> For the complete documentation index, see [llms.txt](https://docs.chord.co/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.chord.co/model-your-data/model-amplifications/advertising-spend.md). # Advertising spend ## Advertising spend {% hint style="info" %} Note: Our Model Amplifications feature **only accepts files in CSV format at this time.** Please make sure the files you upload are CSV files. {% endhint %} ## Overview Many advertising sources provide direct connections to our data warehouse, like Facebook, Google, Pinterest, TikTok, and YouTube. But what if your brand spends advertising dollars on other sources? The Advertising Spend configuration allows you to include any source in our Ads modeling. All that's needed to include a source is the date of the spend, the amount spent, and the name of the source. This allows the model to capture a high-level view of the spend by source. Unlike connected data sources, the configuration is limited to overall spend per source and does not drill down into more detailed information on campaign or metrics like views, clicks, and impressions. ### Sample use case Brands can easily extend their enriched Chord data set to include Ad Spend data and answer more robust business questions about return on investment by channel, campaign, and even demonstrate product interests by channel. --- # 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.chord.co/model-your-data/model-amplifications/advertising-spend.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.