I

I built a tool that helps you talk with customers

Hacker News

I built a tool that helps you talk with customers

"Build something people want" - simple statement, not simple to execute. Having a product is a good start but the hardest part is crafting that product into something people actually love! You need to figure out a bunch of stuff about your users…here's a starting point: - Who actually needs your product and why? (persona, problem) - What message resonates strongly enough for them to care? (value prop, positioning) - Why are some customers sticking around? (product benefit) - Why are some customers leaving? (value gap, positioning misalignment) This is WAY harder than it sounds (speaking from personal experience)! And basically no one does it well. (only 10% of SaaS companies have quantified buyer personas) I think the big reason is it's actually REALLY hard to consistently talk with customers. --- Ok, here's why it's difficult to consistently talk with customers: 1. First, it's super inconvenient for customers - Most don't want to "jump on a call" 2. Second, if you do get them on a call - you'll likely get bad data - Humans don't like giving other humans bad news - You're at risk of confirmation bias or to just start selling (I'm guilty of this) - Consistently capturing this data / scaling this process is v time consuming 3. Third, surveys are another option but they mostly suck - Understanding customers requires depth which surveys lack - you need to ask 2-3 WHY questions to understand the root insight (and ideally get concrete examples to make that insight objective rather than subjective) - People have survey fatigue and don't take them seriously 4. Fourth, another option is to email "please give us feedback" - This is ok but it puts all the burden on the customer - Ideally you want to give them a bit more to work with than that 5. Fifth, drawing conclusions from qualitative data has historically been difficult - I.e. word clouds aren't that useful - It's difficult to extrapolate completely unstructured qualitative data with much rigor Said another way - surveys have structure but lack depth, human-led interviews have depth but lack scale = you need something that works for you AND your customers, too. --- Meet franko.ai - https://franko.ai/ Franko is an AI agent that has conversational depth but survey cost and convenience. This helps you talk to 100s of your customers each month, each as short semi-structured topical conversations. Getting setup takes just a few minutes 1. Add your business context 2. Configure an agent by generating (and reviewing) a "Conversation Plan" 3. Share the link (i.e. in an email sequence like churn or onboard) 4. When customers click, a ChatGPT-type interface opens up and they're guided from there 5. Once done, the transcripts, summaries, details, all appear in your dashboard --- Thanks for reading! Do you have a customer feedback loop built in for your product? Does this solution look like it would be helpful for you? All comments welcome :)

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
94%94% 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: agent, user, new · Missing: mac, agents, macos
91%91% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: personal, month, users · Missing: mobile apps, ios, entrepreneurs
61%61% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
33%33% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface, users · Missing: plus, platform, intuitive
27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue
24%24% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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