> For the complete documentation index, see [llms.txt](https://docs.struct.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.struct.com/reference/publication/publication-template/file-formats.md). # File formats ### PPTX (Microsoft PowerPoint) This is the presentation layer for your PIM data. Instead of manually creating slides, Struct uses this format to automatically populate templates with product images, features, and pricing. * **Primary Use:** Generating sales decks or "lookbooks" instantly. * **Structure:** A visual-first format where data is mapped to specific "placeholders" (text boxes or image frames) on a slide. * **Best for:** Sales teams who need a professional, editable pitch deck without the manual design work. ### XML (Extensible Markup Language) XML is the backbone of print automation. It is a highly structured, tag-based format that is both human-readable and machine-readable. * **Primary Use:** Feeding data into Adobe InDesign via tools like EasyCatalog. * **Structure:** Uses custom tags (e.g., ``) to define data hierarchy. * **Best for:** Complex catalogs where specific data points must be mapped to exact locations in a design template. ### CSV (Comma Separated Values) The "no-frills" format. A CSV is a simple text file where each line is a data record and each field is separated by a comma. * **Primary Use:** Quick data dumps or bulk updates to third-party systems. * **Structure:** A flat, 2D table (rows and columns) with no formatting, styling, or multiple tabs. * **Best for:** Fast, lightweight transfers of basic product lists where complex relationships (like variants) aren't the priority. ### JSON (JavaScript Object Notation) JSON is the modern standard for web and app integration. It is lightweight and handles "nested" data (like a product that has multiple sizes, which each have multiple colors) much better than a flat table. * **Primary Use:** Connecting Struct PIM to modern web storefronts or mobile apps. * **Structure:** Uses "key-value" pairs and arrays (e.g., `"Price": 19.99`). * **Best for:** Developers building custom digital experiences that require fast, hierarchical data retrieval. ### XLSX (Microsoft Excel) The gold standard for data management and auditing. Unlike CSV, XLSX supports multiple sheets, data validation, formulas, and formatting. * **Primary Use:** Exporting data for internal review, complex pricing calculations, or bulk enrichment. * **Structure:** A robust spreadsheet format that can handle large volumes of data while maintaining specific data types (dates, currencies, etc.). * **Best for:** Marketing and Product Managers who need to manipulate and "clean" data before it goes live. --- # 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 dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.struct.com/reference/publication/publication-template/file-formats.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. 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.