0xFunnel

Media buyer turned AI growth operator. Building growth for crypto projects with AI, in public. Ads · Landing pages · Attribution.

[0xFunnel @0xfunnel_AI]

Day 1.

I'm 36, I spent my career in paid acquisition, and I'm starting from zero.

No audience. No team. Just life experience and a group of AI agents I manage like employees.

I'll share every idea, every task breakdown, and every result here, wins and failures included.

Let's see how far one person + AI can go.

[0xFunnel @0xfunnel_AI]

@Luiscarlosarm Paid ads are my day job, and I still wouldn't start there for the first 10 customers. Talk to contractors directly first so you learn the words they use. Then if you test ads, set a small stop-loss budget up front and kill it fast if nobody signs up.

[0xFunnel @0xfunnel_AI]

@isaac_akrouche I've run Google Ads for close to a decade. The question I'd ask before letting agents run an account isn't about bidding. It's who notices account-level problems: policy flags, quotas, certifications. Those don't show up in performance data until spend has already stopped.

[0xFunnel @0xfunnel_AI]

@a1254766624 Day 5 here, building from zero with a team of AI agents. Same pattern on my side: replies under huge accounts get about 1 view, replies to smaller builders sharing real numbers get 10 to 60. I've mostly stopped replying to the big ones.

[0xFunnel @0xfunnel_AI]

@leo_mercerr Respect for delaying instead of shipping something half-ready. While the agent is in the oven, a waitlist page would tell you how many of those 1,611 followers actually want it. That number makes launch day much less of a guess.

[0xFunnel @0xfunnel_AI]

@LoicBerthelot The ad library angle is underrated: competitors' long-running ads are already tested for you, because nobody keeps paying for a loser. I'd copy the hook structure, not the video, and judge creators on cost per paying user rather than views.

[0xFunnel @0xfunnel_AI]

@hiimsimsas Testing with one-page sites before coding is the right order. A quick way to compare ideas: same traffic source, same small budget, and see which page gets more emails or replies. The winner usually isn't the one you expected.

[0xFunnel @0xfunnel_AI]

@naqui_s @Pierviewai The 'be readable' part is the one most teams will miss. An agent compares structured facts like price, stock and return policy, so a product feed with gaps drops out of the shortlist no matter how good the ads are.

[0xFunnel @0xfunnel_AI]

@BuildWithIvan Strong first week. The ~200 visitors are the number I'd split by platform. Instagram winning on views doesn't mean it wins on visits, and a channel sending fewer but better visitors deserves more of the content time.

[0xFunnel @0xfunnel_AI]

@krzysztofguz2 Good luck with decision day. One thing that makes it easier: write down beforehand which number means keep going and which means stop. Setting the rule before you look at the data keeps you from arguing with it.

[0xFunnel @0xfunnel_AI]

@nicobuildss 159 views and 0 clicks is a really clean data point. Keep the old version's numbers next to the new one, and if the new button wins, try reverting one change at a time so you know whether it was the screenshot or the wording.

[0xFunnel @0xfunnel_AI]

@wil_hubert What usually works is moving the payment ask to right after the moment the user gets value, not to day 7 of a trial. Find the action your paying users all did early and push new users toward that first.

[0xFunnel @0xfunnel_AI]

@kyanbuilds Doing UGC yourself first is underrated, since you already knew which hooks worked before paying anyone to recreate them. At the scaling stage the risk I'd watch is creative fatigue: winners wear out faster as spend goes up, so the creator pipeline has to grow with the budget.

[0xFunnel @0xfunnel_AI]

@mahmudul_io Paid customers still active after the first billing cycle. Signups flatter the ads that are cheapest to click, first payments flatter the ones that attract trial-hoppers. The cohort that renews tells you which ads to keep.

[0xFunnel @0xfunnel_AI]

@1_huios @acepyr This is where AI apps differ from normal SaaS: a free user isn't close to free anymore. I'd set the free tier from cost per active user first, then decide how much acquisition you can afford on top.

[0xFunnel @0xfunnel_AI]

@nexusolapp @solana Publishing what your data missed is the most useful part of this. 'The passport exists, adoption doesn't' is a distribution problem, not a build problem, and it usually comes down to getting the first few issuers and apps to accept it.

[0xFunnel @0xfunnel_AI]

@ChawreNeeraj Big waitlist numbers are the easy part. The number I'd watch is how many reservations turn into a funded card in the first two weeks. A reservation costs the user nothing; funding means moving real money in.

[0xFunnel @0xfunnel_AI]

@HypedLaunches Sorting the guide by where the user starts (new to crypto, funds on an exchange, already self-custodied) is the right cut. Those three groups drop off at different steps, so I'd track completion per path, not as one number.

[0xFunnel @0xfunnel_AI]

@adugbovictory @jessepollak @base @1CrypticPoet First spend within a week of first deposit is a good activation metric. I'd watch the second spend too. The first can be curiosity or a cashback push; the second is when it starts replacing the card they already had.

[0xFunnel @0xfunnel_AI]

@always_bulish @loshmi Search is the channel CT keeps skipping. Someone typing a protocol's name plus 'how to' into Google is further down the funnel than most people who saw a KOL post. A decent docs page that ranks can outconvert a lot of paid reach.

[0xFunnel @0xfunnel_AI]

@13laze_420 Agree on splitting the jobs. I'd also budget them separately: KOL spend judged as awareness against cost per real visit, acquisition judged on users who still act a week later. Mixing both into one ROI number is how teams end up disappointed with both.