> ## Documentation Index > Fetch the complete documentation index at: https://docs.ocular.dev/llms.txt > Use this file to discover all available pages before exploring further. # Choose your path > A persona-routed reading order for the Ocular docs — pick the role closest to yours (founder, marketer, analyst, ops) and follow the curated path. Ocular serves three primary audiences. Each has a different reason to open the docs, and each benefits from a different starting point. Pick the one closest to your role. Not sure which one fits? Most ecommerce teams have someone in each of these roles. Read the role description and pick the one whose questions you spend the most time on. Founders, CXOs, heads of ecommerce, GMs Growth leads, performance marketers, brand & creative Analysts, data engineers, BI leads *** ## Operator \[#operator] *Founder, CXO, head of ecommerce, GM* The P\&L, channel-level profitability, inventory, pricing strategy, vendor and marketplace negotiations. "What's my true contribution margin this month?" "Which channel is actually profitable?" "Are returns eating my margin?" "Is our discount strategy working?" **Your reading order:** [Read the 5-minute orientation](/overview/what-is-ocular). [Every question an operator typically asks](/overview/start-with-the-question#profitability), mapped to the right module. The waterfall view and channel comparison are the operator's home base. *(in Use Your Data → P\&L)* Top products, discount depth, holiday performance, new vs. repeat mix. *(in Use Your Data → Sales Performance)* When leadership asks about LTV, CAC payback, or acquisition vs. retention. *(in Use Your Data → Cohorts)* For the moments when a number doesn't look right. **Skip for now:** the breakdown-level data models and the metric/dimension dictionary. You don't need them. *** ## Marketer \[#marketer] *Growth lead, performance marketer, brand & creative* Ad spend allocation, creative briefs, attribution, campaign performance, channel mix, retargeting. "Is my ad spend actually working?" "Which creatives should I brief next?" "Which campaigns are wasting budget?" "Why doesn't my Meta ROAS match Shopify?" **Your reading order:** [Orientation](/overview/what-is-ocular). [Your most common workflows](/overview/start-with-the-question#marketing) mapped to modules. Blended ROAS, MER, per-platform performance, demographic and dayparting heatmaps. Storefront Net ROAS vs. Ad Platform ROAS, attribution model selection, bubble chart for budget decisions. For creative brief prep. UTM, fbclid, gclid configuration. Do this once at the start of every new ad account. Make downstream reporting useful by getting names right at the source. When you need to defend the numbers, this is why Ocular says what it says. **Skip for now:** the data-model deep dives. The Marketing, Ad & Campaign Performance, and Creative Deep Dive modules surface everything you need without going to Chart Builder. *** ## Data & analytics team \[#data-team] *Analyst, data engineer, BI lead* Custom analyses, building dashboards for the org, validating numbers against source systems, owning the team's understanding of how Ocular's semantic layer is built. "How does Ocular define contribution margin?" "How do I build a custom retention cohort in Chart Builder?" "Why doesn't Shopify's revenue match Ocular's net revenue?" **Your reading order:** Context. [What is Ocular](/overview/what-is-ocular) · [Salient features](/overview/salient-features). How raw data becomes the unified semantic layer; facts, dimensions, derived metrics. Ingestion → cleaning → enrichment → semantic layer. The metric and dimension reference, A–Z. The single most-linked page in the docs. Sales, Customer Activity, Fulfilment, Meta Ads, Google Ads. One page per model. Recipes for ROAS, retention, LTV, contribution margin, return rate — built in Chart Builder. For ad-hoc analyses and sharing the result with non-technical stakeholders. The patterns you'll get asked to explain. **Skip for now:** nothing. The data team typically needs the deepest read of the docs. *** ## Not sure where to start? Read **What is Ocular**, **Salient features**, then skim **Start with the question** to see if your real-world questions are covered. Go to **Setting up your workspace**, then **Implementation checklist**. **Start with the question** is the fastest path. If a number doesn't match a source, jump to **FAQs → Reconciliation**.