More than just conversations
Why AI analytics matter
Your bot isn’t just answering questions. It’s shaping the customer experience. But without proper analytics, you’re flying blind. To improve your flows, increase conversions, and build better relationships, you need visibility into what’s actually happening in every conversation.
Most chatbot platforms offer little more than raw logs. Understanding user journeys or optimizing your flows? Not so easy.
With Chatbot Analytics, you could:
- Identify drop-off points in real time
- Track which messages or buttons perform best
- Compare flows across channels, times, and devices
- See what happens before users hand off to a human
And best of all: you don’t need a data science team to get insights.
The analytics gap
Why there’s no great solution yet
Traditional analytics tools were built for websites, not conversations. And most chatbot platforms focus on building flows, not understanding them. That’s why teams end up stitching together logs, guessing user intent, or skipping analytics altogether. It’s time for something better.
Most analytics tools focus on pageviews and funnels. They weren’t built for conversational interfaces. And the ones that claim chatbot tracking? They’re often clunky, complex – or intrusive.
TelemetryDeck is exploring a new path:
✅ Easy integration with your chatbot
✅ Event-based analytics for messages, replies, drop-offs
✅ Fully anonymized, privacy-first tracking
✅ Dashboards built for real humans – not just data teams
Let's build this together
Help us build it for you
We don’t want to guess what chatbot developers need; we’d rather ask. If you’re building, maintaining, or optimizing a chatbot, your insights are incredibly valuable. Tell us what you’re missing in your current tools, and we’ll use your feedback to shape a privacy-first analytics solution that actually works for you.
We’re seeing growing interest in chatbot analytics – and we want to build the solution the industry really needs.
But first, we want to hear from you.
Are you developing or managing a chatbot?
Tell us what you’d like to measure. What matters to you? What frustrates you?
Shape the future of privacy-first chatbot analytics!
Your input will help us build a solution that works for you. Of course you’ll get early access when we launch.
Fits right into your ecosystem
Integrate with existing tools for language builders
There's a missing link in your infrastructure – we want to be there.
LLM developers use a plethora of tools and services that enable them to build and improve their chatbots. Most of these have telemetry, so we should be able to plug right in there.
These tools parse user input and generate smart replies:
- OpenAI (ChatGPT / GPT API) – High-quality conversational AI via API.
- Google Dialogflow – NLU engine with integrations and intent management.
- Microsoft Bot Framework + LUIS – Enterprise-focused bot and language tools.
- Rasa – Open source NLU and dialogue management with on-prem hosting.
- Hugging Face Transformers – For custom LLMs and fine-tuning.
- Anthropic Claude / Mistral / Cohere / Meta LLaMA – Other LLM options for building smart bots.
For orchestrating conversation flows, managing sessions, and integrating APIs:
- Botpress – Visual interface + code, great for developers and non-devs.
- Microsoft Bot Framework SDK – .NET and JavaScript SDKs with rich features.
- Rasa Open Source – Python-based stack with conversation state, fallback handling, etc.
- Node.js / Python (FastAPI, Flask) – U
- Flowise / Langflow – Low-code tools for chaining LLM workflows.
- Langfuse – Build and evaluate your chatbot
To train your NLU models and test performance:
- Label Studio – Open source data annotation for chatbot training data.
- Prodigy – Fast, scriptable annotation tool for training NLP models.
How to measure the performance of a chatbot
What could you track with chatbot analytics?
Designed for Real Conversations
Chatbots speak in turns, not clicks. That’s why event-based analytics make more sense than pageviews or funnels. By tracking meaningful conversation events – like messages sent, replies chosen, or handovers to human agents – you’ll gain the insights you need to optimize every dialogue, without compromising user privacy.
Here’s what our system could analyze – always anonymized, never creepy:
messageSent– when a user sends a messagereplySelected– when a user taps a suggested replyconversationStarted/conversationEndedfallbackTriggered– when the bot fails to understandhumanEscalation– when a live agent is contactedconversionAchieved– based on your own logic
All data would be event-based, minimal, and cookieless – just like the rest of TelemetryDeck.
Thousands of organizations trust TelemetryDeck
- Organizations
- Apps
- Insights
- Events
FAQ
What is Chatbot Analytics?
Chatbot analytics help you understand how users interact with your chatbot – which flows work, where they drop off, and how to improve the experience.
Can I track chatbot performance without storing personal data?
Yes. With privacy-first analytics like TelemetryDeck, you can track behavior without collecting personal information.
Which platforms would be supported?
We’re currently exploring integrations for platforms like Dialogflow, Microsoft Bot Framework, Botpress, and custom-built bots.
Let’s Shape the Future – Together
Help us build the tool you’ve been looking for
Want better insights from your chatbot – without compromising on privacy?
You’re the expert on your chatbot. We’re experts in privacy-first analytics. By joining forces early, we can build a tool that truly fits your needs – simple, powerful, and respectful of user trust. Share your thoughts, and help us make chatbot analytics better for everyone.
