ content worked late, not early >he wrote zero content early, big mistake >old posts generated inbound near the sale >specific articles became long-term acquisition assets >content felt useless before it compounded 4/ specific content beat polished advice >generic startup advice got ignored fast >exact failures made the lessons believable >wrong assumptions created the strongest posts >founders trust scars more than frameworks 5/ boring problems made the business >B2B finance teams were leaking money >not sexy, but expensive enough to fix >clear ROI made buying easier >boring pain created real willingness to pay the actual lesson: >talk before automating >demo before scaling >write before ready 0 to 1 is uncomfortable. thats why founders avoid it.
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@ascorbichelix ·
🚀 Startup Concepts Every Founder Should Know [Part 3] In Part 2, we explored Competitive Advantage, Network Effects, and Switching Coste, the concepts that help startups defend their position once they've built something valuable. But before any of those matter, a startup first needs to answer one question: Do people actually want this product? Let's look at three concepts that explain how successful startups find product-market fit and scale from there 1. Product-Market Fit (PMF) Product-Market Fit is the stage where your product solves a real problem for a specific group of customers so well that they keep coming back and actively recommend it to others. Before PMF, growth often feels forced. After PMF, customers start pulling the product instead of the company constantly pushing it. Signs of Product-Market Fit include: - Strong customer retention - Word-of-mouth referrals - Increasing organic growth - Customers saying they would be disappointed if the product disappeared Example Imagine you build an AI coding assistant. Initially, developers try it but continue using other tools because it doesn't offer enough value. Over time, you add a planning mode, task checklists, significantly improve code quality, reduce hallucinations, and make it consistently follow software engineering best practices. Developers now rely on it for their daily work, use it across entire projects, and recommend it to their teammates because it has become an essential part of their workflow. That's a strong indicator of Product-Market Fit. 2. Growth Loops A growth loop is a system where each new user helps generate future users. Instead of relying only on paid marketing, the product itself drives growth. Example Imagine you build an AI resume platform. A job seeker creates a polished resume using your AI tool and shares a review link with mentors or friends for feedback. They also share the resume with recruiters and hiring managers during job applications. The mentors, recruiters, and hiring managers discover the platform, recommend it to other candidates, or use it to create and review resumes themselves. Those new users then share resumes with even more people, bringing additional users onto the platform. Every new user helps attract more users, creating a continuous growth loop. 3. Flywheel A flywheel is a self-reinforcing cycle where improvements in one part of the business make every other part stronger. As the cycle repeats, growth becomes easier and faster. Example An AI coding platform attracts more developers. More developers generate more feedback and bug reports. That feedback improves the model. A better product attracts even more developers. The cycle keeps reinforcing itself, making the business stronger over time. Many of the world's most successful companies are built around powerful flywheels rather than one-time growth hacks. Thanks a lot for staying till the end!! Wait for Part 4! #startups #tech #business
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@elgermerlo ·
How I get my first 100 users without ads: - Find 3 Reddit threads where your problem is being complained about. Comment with actual help, not a pitch - DM every person who liked a competitor's launch post on X - Post in niche Slack/Discord communities — not product spam, just "who deals with X?" - Write one SEO post targeting a very specific pain point, not a broad keyword - Do 5 manual onboarding calls. Embarrassingly hands-on. Worth every minute Distribution isn't a strategy you set up once. It's a habit.
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@SSage38676 ·
Most early-stage founders chase followers and grow linearly. The winning ones build growth loops that compound. Here's what keeps you stuck in linear: - Posting without capturing demand - Cold DMing without building trust first - Not building audience lists - Tracking the wrong metrics - Outreach without a strategy - No funnel strategy - Not optimising your signup-to-purchase flow You're working hard. But linear effort gives linear results. You only compound when you build the right growth foundations. Think of outreach as a sampling process — build trust first. A focused, engaged audience will always outperform a large, passive one. Build your growth loop. That's where the compound begins.
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@NFX ·
How to move faster: Adopt a mindset of rapid experimentation. Your seed round is a bank of experiments. The goal is finding product-market fit. Years ago, a typical startup might run 5-10 experiments during its seed stage. Today, we see some running 50-100. More experiments mean a wider scope of ideas tested. You discover what actually works, not what should work. Perfect it from there according to real data, taste, and vision. The market rewards learning from doing.
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@rfunk82 ·
Tracking growth publicly as I build #Talo. 1 week update 👇 Current user acquisition: Building Talo | User Acquisition: ▓▓░░░░░░░░ 53/300 Goal: 300 companies. Current: 53 companies. +23 companies in the last week 🚀 Top acquisition channels: • Organic TikTok content • Partnerships with mentors & coaches What's been most exciting is that many of these users are coming through word of mouth and community referrals. Also, Talo was built entirely on @Replit, which has allowed us to move from idea to product faster than anything I've used before. 17.7% of the way there. #buildinpublic #replit #saas #startup #cleaningbusiness #smallbusiness #talo #replit @zhenthebuilder @MannyBernabe @raymmar @amasad @HL3rd_ @nickco @amapel @samuel_spitz @agi2asi
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@Nate_Google_ ·
if you're spending over $300k/month on google, when is the last time you tested whether your branded traffic is actually incremental? actually driving net new revenue, not conversions you would have gotten anyway? we had a brand spending $350k/month on google sign with us because we didn't sound like every other google ads agency trying to sell them media buying. media buying is only half the battle. we do it the best, but that's not what brands at scale care about most. they care about measurement. proving the spend you're driving is added net new customer revenue. we have these conversations all the time. we're currently running a geo-holdout test for another brand that's been hesitant to scale youtube because they've scaled on meta for the life of the business, so youtube reads to them like a retargeting tool. we're taking youtube to $10k/day, then holding spend flat in a set of matched control DMAs while we scale the test markets. matched controls, not just our historically strong markets, because if you pull spend from your best DMAs you bake in selection bias and regression to the mean and your incrementality read is junk. this has to be done for both meta and youtube, because it resets the platform CAC and ROAS targets you've set in your MTA stack (northbeam, triple whale, etc). example: say you're running a $55 CAC target on both meta and youtube. if you find youtube's iROAS is higher than meta's, you can tolerate a higher reported CAC on youtube, because the true incremental cost per customer is lower than the platform number says. and you can't test it once. iROAS decays as you scale, so you re-test at different spend levels to see where diminishing returns kick in. youtube might run a 1.7x iROAS at $10k/day and a 1.5x at $30k/day. the CAC targets should move with the level of scale, not stay fixed. this is where MMM earns its place. incrementality experiments are point-in-time and you can't run them continuously across every channel. MMM is always-on. it captures cross-channel halo, saturation curves, and longer-term brand effects across the entire ecosystem, and you calibrate it with the geo experiments so the model is grounded in causal truth instead of correlation. that's how you keep making data-driven allocation decisions at scale instead of guessing why you can't hit CAC anymore. measurement triangulation, MTA plus incrementality experiments plus MMM, is one of the most important pieces of the puzzle for brands at scale. almost none of them are doing it correctly. we're working on getting certified through google's meridian partner program so we can build MMM and incrementality in-house. not renting another 3rd party platform's black box and trusting their number. owning the measurement.
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@robaiapps ·
Reddit is the best acquisition channel for B2C apps. But Redditors can smell a marketer from a mile away. My exact strategy: - Find highly specific niche communities - Answer questions genuinely - Drop the link ONLY when it perfectly solves their problem - High intent traffic > viral vanity metrics 📈 Are you using Reddit for growth yet?
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@rcmisk ·
growing on X without posting cringe "growth hacks": - say something specific, not something safe - reply to people with an actual take, not "great point!" - post when you have something real to say, not to stay consistent - let your failures be public before your wins the accounts I watch grow fastest aren't optimizing for virality. they're just relentlessly honest about what they're building and what isn't working.
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@elgermerlo ·
Distribution moves that actually worked for me at zero ad spend: — replied to niche subreddit posts where my product solved the exact problem being described (no spam, genuine answers) — posted the same content on X and LinkedIn same day, LinkedIn consistently outperformed on reach — turned support conversations into public content — real questions, real answers — found one person with a small but engaged audience and asked them to try it for free None of this is glamorous. All of it compounds.
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@SSage38676 ·
Most founders treat growth like a launch. Build. Ship. Push hard for a few weeks. Then it slows — so they plan the next one. That's not growth. That's a treadmill. Real growth is a system. You build the machine: funnel, messaging, campaigns, landing pages, tracking, conversion fixes. Then you make it repeatable with one simple weekly loop: → Run a few focused experiments → Watch the right metrics → Review what worked → Ship one real improvement Every week. Without fail. Small wins stack. That's the whole point.
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@MehulFanawala ·
Everyone loves talking about growth. Until you ask about churn. Over the last few weeks, I have been meeting founders, some in person and some online, asking a simple question: “How is growth going?” Almost everyone had a good answer. But when I asked the next question “What does your churn look like?” The energy in the room changed. Here is a simplified version of what I kept seeing: Founder A 10% churn, 12% growth Founder B 12% churn, 10% growth Founder C 15% churn, 16% growth Founder D 5% churn, 10% growth Founder E 3% churn, 9% growth At first glance, Founder C looks like the winner. Highest growth. But when you look closer, something interesting appears. The founders chasing growth the hardest are also losing customers the fastest. And the founders growing slower? They barely lose customers. The reason is simple. Most founders are obsessed with acquisition. Very few are obsessed with customer experience. When growth becomes the only goal, teams start ignoring the product gaps, the support tickets, the onboarding friction, and the small frustrations customers feel every day. Revenue comes in through the front door. Customers quietly leave through the back. But the founders who focus on customer experience build something different. They grow slower. But they keep their customers. And over time, that compounds. Lower churn means: • Higher lifetime value • More referrals • Less pressure to constantly chase new customers • More predictable revenue In the long run, the founder growing at 9% with 3% churn often makes more money than the founder growing at 16% with 15% churn. Because growth without retention is just temporary revenue. The real growth engine is not acquisition. It is keeping the customers you already worked so hard to earn.
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@jiayuan_jy ·
Recently, I did some research about @ahrefs. Ahrefs started as a tiny bootstrapped SEO tool built by a solo engineer who put his own savings on the line. Today it does $100M+ in ARR, is still independent, and competes head-on with giants. Meanwhile, its rival Semrush just agreed to be acquired by Adobe for $1.9B. Here's the story of Ahrefs: > be geeky engineer obsessed with backlinks > hack nights building your own web crawler > put ~$300k personal savings into servers instead of a house > launch basic backlink checker, niche SEO folks notice > no VC, no sales team, just ship and support users > move team to Singapore, keep headcount lean > answer support tickets yourself, fix bugs same day > 2015: hire first marketer, Tim, when ARR still under eight figures > decide “we’ll just teach SEO better than anyone” > publish deep tutorials, case studies, experiments > every blog post quietly pulls in more customers > no tracking pixels, no retargeting, no crazy funnels > revenue compounds from a few million to $100M+ ARR > still no investors, still no outbound sales machine > 2025: headlines say “Adobe to acquire Semrush for $1.9B” > Ahrefs just keeps shipping features and content > users stick around because the tool actually works What makes this story wild is how boring it looks from the outside. No funding announcements, no hype cycle, no “growth hacks”. Just a founder willing to risk his own money, a product that keeps getting better, and a team that learns in public for a decade. While competitors chase exits and acquirers, Ahrefs shows another path: build slowly, own your distribution, and let trust compound. Don’t worry if you lack big logos, flashy investors, or a “strategic acquisition" coming up. Focus on solving a real problem, demonstrate your work, and keep going even when others get distracted.
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