> For the complete documentation index, see [llms.txt](https://dshub.gitbook.io/ds-hub/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://dshub.gitbook.io/ds-hub/geospatial-analysis/gsa-at-work.md). # GSA at Work As we defined in the [Geospatial Analysis (GSA) Basics](/ds-hub/geospatial-analysis/geospatial-analysis-basics.md) section, GSA is the process of studying entities by examining, assessing, evaluating, and modeling spatial data features. Businesses can use geospatial analysis to: * Identify new business opportunities * Assess market potential * Optimize market presence * Examine factors that are specific to a geographic region * Enhance new data-driven offerings * Optimize store locations and product offerings * Optimize delivery routes and reduce transportation costs * Identify what stores should be consolidated to decrease sales cannibalization risks Businesses can use geospatial analysis to optimize trade areas: * Model and evaluate site strategies through visualization of demographics, competition, traffic and migration patterns, and more * Ensure equitable opportunity for virtual and in-person sales * Understand where potential acquisition chains' customers live in relation to existing or potential business sites * Identify what stores should be consolidated to decrease sales cannibalization risks Here are some examples of geospatial analyses from different Industries: McKinsey & Company -[ Supercharging retail sales through geospatial analytics](https://www.mckinsey.com/industries/retail/our-insights/supercharging-retail-sales-through-geospatial-analytics) Carto - [How Location Intelligence improves trade area coverage during retail mergers and acquisition](https://carto.com/blog/mergers-acquisitions-location-intelligence) ESRI UK & Ireland - [Increasing Retail Sales by 150 Percent with GIS Data and Analysis](https://www.esriuk.com/en-gb/arcgis/products/arcgis-business-analyst/marketsource-case-study) Kontur - [Using Geospatial Data to Find the Best Business Spot](https://www.kontur.io/blog/population-density-score/) --- # 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://dshub.gitbook.io/ds-hub/geospatial-analysis/gsa-at-work.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.