> For the complete documentation index, see [llms.txt](https://docs.abtasty.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.abtasty.com/emotions-ai/understand-emotionsai/leverage-emotionsai-to-get-high-potential-ab-test-ideas.md). # Leverage EmotionsAI to get high-potential A/B test ideas Capturing the most important emotional need of each user is not only relevant when analyzing campaigns, it also opens new horizons in terms of understanding your visitors and the way your website meets their needs. EmotionsAI enables three key analyses toward this goal: 1. Identify the main profiles of your audience in terms of emotional needs. A dedicated UI will provide you with a very simple way to understand the main emotional needs across your whole audience, or at specific steps of the journey by using your preferred AB Tasty goals (page trackers, action trackers, etc.) 2. Analyze a page regarding its ability to engage users toward a main goal. The automated comparison between conversion rates and EmotionsAI segments provides a ranking to help you understand where emotional needs are not being met, and the impact that has on your conversion rates at a specific step in the journey. By experimenting with new variations of some elements of your page, you can better align your experience with the unmet needs. A dedicated guide with best practices and examples is available to help you craft these great experiences. You can also find inspiration in this [library of customer case studies](https://www.abtasty.com/?s=emotionsAI\&category=case-studies\&sort=). 3. Analyze your website’s entire journey to surface the pages where there are the highest conversion losses due to emotional needs being unmet. In this ranking of pages, you have a clear guide on where to run tests as well as a clear hypothesis based on quantified emotional satisfaction - the perfect input for your experimentation roadmap. Experiments based on these segments have proven to be twice as successful as other tests. The journey analysis requires mapping your website, which can be done easily in a dedicated UI by simply arranging your already existing trackers to represent the main steps of your website. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.abtasty.com/emotions-ai/understand-emotionsai/leverage-emotionsai-to-get-high-potential-ab-test-ideas.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.