Support Board

AppSumo

Customers appreciate Support Board for its powerful automation, seamless integration with various platforms, and responsive customer support. While some users find the initial setup slightly complex and the interface a bit outdated, the overall consensus is positive. With a 4.5-star rating from 103 reviews and a 60-day money-back guarantee, it's a solid buy at $69.00. Give it a try and experience the benefits firsthand!

Visit product View on AppSumoDec 13, 2022

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Actual performance

103reviews

Made the leaderboard

Traction signals

Rating4.5 / 5

Purchases4,892

Launch Intel predictions

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AppSumoStrong fit for a featured deal · Strong signals: platform, reviews, interface · Missing: plus, intuitive, host

72%72% predicted probability of success on AppSumo, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

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

49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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

32%32% 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

18%18% 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

8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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