Talklab

AI-Powered Chat Analytics for Customer Insight

5.0•2 reviews•

107 followers

AI-Powered Chat Analytics for Customer Insight

5.0•2 reviews•

107 followers

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Customer support tools

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CRM software

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ChatGPT Prompts

Our platform analyzes customer chats to offer detailed, actionable reports, from sentiment scores to behavioral tags. Navigate through your conversations searching by topics and filter selected chats using natural language prompts. Lower your churn rates and elevate customer satisfaction, changing generic customer service metrics to AI-driven insights with Talklab.

Free Options

Launch tags:

Analytics•Customer Communication•SaaS

Launch Team

Willian Valle

Talklab

Maker

📌

Hello Community! 🖖 I've been working with software development for almost 20 years now, having founded a software house (named SofaCoding) that operated from 2014 to 2018. In recent years, I've been working a lot with customer support and messaging markets, which alerted me to the deficit of information that companies have about what their customers are demanding in support channels. With the recent popularization of large language models, I decided to start a product that could use the companies’ chats and tickets to answer some key questions: 1. What are the main topics that are leading customers to support channels and how the appearance of these topics is evolving over time? 2. Who are the customers that have demonstrated negative sentiments lately, such as frustration or anger? Thanks to the PaLM 2 and GPT3.5 language models, the first public version of Talklab can answer these questions and many more. Currently, our software only integrates with the Zendesk platform, enabling Zendesk users to import chats and tickets. Then, Talklab will automatically generate data about the content of each chat. Using the generated tags, it's possible to create reports based on groups of tags and for a specific time period. We're launching a preview version today that enables the Product Hunt community to explore a demo workspace and create prompt-generated filters, which we are calling 'smart tags.' To access the demo, please head to https://talklab.tech Additionally, we're opening a free-beta whitelist registration that you can join here: https://forms.gle/z4LR2dMop66CAZBq6 -- Willian Valle 🇧🇷 willian@talklab.tech

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2yr ago

Anna Kasumova

Ploito

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?

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2yr ago

Willian Valle

Talklab

Maker

@anna_kasumova Hi Anna. Thanks a lot for your feedback! I believe that, whether using humans or ai, it’s important for the customer support market develop an objective set of parameters that define the quality of a service. So that we can avoid the bias and randomness that both ai and humans have. During Talklab development, I tried a lot of prompts to achieve a fair score of quality, but currently talklab just presents a score that identifies the mood of the customer, which is not suitable to identify the service quality. But, I haven't given up yet 😂 and I’m constantly looking for works or discussions in this field. About monetization: It's the decision that is keeping me awake at night. 😅 It seems clear that I'll pursue a SaaS, subscription-based model, but I haven't determined the pricing yet. I have significant variable costs, primarily based on the number of characters sent to language models. Therefore, the plans should feature different thresholds for character counts per billing period. Do you think it would be acceptable to charge based on the number of characters processed per month?

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2yr ago

Anna Kasumova

Ploito

@vallewillian I think that easier - to make monthly subscription based pricing, without symbol limits. Why? Because pricing MUST be clear for customers. And even I with a lot of experience, I really can't understand the quantity of symbols. It's hard to calculate and understand. Better if you will calculate yourself, and based on your understanding, you make pricing which cover all expenses.

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2yr ago

André J

Now this is cool! What are some of the most common actionable insights your customer finds with this tool?

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2yr ago

Willian Valle

Talklab

Maker

@sentry_co Hi André :) Thanks for the feedback! (are you a brazilian, btw? 😆) Generally speaking, I believe these are the greatest value deliveries that the tool can bring: 1. What are the main topics that are leading customers to support channels and how the appearance of these topics is evolving over time? 2. Who are the customers that have demonstrated negative sentiments lately, such as frustration or anger? The insights brought by the first question can help service teams identify and respond faster to customer demands, while the second question can help reduce churns.

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2yr ago

André J

@vallewillian I added it to my PH collection. Will revisit when we start rolling out a bit more widely. And no, I'm Norwegian.

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2yr ago