Documentation Index
Fetch the complete documentation index at: https://wiki.platelunchcollective.com/llms.txt
Use this file to discover all available pages before exploring further.
Context Map
A Context Map is a structured analysis of the topics, questions, and intent clusters where a brand needs to appear in AI-generated responses. It identifies the semantic territory a brand must be present in, the gaps between where a brand currently appears and where it needs to appear, and the content and entity work required to close those gaps.
How It Works
AI systems build understanding of a brand by associating it with topics, questions, and other entities. A brand that is strongly associated with a specific topic is more likely to appear when that topic is queried. A brand with weak or inconsistent topical associations appears inconsistently or not at all.
A Context Map starts with identifying the queries a brand’s audience is asking across AI search surfaces. It then maps where the brand currently appears in responses to those queries, where competitors appear, and what the content and entity signals are that determine those outcomes. The output is a prioritized list of topics and content gaps.
When You Need It
A Context Map is useful as a starting point for any AI search engagement. It surfaces where the work is needed before execution begins, and provides a benchmark for measuring progress over time.
Work with Plate Lunch Collective on a Context Map
