Hey hunters!
I’m Luciano, the CTO of ScopeAI. We were part of the YCW17 batch (previously known as Quiki). Thanks so much for hunting us @katmanalac!
ScopeAI automates the process of communicating user insights to product and operation teams. Our product leverages natural language processing (a form of AI) to extract insights from customer support conversations.
We integrate with existing support channels such as Zendesk, Intercom, Desk.com (salesforce) to automatically tag and analyze conversations for trends in customer feedback. Our product automates the current process of:
1. Customer support teams manually tagging support tickets
2. Tracking and documenting trends
3. Communicating insights to product and operation teams
Our goal is to replicate the functionality of a customer insights team through software! Would love to hear your feedback and answer any questions!
@dariaevdo I used to do UX research and the process for extracting trends from user interviews was completely manual. I'd codify the conversations and count how frequently certain feedback was mentioned! We knew that that there needed to be a better way of extracting trends from unstructured data and started working on ScopeAI :)
@natalieabeysena congratulations with the launch!
Curious why you didn't do ScopeAI for UX interviews but for support? Or you plan to tackle the UX side as well in future?
@iloveluce - I love this! We just started using intercom, and are naturally seeing similar requests. We're extracting insights manually/anecdotally - doing this with Scope would be really powerful.
Great work!
Love this. Would be really neat if ScopeAI also integrated with big releases / updates to an app -- so you could see if certain things break or become more complicated with a new update.
Congrats on building this. Two questions:
1. Can you include some illustrated example of the kind of insights the system generates, on your home page? I scrolled from top to bottom trying to get a direct example of it but couldn't find it. Imagine me recommending a friend to look at ScopeAI - I can't in a few simple words. An example on your homepage will help users do that.
2. Would this work with tickets where customers mix a bit of local language with English? (mixed multilingual support)
Thanks.
@dotmanish 1. That's a great recommendation - we'd like to include more informative screenshots, so that's really valuable feedback! 2. Generally homogeneity in language works better for the analysis (accuracy is higher) but we do capture tickets with some mixed languages. In this case, we mark the non-english word as an irrelevant entity instead of translating!
A lot of product services and repair companies would greatly benefit from this. I wonder how Apple could integrate this to enhance their Customer service goals.
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