Reporting Deep Dive: From Resale Data to Better Decisions

TLDR: A resale report is useful when it tells you what to change on Monday. Watch units, sell-through, aging, and the gap between the price you recommended and the price you got. Pick one change for the week, then leave the other numbers alone until you can see what worked.

Four numbers, every week

You do not need a wall of charts. Pull these for the last 7 days and the last 30, by store and by department.

1. Units in and units sold. If intake is far ahead of sales, the floor or the listing queue is backing up.
2. Average selling price. Split floor and online. Mixing them hides whether the website is actually earning its fees.
3. Sell-through. Units sold divided by units available, over 30, 90, and 365 days. A pretty category with poor sell-through is overpriced or overbought.
4. Age. Share of units older than your markdown clock, such as 21 days on the floor or 30 days listed.

Write one sentence under the table: what you will change. "Markdown women's denim that is past 21 days" is a decision. "Denim is down" is not.

Compare the price you meant with the price you got

Keep three prices on the item if you can: the recommended price, the price staff accepted, and the price it sold for. The gaps tell you different things. If staff always cut the recommendation in half, the comps do not match your customer, or people do not trust the suggestion. If they accept it and the item still ages out, the demand is not there and the markdown clock should be shorter. If online sales land well under the comp, the listing is missing photos, specifics, or a title a buyer would search.

Route with the report, not with a hunch

Look at recovery after fees, not the sticker. A department that sells in a week on the floor should stay on the floor even if an online comp looks higher. A department that ages on the rack and sells online should be pulled at intake. Review that split once a month. Change the rule, then leave it alone long enough to learn.

HAMMOQ reporting is meant to sit on the same intake, price, and sale records, so these cuts are already in the data. The habit matters more than the screen: same four numbers, same day each week, one change written down.

What a Monday note looks like

This week is made up so you can see the shape. It is not a customer result, and it is not a target.

• Units in 420, units sold 310. Intake is ahead of sales, so the back room is growing.
• Floor average price $11. Online average price $38. Do not blend those into one number. The blend hides whether the website earned its fees.
• Women's denim is selling inside 30 days. Men's fleece is not. Fleece older than 21 days takes the markdown.
• Staff accepted the recommended price on most jackets and cut shoe prices in half. Sit with the shoe pricer. Either the comps are the wrong condition, or the suggestion is not trusted. Both can be fixed. Ignoring it cannot.

One change for the week: mark down aged fleece, and review shoe comps. Leave the rest alone until next Monday. A report that changes ten things changes nothing, because you cannot tell which change worked.

If you want to see these steps run with AI on your own items, book a demo and we will walk through them with you.