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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.

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.

Operator

Founders, CXOs, heads of ecommerce, GMs

Marketer

Growth leads, performance marketers, brand & creative

Data & analytics

Analysts, data engineers, BI leads

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Operator [#operator]

Founder, CXO, head of ecommerce, GM

You spend your time on

The P&L, channel-level profitability, inventory, pricing strategy, vendor and marketplace negotiations.

Your typical questions

“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:

What is Ocular

Read the 5-minute orientation.

Start with the question → Profitability & Margins

Every question an operator typically asks, mapped to the right module.

P&L

The waterfall view and channel comparison are the operator’s home base. (in Use Your Data → P&L)

Sales Performance

Top products, discount depth, holiday performance, new vs. repeat mix. (in Use Your Data → Sales Performance)

Purchase Retention Cohort

When leadership asks about LTV, CAC payback, or acquisition vs. retention. (in Use Your Data → Cohorts)

FAQs → Reconciliation

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.

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Marketer [#marketer]

Growth lead, performance marketer, brand & creative

You spend your time on

Ad spend allocation, creative briefs, attribution, campaign performance, channel mix, retargeting.

Your typical questions

“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:

What is Ocular

Orientation.

Start with the question → Marketing & Creative

Your most common workflows mapped to modules.

Marketing report

Blended ROAS, MER, per-platform performance, demographic and dayparting heatmaps.

Ad & Campaign Performance

Storefront Net ROAS vs. Ad Platform ROAS, attribution model selection, bubble chart for budget decisions.

Creative Deep Dive

For creative brief prep.

Ad Tracking Setup Guide

UTM, fbclid, gclid configuration. Do this once at the start of every new ad account.

Ad & Campaign Naming Convention

Make downstream reporting useful by getting names right at the source.

Attribution philosophy

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.

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Data & analytics team [#data-team]

Analyst, data engineer, BI lead

You spend your time on

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.

Your typical questions

“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:

What is Ocular + Salient features

Context. What is Ocular · Salient features.

Data modeling philosophy

How raw data becomes the unified semantic layer; facts, dimensions, derived metrics.

How your data flows

Ingestion → cleaning → enrichment → semantic layer.

Data Dictionary

The metric and dimension reference, A–Z. The single most-linked page in the docs.

Data Model deep dives

Sales, Customer Activity, Fulfilment, Meta Ads, Google Ads. One page per model.

Common analyses

Recipes for ROAS, retention, LTV, contribution margin, return rate — built in Chart Builder.

Chart Builder

For ad-hoc analyses and sharing the result with non-technical stakeholders.

Reconciliation FAQs

The patterns you’ll get asked to explain.
Skip for now: nothing. The data team typically needs the deepest read of the docs.

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Not sure where to start?

Evaluating Ocular

Read What is Ocular, Salient features, then skim Start with the question to see if your real-world questions are covered.

Implementing for the first time

Go to Setting up your workspace, then Implementation checklist.

Stuck on a specific issue

Start with the question is the fastest path. If a number doesn’t match a source, jump to FAQs → Reconciliation.