TL;DR Summary:
Hammoq turns donated, returned, or secondhand goods into high-performing inventory with AI-powered price optimization.
Resale retailers have a pricing problem—and it’s hiding in plain sight.
Too often, used inventory gets priced with flat numbers like:
- $4.99 for basic tops
- $6.99 for jeans
- $9.99 for jackets
Why? Because it’s fast. It’s simple. It keeps things moving.
But here’s the downside: you’re likely underpricing your best inventory, and overpricing what won’t move.
Whether it's dealing with returns, donations, or second-hands, flat pricing schemes trade margin accuracy for velocity—and in 2025's resale landscape, that costs retailers real dollars.
Hammoq solves that.
It uses AI-driven pricing rules for donated, traded, or liquidated merchandise—accounting for:
- Past historical ASP
- Sell-through rate
- Store-level demand trends
- Brand, condition, gender, and size
- Seasonal trends and performance
The outcome? A tailored price tag for each item—without loading up your team's workload.
Why Flat Pricing Breaks
Flat pricing was designed for speed. But it fails to account for:
- High-ASP donations like Patagonia, Free People, or Coach
- Low-interest categories that sit at $6.99 for weeks
- Staff inconsistency—some underprice, some overprice
- Location-based differences in what sells and when
What’s fast for operations often becomes slow for sales.
Here’s what happens:
Flat Price Result
$6.99 for all denim Levi’s sells fast, but could earn $12.99+
$4.99 for t-shirts Branded athleticwear is undervalued
$9.99 for jackets
Budget brands stall too long, others fly
Flat pricing leaves money on the floor—and inventory growing old on the rack.
Hammoq Makes It Smarter
Here's how Hammoq turns the game around:
- Staff snaps a photo of the item
- AI identifies brand, category, condition, and size
- It connects to 30, 90, or 365+ days of your store's sales history
- It recommends the ideal price, based on what sells
Example:
- Good condition North Face jacket in Store A best at $19.99
- Same jacket in Store B (lower traffic) best at $14.99
- Hammoq prices accurately, based on performance, not policy.
✅ Key Takeaways:
Don't overgeneralize pricing formulas
Flat pricing is easy—but easy ain't profitable. AI brings precision.
Price smarter based on actual real-world resale performance
Run your own POS history to figure out what to charge—per item, per store.
Boost revenue per rack without added overhead
You don't need more bodies—just smarter software.
The Financial Payoff of Smarter Pricing
If you sell 500 units a day:
- If 20% are priced too low by $5 (on potential ASP)
- That's $500/day in missed revenue
- Over 300 days, that's $150,000/year—per store
- Now imagine Hammoq recovering for you even 60% of that.
That's $90K in additional revenue—without hiring more people or raising the sticker price for everyone.
It's not charging more. It's charging right.
Who It's For
This price upgrade is ideal for:
- Thrift store chains
- Liquidation/returns centers
- Consignment shops
- Franchise-based resale models
- Donation-based nonprofits
If your store uses flat pricing to sell faster—Hammoq allows you to sell just as fast, but make more money on each product.
Example: Before and After
Before Hammoq:
- All shoes are $9.99
- Nike sells in 2 days
- Unbranded pairs take 3 weeks
- After Hammoq
- Nike for $19.99 by ASP
- Small brands for $6.99–$8.99
- Both velocity and margin increase
Fewer price markdowns. More consistency. More trust in tags.
What's Next (How To):
- Inspect categories that feel too flat in pricing
- (Denim, outerwear, shoes, handbags)
- Integrate your POS into Hammoq
- Have the system retrieve 30–365 days of actual sales history
Turn on price banding logic by category
For example:
Coats: $9.99 / $14.99 / $19.99 ranges based on brand + condition
Shoes: $6.99 / $12.99 / $24.99+ based on performance
Measure performance on the track within 14 days
Track sell-through, average price by category, and markdown reduction
