The tracking system consists of three automated scenarios that work together to provide comprehensive AIO monitoring. The first scenario handles query tracking and brand mentions, automatically sending prompts to ChatGPT and recording which sources appear in responses. The second scenario performs keyword performance analysis, tracking specific topics or phrases relevant to your business and monitoring whether you're gaining or losing visibility. The third scenario focuses on competitor tracking, identifying when competitors appear in AI responses and analyzing their positioning compared to yours.
Finding these queries requires a different research approach than traditional keyword research. Rather than using tools that show search volume and competition metrics, you need to understand what questions your target audience actually asks AI models. This means thinking about their problems, concerns, and information needs, then formulating those as conversational queries. Tools like an LLM Query Generator can help by analyzing your content and suggesting relevant questions people might ask to find that information.
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Individual gameplay features are implemented as API calls from the Unreal game client to our backend with the actual logic living exclusively in the C# microservice codebase. The service receives a request to perform a particular action on a specific player’s inventory. The service fetches the inventory from the Azure Cosmos database, confirms that the requested action is valid, modifies the inventory appropriately, persists the updated inventory back to the database, and returns a response to the game client that includes a list of all item changes as well as any other side effects that may have occurred from the action.