> For the complete documentation index, see [llms.txt](https://fair-indonesia.gitbook.io/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://fair-indonesia.gitbook.io/docs/features/brand-analytics.md). # Brand Analytics A comprehensive view of your influencer marketing performance across all campaigns, creators, and platforms. *** ## Overview Brand Analytics aggregates data from all your campaigns into a single reporting layer. Instead of looking at each campaign in isolation, you can see how your influencer activity is performing as a whole — and identify what's working. *** ## Key metrics | Metric | Definition | | ------------------------- | -------------------------------------------------------------------------------- | | Total reach | Combined unique reach across all campaigns and creators | | Total impressions | Total number of times content was displayed | | Total engagement | Sum of likes, comments, shares, and saves | | Engagement rate | Average engagement rate across all content | | Cost per view (CPV) | Total spend ÷ total video views | | Cost per engagement (CPE) | Total spend ÷ total engagements | | Active campaigns | Number of campaigns running in the selected period | | ROI | Return on influencer investment (configurable based on your conversion tracking) | *** ## Filtering and date ranges All Brand Analytics data can be filtered by: * **Date range** — select any custom date range, or use presets (last 7 days, last 30 days, last quarter) * **Platform** — Instagram, TikTok, YouTube, or all combined * **Campaign** — one specific campaign or all * **Creator** — drill down to a single creator's contribution *** ## Campaign comparison Compare the performance of multiple campaigns side by side to understand which campaign types, creator tiers, or content formats drive the best results for your brand. *** ## Creator performance ranking The **Top Creators** view ranks all creators you've worked with by: * Total reach delivered * Engagement rate * CPV * Number of deliverables completed Use this to identify which creators are consistently delivering results and should be prioritised for future campaigns. *** ## Exporting reports All analytics data can be exported in two formats: * **PDF** — a formatted report suitable for sharing with stakeholders * **CSV** — raw data for further analysis in Excel or your BI tool *** ## Related * [Campaign Management](/docs/features/campaign-management.md) — manage individual campaigns * [Reading Your Analytics](/docs/guides/reading-your-analytics.md) — how to interpret your data * [API Reference](/docs/developers/api-reference.md) — pull analytics data programmatically --- # 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://fair-indonesia.gitbook.io/docs/features/brand-analytics.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.