quick intro: ex-google growth. took pangaea from $5k to $2.4m arr, now building quickads ($3m arr). here i test ai ad tools, ugc pipelines and aeo in public - real numbers, ugly truths, zero pitches. what's the one growth channel you actually trust right now?
@illaigescheit did charging from day 1 change what you built first - do paying customers pull the roadmap somewhere different than free users would have?
@kade_hinkle weeks of crickets on the same accounts, then one copy change and 4 replies - how do you read that: the list was right all along and copy was the blocker, or too small a sample to tell yet?
@itsjacobbreton what happens to the positive replies that land when nobody on the team is awake - does someone always cover, or do those just eat the drop to 5%?
@federicomolinac where does the loom and manual calls setup break first - too many customers to onboard one by one, or the founder just gets tired of the same call every day?
@yerenkucuker on distribution first - what did flipping the order look like in practice this time? did you have the channel or audience picked before building, or find it while the product was still small?
@RennieHaylock that tracks with the deadline doing the selling for you. would you run the same month-long play again on another event, or does the next one need year-round demand to be worth it?
@itsbongoo the number i keep coming back to: 2,261 new customers against 82 active subs. where's the drop - people trying it once and leaving, or trial-to-paid?
@MordyOberstein when you say attributable traffic from LLMs isn't fundamentally viable - is that because the clicks themselves don't convert, or because the attribution tooling can't see them? those are pretty different problems.
@hankleber on the 1m/week referral drop - did the letter attribute it to a specific surface like AI overviews, or is it aggregate search traffic? and did they say whether the logged-in tests recovered any of it?
@joshwhitfieldai the gap i'm curious about: 1,081 unique replies against 190 booked calls - what does the reply-to-booked conversion look like? is the drop in qualifying replies or in getting them to pick a time?
@iamsikandar92 quick question on the X posts: are they showing the 24h-unblock moment itself - someone trying to open a blocked app and hitting the wall - or describing the feature? that moment is the demo i'd lead with.
@foundurslab free from competitors at what usage level though - are your most active users actually staying inside those free tiers, or hitting their limits? the ones hitting limits are who you charge.
@DanniChenGTM you tracked week-2 generation alongside CAC - did week-2 activity actually predict who was still around at day 30, or did the two metrics move independently?
@0xbono the education outlier is interesting - 23.5% of trials starting 31+ days after install. does the report say whether those late starters convert at the same rate, or should education apps treat the first session differently?
@boomerrbryan on the 52%: how concentrated is that across the 207 channels - a few monster videos carrying the number, or a pattern that holds for a typical channel? that's the difference between a repeatable formula and a lottery ticket.
@souptikdn the no-sign-up choice is the interesting one. where does invoice history live then - if someone needs to pull up a six-month-old invoice at tax time, are they on their own to keep the links?