Simple paywall and micropayment add-on for your website

Hacker News

Hi HN users, we've built a simple add-on which allows website owner to individually paywall content. Add-on allows website visitor to micropay anywhere between 5 to 15 cents to access a paywalled content. Check up an explanatory GIF at: https://zen.market Ad-generated revenue keeps falling. Some publishers have installed soft paywalls which push website visitors to start monthly subscriptions. However, the way paywalls are usually implemented is unfriendly and discourages visitors from paying. Most publishers report that only 0.1-0.3% of their site's visitors become paying customers. Micropayments is a visitor-friendly option for earning revenue from your content. We recently surveyed 338 visitors of news websites (news websites in Google Consumer Surveys network, USA, age 18-44) and asked about their preferred payment method for the online content: https://s3-us-west-1.amazonaws.com/zenmarket/338.png Over 84% of respondents preferred a pay-as-you-go paywall with micropayments. If you'd like to demo the paywall as a website visitor, please go to: http://asiatoworld.com/2016/03/07/there-are-worlds-biggest-and-deepest-lakes-located-in-asia-it-is-amazing/ Email: demo@zen.market Password: demo We've signed up one blogger so far and I am currently working on getting warm introductions and setting up meetings with LA-based publishers. We're based in LA. I would be very grateful for any feedback and any advice on B2B sales from HN community! Thanks!

Visit product View on Hacker NewsApr 26, 2016

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best fitHighest predicted score across all platforms for this description.

AppSumoStrong fit for a featured deal · Strong signals: friendly, users · Missing: plus, platform, intuitive

62%62% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Strong signals: google, user, new · Missing: mac, agents, macos

61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: month, google, monthly · Missing: mobile apps, ios, personal

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Acquire.comPre-revenue stage for this audience · Strong signals: revenue, subscription · Missing: arr, mrr, profit

25%25% 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, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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