[case] Online store for US electronics + AI admin panel · USTECH
A store for US electronics with AI assortment analytics — USTECH case study
E-commerce + admin panel · storefront + AI assortment analytics · USTECH
[01] challenge
What the project had to solve
USTECH is a store for genuine US goods: electronics, home appliances, tools, household items. Everything is already in Ukraine — imported, cleared through customs, ready to ship. There are two pains here, on opposite sides of the screen. On the buyer's side: US electronics are cheaper than the market, but the buyer doesn't see it — to them it's just another price where it's unclear whether they're overpaying or not. Without justification, the savings don't land. On the owner's side: goods arrive on pallets — mixed batches from the US. Each pallet is a blind purchase: what will fly off the shelf in a week, and what will sit in the warehouse for months and freeze the cash. Decisions about the next pallet were made on intuition, and slow-moving stock sat there until someone remembered to manually move it into a sale.
[02] solution
What we did — and why
A storefront that sells. A catalog built for value: filters by category, brand, price, condition (new / refurbished), and a separate "savings vs. market" filter; a "by value" sort surfaces what the buyer wins on most; "from the US" and "last one" badges add trust and urgency. A card with AI price comparison: on every item, AI shows the USTECH price next to the market average and maximum, computes the savings percentage, and gives a verdict "best price on the market" — the buyer sees a justification, not a bare number. A fast path to purchase: gallery, specs, condition, warranty, reviews, and checkout without extra steps. AI inside the system — on two levels. For the buyer: AI price comparison turns an abstract "discount" into a concrete "32% cheaper, you save 7,000 UAH" — this removes the main objection on US goods, distrust of the price. For the business — AI assortment analytics in the admin panel that answers three money questions: what to bring on the next pallet (AI forecasts the most profitable categories with a probability of fast sale and expected profit), what to do with slow-moving stock (the system itself surfaces items sitting 70+ days and gives a concrete action — drop the price by 12%, bundle into a promo set, launch ads), and where the margin is (a profitability map by category instead of gut feel). How we built it: a storefront (home, catalog, product card, cart, checkout), an admin panel (products, pallets, orders, and AI analytics in one workspace), AI modules (price comparison for the buyer, assortment analytics and pallet forecasting for the business). Development was led by our developer paired with AI-assisted development.
project frames
[03] result
→ The savings became visible: AI price comparison justifies every price and removes distrust of US goods → Buying pallets stopped being a lottery: AI forecasts what to bring next time → Slow-moving stock doesn't sit dead: the system surfaces it with a ready action for a sale → The real margin is visible: a profitability map by category instead of gut feel
AI price comparison
для покупця
Pallet forecast
AI
Slow-moving stock
авто-дія 70+ днів
Margin
карта по категоріях
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