fforward is an AI Co-pilot for Product Teams
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Max Cameron

fforward.ai - Copilot for customer interviews

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Product teams use fforward to unlock insights and patterns in their user interviews and build a better product roadmap.

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Rayan de silva
When starting a business, it's critical to identify actual customer pain points. Many founders rely only on their intuition, believing they have all the answers; however, using actual data to support judgments can be quite helpful. Thank you for your assistance!
Cameron Westland
Maker
@rayan_de_silva It's *great* to have intuition. We believe it's *greater* to use that intuition to place bets and gather evidence to support or refute them! Our aim is that fforward helps you gather that evidence 10x faster than before.
George Francis
This is very amazing and interesting Giving every PH user three free interviews analysis credits it's impressive. Great projects that will transform lives.
Cameron Westland
Maker
@georgefrans52 thank you! Yeah those credits are pretty valuable. We use A LOT of OpenAI compute for each interview.
Akhere
This is an impressive work. Keep it up!
Cameron Westland
Maker
@akhere12eth we will!
Ziauddin Rafiat
It's evident that fforward recognizes the importance of customer interviews in informing product decisions and acknowledges the time-consuming nature of analyzing them. By conducting interviews with various professionals in the field, they aim to streamline this process and empower teams to make informed decisions efficiently. Congratulations on your launch and UpVoted.
Cameron Westland
Maker
@ziauddin_rafiat thank you so much. You're 100% on all accounts!
Amirali Nurmagomedov
Congratulations on the launch @maxcameron
Cameron Westland
Maker
@maxcameron @amirali_nurmagomedov thanks for supporting.
Sulman Agha
Wow that's awesome Congrats on the launch! Does it also do the interviews transcripts (e.g. can it attend a gmeet and take notes?)
Cameron Westland
Maker
@sulman_agha not it doesn't. Most video conferencing apps have built in support for transcripts now. We take those as input!
شهاب الأوتشيها.
Yes, Walado Abkarat was amazing, it is definitely better.
Cameron Westland
Maker
@new_user__020202487ed5537bea122ad Thanks for participating!
David Banks
Interviewing customers is one of the best parts of the job. Organizing all the notes and mining for insights is one of the worst. So far fforward has been able to save me and my team hours of time and dozens of post-it notes.
Cameron Westland
Maker
@davidbanks totally agree! Nothing so painful as to be *punished* for speaking to customers because you're under-utilizing your takeaway data.
George Gevorkian
Well done team, much needed such a helpful product!
Cameron Westland
Maker
@george_gevorkian Thank you George!
Lindsay
Congrats Cam, Max and Jon! As a designer, researcher and product leader, I see the value in having AI supported analysis and synthesis of data. Couple of questions: how does the AI know what themes, needs and opportunities to highlight? Does the user have to tag or generate labels for the data to identify what to pay attention to? And assuming it distinguishes between the interviewer and interviewee so it's focusing on the right data? I have used Momentum.io and it mixes up the interviewer responses with the interviewee responses so the data can be biased to what the interviewer is saying. Looks awesome! Can't wait to try it ;)
Cameron Westland
Maker
@lindsay6 sweet questions! > how does the AI know what themes, needs and opportunities to highlight We have a calibration phase during onboarding which helps align the model to the specific types of problems you're discussing with your users. From there, it's about trying to go line-by-line through the transcript to identify relevant opportunities to that calibration. > Does the user have to tag or generate labels for the data to identify what to pay attention to? No, since we're using a foundational LLM under the hood, no tagging or labelling is required other than the calibration. > And assuming it distinguishes between the interviewer and interviewee so it's focusing on the right data? Yes, the first thing the user does when analyzing a new transcript is identify the interviewee so the analysis can know where to focus. Thanks for your support!
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