The gap between what platforms report by default and what trading teams need to decide is widening. These are the metrics that close it.
Kept order value, not gross order value
Gross revenue includes items that will be returned. For fashion brands running home trial or high return categories, kept order value is the figure that reflects actual commercial outcome.
Tracking kept revenue separately from initial checkout value prevents overstated performance reporting and supports more accurate margin analysis.
Trial-to-keep rate by category
Aggregate return rate hides category-level variation. Denim, footwear and knitwear carry different keep profiles.
Trial-to-keep rate by category informs buy depth, size curve allocation and promotional strategy. It also flags product issues earlier than warehouse return counts alone.
AOV by order type
Comparing average order value between trial orders and standard buy-now orders reveals how confidence changes basket behaviour.
Brands often find trial customers order more units per transaction. That insight reshapes how teams evaluate programme ROI against acquisition spend.
First-time buyer keep rate
New customers acquired through trial behave differently to repeat buyers. Isolating first-time keep rate shows whether the programme lowers first-purchase friction effectively.
Marketing teams use this to assess channel quality. Merchandising teams use it to identify entry categories that earn loyalty.
Return reason distribution
Knowing that returns happened is less useful than knowing why.
Structured return reasons across fit, quality, style and expectation mismatch turn customer feedback into product and content actions. Over time, reason trends predict margin leakage before it appears in P&L summaries.
Inventory recovery cycle time
Returns sitting unprocessed are unavailable inventory. Cycle time from customer return initiation to sellable stock affects cash flow and sell-through.
Operations leaders track this alongside conversion metrics because speed of recovery directly influences full-price sell-through.
From reporting to decision-making
Fashion ecommerce has outgrown generic analytics defaults. Teams managing trial and returns need a commercial view tied to behaviour, not just traffic.
Mirra Analytics surfaces these metrics in one dashboard so operators can connect customer decisions to revenue performance without stitching data across disconnected tools.
