AB Experiment - LLM AI Assistants and Websites

**Overview**
A/B EXPERIMENTING WITH CONVERSATIONAL INTERFACES, AI Assistants, Chatbots and Websites.

**Use cases**

- Experiment with LLM Prompts
- Experiment with Websites
- Experiment with conversational interfaces - chatbots, AI Assistants
- Experiment with LLM RAG approaches
- Experiment with Models

**Product details**
Harness the power of qualitative and quantitative data to drive the future of your Data Product. Do traditional A/B testing with AB Experiment.

The playground for experimentation is vast for LLM and conversational interface- experiment with different LLM, different embedding provider, different ways to query vector DB.
Prompt enginering have many experiment and user try different tone, persona, design variation. In addition test different visual design and see how user interact with website and chatbot.
Response design is another area to explore and determine whether user like detail, summary, graphs format.

- chatbot ratings
- website clicks
- ecommerce conversion
- price data. - ctageory
- campaign data
-
For more details, refer to the embedded notebook.

**Additional Insights**
Add any additional insights on the listing here. This can include relevant links pertaining to research related to the listing dataset, etc.

搜集汇总

背景与挑战

背景概述

该数据集专注于LLM AI助手和网站的A/B实验，支持在对话界面、聊天机器人及网站中进行测试，涵盖LLM提示、RAG方法、模型和视觉设计等多方面的实验。它利用定性和定量数据，帮助用户通过传统A/B测试方法优化数据产品，包括测试不同LLM、嵌入提供商和响应设计等关键领域。