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Real-time 4/20 cannabis sales dashboard using Estuary and Tinybird

Hacker News

Real-time 4/20 cannabis sales dashboard using Estuary and Tinybird

Built this dashboard to visualize cannabis sales in real time across North America during 4/20. The data updates live from thousands of dispensary POS transactions as the day unfolds. Under the hood, we’re using Estuary for data streaming and Tinybird to power super fast analytical queries. The charts are made in Tremor and the map is D3.

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: visual, tiny, using · Missing: mac, agents, macos
68%68% 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.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: visualize · Missing: mobile apps, ios, personal
56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
54%54% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: real time · Missing: web3, chat, crypto
37%37% predicted probability of success on BetaList, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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