Fashion moves fast. New collections every season, trends shifting weekly, and return rates that would sink most businesses. StoreLyst gives fashion brands the per-SKU profitability, return analytics, and competitor intelligence they need to stay profitable at speed.
Fashion isn't a steady-state business. You buy inventory months ahead, mark down what doesn't sell, and try to predict what will trend next season. Without per-product margin tracking that accounts for markdowns and seasonal velocity, you can't tell if a collection was truly profitable.
Fashion has some of the highest return rates in ecommerce — 25-40% is normal. Every return is a double hit: you've already paid for fulfillment, and the returned item might not be resellable. If you can't track return rates per product, colour, and size, you can't fix the root cause.
A single dress comes in 5 colours and 6 sizes — that's 30 SKUs. Each has a different sell-through rate, return rate, and marketing cost. Shopify's native analytics show you product-level data at best, never the variant-level detail you need to make real merchandising decisions.
A competitor drops a new collection and your customers see it on Instagram within hours. By the time you notice, they've already captured demand you could have met. Without monitoring competitor activity, you're always one step behind the market.
Every feature built with fashion & apparel brands in mind.
Set COGS per colour, per size, per product. When you negotiate different rates for different colourways or when certain sizes cost more to produce, StoreLyst captures that granularity. See true margins at the variant level, not just the product level.
Learn more about COGS Tracking →Identify which specific variants drive the most returns. Is it the oversized fit in the S-M range? A colour that looks different in photos? A fabric that doesn't meet expectations? Pattern recognition at the variant level lets you fix problems surgically.
Learn more about Returns Analytics →Monitor competitor stores for new product additions, price changes, and collection launches. See what's trending in your competitive landscape before it shows up in your declining sales. Plan your assortment strategy with market data, not just gut feeling.
Learn more about Competitor Monitoring →Fashion catalogues are massive. Manually optimizing every listing's title, description, and tags for SEO is a full-time job. StoreLyst's AI handles it — writing compelling, keyword-rich copy that matches your brand voice across hundreds of products.
Learn more about AI Listing Optimizer →Here's what running your store looks like when everything works together.
Check P&L for your current season's collection. See which pieces are selling at full price, which need markdown consideration, and which are your unexpected hits. Compare against last season's performance at the same stage.
Review competitor activity from the last 48 hours. See new product launches, price drops, and collection themes. Use this intel to adjust your own pricing strategy and identify gaps in the market.
Run the AI optimizer on products with high impressions but low click-through rates. Improve titles with trending search terms, enhance descriptions with better size and fit information, and update tags for seasonal relevance.
Drill into return analytics by product category, colour, and size. Identify any patterns — maybe returns spiked on a specific fabric or a new fit. Create action items: update size guides, adjust photography, or discontinue problem variants.
End the day with a clear picture of which product lines are performing. Compare margin by category — dresses vs. tops vs. accessories — and factor in return rates for the complete profitability picture. Feed insights into next season's buying decisions.
Common questions from fashion & apparel brands about StoreLyst
Yes, this is one of StoreLyst's strongest features for fashion brands. You set COGS per variant, and the P&L dashboard shows margin at the variant level. So you'll know that your red dress in size M has a 62% margin while the same dress in blue size XL has only 41% after higher return rates.
By identifying exactly which products, colours, and sizes have the highest return rates, you can investigate root causes. Common findings include: sizing inconsistencies across brands, colours that look different on screen vs. in person, and fabrics that don't match the listed description. Fixing these issues at the source is far more effective than accepting high returns as inevitable.
Absolutely. StoreLyst's P&L dashboard lets you filter by custom date ranges, so you can compare this season's performance against last year's. You can also track sell-through velocity to identify which pieces will need markdowns before they become dead stock.
You add competitor Shopify stores to your monitoring list, and StoreLyst tracks every product change — new additions, price changes, removed items, and more. For fashion brands, this is invaluable for spotting trend shifts, understanding competitor pricing strategy, and identifying gaps in the market before planning your next collection.
The AI adapts to your existing listing style. It analyzes your best-performing product descriptions and maintains that tone while improving SEO and conversion elements. You always review and approve before changes go live — the AI does the heavy lifting, you maintain creative control.
Yes. StoreLyst is built for large catalogues. The AI optimizer can process hundreds of listings in batch mode, the P&L dashboard handles thousands of SKUs with fast filtering and sorting, and COGS can be imported in bulk via CSV. Scale is a feature, not a limitation.
Per-SKU profitability, return analytics, and competitor intelligence — built for fashion brands that want to stay profitable. Start your free 14-day trial.