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Ergo is a $19.99/month Shopify app adding a "Name Your Price" button to product pages, giving retailers a simple tool to clear excess inventory by accepting buyer offers.
ENTRY ANGLES
AI-powered dynamic pricing infrastructure that continuously monitors and adjusts prices based on inventory, cash position, and demand signals · Inventory optimization engine that tracks aging inventory, seasonal patterns, and buyer history to automate pricing decisions · Feedback loop mechanism integrating buyer input (Name Your Price) with purchase data to calibrate price sensitivity signals
VERTICALS
CAPABILITIES
AI/machine learning for multi-variable optimization, Real-time inventory and pricing data integration, Demand forecasting and seasonal pattern analysis
Ergo wants to change how online retailers price inventory – and its approach is almost defiantly simple. Any shopper can click a "Name Your Price" button on a participating product page, enter the amount they're willing to pay and a deadline for the offer, and leave their contact details. The store owner reviews incoming offers and accepts or declines each one manually. If accepted, the platform creates a special-price order and sends the buyer a link to confirm and pay.
The product exists as a Shopify app, priced at $19.99 per month. The startup launched this year and is still running an early test version. Despite that – or perhaps because of it – Ergo attracted $1.5M in its first funding round.
The funding raises an obvious question: why back something this straightforward? The answer is that capital tends to follow the size of the problem, not the sophistication of the solution.
The problem Ergo names is real and large: retailers accumulate excess inventory that ties up working capital, requires storage costs, and eventually forces a choice between markdowns and margin erosion. The total value of goods sitting in retail storage at any given moment exceeds $500 billion. Sell-through rates in slower categories tell the story vividly – retailers move only 22.8% of fragrance, 24.3% of apparel, and 25.4% of cosmetics within two months of receiving stock. Even after a full year, roughly half of cosmetics inventory and a third of apparel inventory remains unsold.
Regular sales are the blunt instrument most retailers reach for, but they carry a long-term cost: training buyers to wait for discounts rather than paying full price erodes baseline revenue over time. Ergo positions "Name Your Price" as a quieter alternative – clearing slow movers without signaling to the broader market that a discount event is happening.
Several other startups are working on the same underlying inventory problem from different angles. Ghost ([covered here](/review/tvoi-dengi-lezhat-u-nih-na-sklade)) built a wholesale liquidation marketplace where retailers can move excess stock to off-price channels or international distributors; it has raised $68M. Max Retail works on a similar model with $5.8M raised. Yaysay, [reviewed recently](/review/500-milliardov-dollarov-za-30-minut), routes surplus inventory direct to consumers through an AI-curated daily feed with a 30-minute purchase window – $10.3M raised. Nibble, [covered previously](/review/nazovite-svoju-cenu), uses an AI negotiation bot: the buyer proposes a price, the bot pushes back with counterarguments and a counteroffer, and the conversation continues until it lands inside the seller's acceptable range. Nibble has raised $3.6M.
Ergo's version strips all of that down to a single input field. No negotiation bot, no feed algorithm – just an offer and a decision. That simplicity is a genuine differentiator for buyers who find back-and-forth negotiation with an AI more friction than it's worth.
A secondary value is analytical: the stream of offers a retailer receives is a direct signal of where buyers' price ceilings actually sit, separate from whatever inference can be drawn from click-through or cart abandonment data. That signal can inform repricing decisions independent of the "Name Your Price" mechanic itself.
The manual review step in Ergo's current design is the bottleneck that limits how useful the product can become at scale. A merchant receiving dozens of offers across hundreds of SKUs can't efficiently evaluate each one against current inventory costs, cash flow timing, customer history, and demand forecasts in real time. That's the kind of multi-variable optimization AI handles better than humans.
The more durable play in this space is dynamic pricing infrastructure that operates continuously rather than on demand. The core of such a platform would be an AI engine monitoring inventory aging, cash position, seasonal patterns, and buyer history – adjusting displayed prices automatically in response to shifting conditions. The "Name Your Price" mechanism fits naturally as a feedback module within that system: periodic buyer input that helps calibrate price sensitivity signals in ways that purchase/no-purchase data alone cannot.
The real entry point is the $500B inventory problem, not the price-negotiation mechanic. The mechanic is one module; the opportunity is building the pricing intelligence layer that online retailers currently lack entirely.