PageWisr
Indie HackersFind what’s costing you customers, and fix it fast
As a builder, I’ve spent way too much time wondering why a website wasn’t performing the way I expected. I built PageWisr to answer that question. It exists to give founders and builders the honest feedback they need to
Share cardActual performance
1followers
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting72%72% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, io · Missing: https docs, excited, just released49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: builder · Missing: plus, platform, intuitive40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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BetaListId
Identifying, Segmenting and Contacting our Customers51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Identifying, Segmenting and Contacting our Customers
Hacker News11Ou
Our first three featured customers57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Our first three featured customers
Hacker News3Fi
Fix Firefox46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Fix Firefox
Hacker News10kant.au17%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
See everything. Fix it before anyone notices.
Indie Hackerscommitment-side-projectFlareLog28%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Your AI can't fix what it can't see
Indie Hackerscommitment-full-timeInsightify68%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Know what customers love — and what to fix — automatically
Indie Hackerscommitment-side-projectAuklet.io49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Fix Software Problems Before Customers Find Them
Indie Hackers2aiIndexMachine30%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Fix "Discovered: currently not indexed" limbo fast
Indie HackersAthena34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Know what to Fix. Fix it first!
Indie Hackerscommitment-full-time