# User Documentation ![](/files/-MkwC-8653VSvglLakJw) ACONA stands for Augmented Content Analytics - an open source tool that automatically analyzes and simplifies data, for example from server logs or existing (open source) analytics tools, and proposes concrete measures for optimizing content. To determine the success of a certain website or URL we developed an ACONA Success Scores Software that has a functionality to calculate individual success metric. Different page types require different criteria to determine success: scroll depth, number of conversions, number of interactions or a combination. This should be definable in the settings (depending on the existing data sources, a certain selection is suggested). This individual success indicator is then calculated for all important) URLs and can be queried via an API. In a simplified view ACONA consists of three components:\ 1\. The **ACONA Administration Tool**: This is a central site where users can create an ACONA user and set up their ACONA system and define settings. For us it will be available under [www.acona.app](http://www.acona.app). 2\. The **ACONA Data Warehouse**: Storage of the data with an API to query it. We have it running on data.acona.app. 3\. The **CMS integrations**: Used on the website that is analyzed. Here data and recommendations are shown. You will have to install one of the available integrations: WordPress, Drupal, Neos. ### [ACONA Administration Tool](/acona/user-documentation/the-backend-system.md) ### [CMS Integrations](/acona/user-documentation/wordpress-integration.md) ### [FAQ](/acona/user-documentation/faqs.md) ### Funded by netidee.at The project is funded by [netidee.at](https://www.netidee.at). --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://acolono.gitbook.io/acona/user-documentation.md?ask= ``` The question should be specific, self-contained, and written in natural language. 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.