Overview
A category performance report helps a category manager keep one collection or product family out of spreadsheet limbo. This playbook installs a category metrics table and a working review document so each recurring readout can connect performance movement to merchandising actions and evidence gaps.
It is deliberately narrower than a full ecommerce dashboard. Use it when a collection owner needs durable category-level state: the same category boundary, the same comparison frame, the same open questions, and a clear place to record what changed since the last review.
Juno can start from pasted metrics, uploaded exports, existing workspace tables, collection URLs, or manually supplied updates. It does not require a Shopify, analytics, or warehouse connection to replace the minimum workflow.
Why you should review category performance separately
Storewide ecommerce reports are useful, but category decisions often happen one level down. A strong total revenue week can hide a weak collection, a stock issue can make a category look demand-constrained, and a promotion can lift orders while squeezing margin.
Shopify's analytics guidance describes reports for sales, behavior, marketing, and customers, which reflects how many lenses ecommerce teams already juggle (Shopify Help Center). Google also notes that ecommerce measurement depends on sending the right recommended events before reports can show item and purchase behavior (Google Analytics Developers).
The messy part is turning those signals into a category owner decision. Juno keeps the readout compact: what moved, what evidence supports it, what is missing, and what merchandising action should happen next.
Step-by-step
- 1Confirm the store or brand, category or collection in scope, reporting period, currency, review cadence, and the decision the category manager needs to make.
- 2Set up the installed workspace with a primary Category metrics table and a Category review document for the recurring readout.
- 3Record available category metrics such as revenue, orders, units sold, sessions, conversion rate, AOV, margin, inventory notes, promotion context, top products, and evidence links.
- 4Compare the category against the chosen frame, usually the previous comparable period, a target, or a known merchandising benchmark.
- 5Separate likely causes across demand, traffic, conversion, order value, margin, inventory, promotion, assortment, and measurement gaps without inventing unsupported numbers.
- 6Update the review document with the current readout, recommended merchandising actions, risks to watch, owners, and evidence gaps to resolve before the next run.
Frequently asked questions
Is this the same as an ecommerce dashboard?
No. The ecommerce dashboard covers storewide trading metrics. This playbook is a focused category workbook replacement for collection-level decisions, history, evidence, and actions.
What data do I need for a useful first run?
Start with the category name, period, comparator, and any available metrics. Revenue, orders, units, sessions, conversion rate, AOV, margin, inventory notes, and promotion context are useful, but Juno can mark missing fields instead of blocking the whole review.
Does it require Shopify or Google Analytics access?
No. The default workflow uses Juno's installed table, document, web review, and scheduling capabilities. Connected sources can improve confidence later, but they are not required for the minimum replacement.
How often should category managers run it?
Weekly works for active merchandising cycles, promotions, and fast-moving categories. Monthly is better for slower collections where the team needs trend review rather than rapid trading action.