Foodspan – Reduce your food waste

Hacker News

Hi Hacker News, For the past few months I have been working on a tool around helping people with their meal planning (meal prep). After doing some customer research via Facebook groups and Reddit /r/MealPrepSunday (check it out!). I found that meal planning individuals had these 3 problems: 1. Budgeting 2. Food waste 3. Finding recipes And so Foodspan was born (lifespan + food) to tackle this. Foodspan is rather simple, it works by: 1. Estimating a recipe's lifespan whether in the fridge or the freezer. 2. Estimating a recipe's cost per serving. 3. Alerting you when your cooked meals are about to expire. When released it will cost around £10-15 a month. I plan to add features around discovering cheap long lifespan freezable recipes. I would love to hear your feedback. https://foodspan.app/

Visit product View on Hacker NewsJan 13, 2019

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

83%83% 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.

Hacker NewsStrong engagement from HN community · Strong signals: hacker news · 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.

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

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

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

Product HuntUnlikely to reach the leaderboard · Strong signals: new · Missing: mac, agents, macos

25%25% predicted probability of success on Product Hunt, 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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