
Talklab
AI powered chat analytics for customer insight





About | Details |
---|---|
Name: | Talklab |
Submited By: | Godfrey Donnelly |
Release Date | 1 year ago |
Website | Visit Website |
Category | Analytics Customer Communication SaaS |
Say goodbye to generic customer service metrics and hello to AI-driven insights with Talklab. Our platform analyzes customer chats to offer detailed, actionable reports, from sentiment scores to behavioral tags. Lower churn rates, elevate customer satisfaction
TalkLab looks like an interesting platform for team communication. How does it enhance collaboration within teams? 💬
10 months ago
Hey there! Congrats on the awesome launch of Talklab! The AI-powered chat analytics for customer insight sounds super intriguing. One suggestion to consider for future improvements would be to explore integrating real-time sentiment analysis. It could offer even more valuable insights into customer experiences. Have you considered any unique use cases for Talklab in specific industries?
1 year ago
Wow, Talklab sounds like an incredible tool for customer insights! I'm excited about the AI-powered chat analytics feature. Can you tell me more about how it analyzes customer chats? Does it use natural language processing to understand sentiment and behavioral patterns? Also, I recently came across a study highlighting the importance of personalized customer service in reducing churn rates. Have you considered incorporating personalization features into Talklab? It could be a game-changer in terms of boosting customer satisfaction. I look forward to hearing more about your product and how it can revolutionize the customer service industry!
1 year ago
Now this is cool! What are some of the most common actionable insights your customer finds with this tool?
1 year ago
It appears to be a fantastic tool. Congratulations and best of luck! I'm curious about how you generate the topics you associate with each customer conversation. Are you using ChatGPT for this?
1 year ago
Hi Willian! Congrats on the launch. In my first business project over 10 years we control customer support every day be reading all messages and listening all voice records. It works, we really keep the qulity of our customer support service. But it's a human-factor. The QA who checks it, with time can be not so strong with the mistakes. Also they start friend and the quality of testing becomes weaker in time. Also we have the exam system which analyze the work of every agent and gives rating. But it's not AI driven and takes a lot of resources. Your tool can help us and a lot of B2B companies who cares about the customer support. I think I can start test it the nearest time. What about your monetization scheme?
1 year ago