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Relay – an update after three years on anonymous team check-ins

Hacker News

Relay – an update after three years on anonymous team check-ins

Three years ago I posted our product Signals here: https://news.ycombinator.com/item?id=34405962 It’s rebranded to Relay now. Same idea-ish. We’ve cut back a lot but leaned right into the anonymity aspect for staff. We believe that as long as we protect the ability of the team to have a voice without negative consequences, then management gets more accurate data to act on. And also that it’s managements role to listen and respond to the commentary, even if just to acknowledge it. We have definitely taken a hard path on this. The product requires strong management or team leads who aren’t afraid of criticism … funnily enough, that doesn’t make it easily saleable. But the businesses that are using it, and responding weekly to their teams concerns, do see a growth in trust and engagement. That lowers staff churn, increases institutional knowledge, etc. etc. Additionally - we’re an AUS based business where state laws on psychosocial safety are quite strict - we actually meet the reporting, recording and response requirements for that legislation. We’ve made loads of product improvements - AI generated summaries that keep context on the clients over time, easier account sign ups and logins, simpler pricing, better dashboards and an increase in anonymity through how we collect responses. Over the last three years we have learnt that we are not sales people. It’s our single biggest challenge. We’re just not good at it. So that’s something we’re trying to solve. It’s free to sign up and start using it. We’d love any and all feedback - the last time we posted was super valuable and I really appreciated everyones feedback.

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, context, single · Missing: mac, agents, macos
83%83% 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
80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: lua, ide, 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.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
46%46% 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
26%26% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: growth · 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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