Reinventing the Activity Stream for Wishberg

Hacker News

Hey everyone, We've pushed a new Activity Stream (aka Wall) to Wishberg. We had set a very high benchmark for this - build something better than Facebook's wall, or at least match it in worst case. Here is what we have intended - a. Ability to discover interesting wishes & experiences. b. Discover new interactions - like / comments / reviews / requests / thanks / follow c. For new users - guide them towards power users whom they can follow based on interests. d. Analyze mutual relationships and suggest interactions of people whom they might be knowing but not following each other on Wishberg. We don't have tons of data like Facebook, good number of users and it was a product challenge to build something like this. Do let me know your feedback and how we fared. Post on blog: http://blog.wishberg.com/re-inventing-the-activity-stream-on-wishberg

Visit product View on Hacker NewsJan 31, 2013

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

78%78% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: reviews, users · Missing: plus, platform, intuitive

47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

15%15% 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.

Incorrect prediction on native model

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