Align AI vs. traditional product analytics tools
AI-native conversational products vs. traditional chatbots
New conversational products are coming day-after-day, powered by Large Language Models (LLMs) like GPT, Anthropic’s Claude, etc. These AI-native products are revolutionizing the way we communicate and interact online. But how do they differ from the traditional chatbots we’ve known for years?
At Align AI, we’ve distilled this down to 2 key differences:
1) From rule-based to personalized experiences
Traditional chatbot products are rule-based. Remember those experiences where you got really frustrated at the CS chatbot and you wanted to speak to a human agent? These experiences happen because traditional chatbots are structured to do very specific things based on the prior planning of a product manager. What this means is that these chatbots are more like your digital concierges locked in text — efficient, swift to respond to your questions. However, what rule-based chatbots lack is the personalized experiences that are enabled with AI-native conversational products. With AI-native conversational products, you can receive tailored experiences that are specific to you!
2) Broad, flexible experiences and features
An extension of personalization, AI-native conversational products are able to do much more things compared to a traditional chatbot. Think ChatGPT. You can ask it to summarize text, answer math questions, write new content for you, provide feedback on your writing, do a business analysis, etc. The possibilities are endless. Traditional chatbots on the other hand are limited in the experiences they provide.
Can’t we just analyze with a tool like Amplitude or Mixpanel?
The main type of data produced and saved from AI-native conversational products are conversations and text. The problem is that traditional product analytics tools like Amplitude or Mixpanel (we love these tools by the way!) aren’t built to effectively analyze conversational data. Traditional product analytics tools focus on analyzing event data such as button clicks, moving across pages, and more.
Align AI on the other hand focuses on conversational data, and enables you to analyze subjective conversational data (starting with text and evolving to other modalities), in real-time, while providing tools to help any builder easily understand what to do with the data in front of them.
Start analyzing conversational data, today!
Our goal is to work with builders who want to build better AI-native products that are hyper-personalized and aligned with users. If you are one of them, please feel free to reach out at support@tryalign.ai to learn more about Align AI or get started with your analysis!
Looking for more resources?
Read one of the guides below:
📄 Align AI 101: Getting started with AI-native data analysis →
📄 Case Study: How is an ed-tech product leveraging Align AI? →
link: https://tryalign.ai/
