Wiwo – Find events happening around you. Google Maps, but for events.

Hacker News

Hey everyone in the USA! I'm developing a map-based event discovery platform that helps people find unique and exciting events in their city or area. I imagine that it could help young locals who are searching what is to be attended in their area & tourists who are visiting and want to find what to do in the area. But before I unleash it on the world, I need your help! One major pain point that I am trying to solve is information overload and difficulty in discovering relevant events nearby. Traditionally, people might rely on social media, local newspapers, or word-of-mouth to find events happening around them. These methods can be: Scattered: Information is spread across different sources, making it time-consuming to search. Unfiltered: Showing a large amount of events, not necessarily relevant to individual interests. Limited information: Often lacking key details like event descriptions, schedules, or ticket options. So my MVP address these issues by: Aggregating: Bringing together event information from multiple sources in one place. Personalization: Using filters and user preferences to recommend relevant events. Visualization: Displaying events on a map, allowing users to discover events based on location and proximity. Detailed information: Providing comprehensive descriptions and links to purchase tickets. What other features I plan to build: Build-in resell marketplace, own event upload, live-streaming, PPV and more. However I find it difficult to get any feedback on the platform. I've tried paid ads, posting to other Early Adopters websites, personally reaching out to people, who I think are target users, but do not get any meaningful feedback. So I'm eager to hear your honest opinions: What works well in the platform? What needs improvement? Are there any features you'd like to see added? Your feedback will be invaluable in shaping the future of Wiwo! P.S. For now only US users are needed, as other won't find events in their areas :)

Visit product View on Hacker NewsFeb 21, 2024

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

81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

80%80% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: lua, io · Missing: https docs, excited, just released

21%21% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: paid · 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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