E-commerce

In e-commerce, demand changes more dynamically than in retail — this is influenced by changes in prices and delivery costs, product positioning in the results list, campaigns and activities of creators, customer feedback and marketplace algorithms. On the other hand, there are supply slips and temporary shortages in warehouses. For the sales team, such a set of factors creates a chaotic signal that is difficult to interpret and translate into a decision on the next move.

At the same time, this whole world is digital: data on traffic, click-through rate, conversions, shopping carts, search engine positions and campaign calendars are available almost at your fingertips. They just need to be interpreted well.

That's what Nadia does. Dedicated e-commerce models (developed by ML specialists with the title Kaggle Grandmaster) learn the influence of individual factors on sales for each product and channel.

The forecasts are probabilistic, which means that instead of a single number, Nadia gives a distribution of possible demand. Based on this, the system calculates decisions that minimize the total cost: risk of lost sales, cost of excess inventory, transportation and commissions of marketplaces, selecting the level of inventory, allocation and pace of orders.

When part of the information is missing or uncertainty grows, Nadii automatically increases caution for strategic positions and allows greater hesitation for substitute products. At the end of the season, he limits purchases, proposes smart sales and sets so as not to enter sales. Everything happens at a frequency that fits your business—every day, several times a day, or less frequently, so you can respond quickly to micro sizes without overloading operations.

What you gain:

• higher availability of goods with a lower total stock — also on days of big fluctuations,
• and thus less need to introduce discounts at the end of the season thanks to earlier, precise decisions,
  
• fast, automatic response to changes in prices, demand and supply in each channel,
• one consistent approach from forecasting to procurement and allocation — with the rationale for the decision directly in the Nadia app.

In e-commerce, the so-called “long tail” are hundreds of variants that are rarely sold (e.g. niche sizes and colors), but which customers are looking for and which they can bring to your store a customer who otherwise would not have come to it. Platforms and your e-shop expect too exposure minimums/availability — at least one piece is needed so that the offer is visible and so that the product card does not frighten with empty variants.

Too wide catalog freezes cash, too narrow cuts sales and reduces visibility in the search engine of a store or marketplace. In Nadia we forecast demand for each product, channel and variant (SKU — Assortment item). On this basis, we designate real exposure minimums: enough to maintain visibility and liquidity of sales, but without creating surpluses. Nadii points out, which positions to hold constantly, which only seasonally, and which to transfer to order or extinguish. We propose specific quantities and schedules of replenishment, we make sure that the “minima” do not inflate the stock: we allow to combine free pieces in sets, we transfer stock between channels or locations and we prioritize “must have” variants, limiting investment in those that do not work for the result.

What you gain:

• less capital frozen in stock and less sell-off,
• the correct width of the offer in each channel,
• faster rotation of rare variants (long tail),
• better margin through smart selection and controlled minimums.

Purchases with a long lead time, like products imported from Asia, are a chain of decisions stretched over weeks: production, negotiations with price thresholds and minimum order sizes, reservations for a seat on a ship or train, clearance and campaign deadlines on the sales side. Private label orders also have a specific ordering process.

Every mistake means losses — empty space in the container, express deliveries, launch slippage. Nadii runs the process “from forecast to freight” and updates it daily: every sales hour recalculates the needs, and the system Refreshes recommendations immediately after any change in prices, minimum volumes or delivery dates. The procurement proposals are securely suspended for the duration of the negotiations and each time we show a transparent “before/after” for approval. In parallel, we plan to replenish the goods under Actual forecasted term and risks (cruise calendar, holidays, queues in ports, check-in), as well as we consolidate loads: we combine positions and suppliers to fill a container or optimally build a pallet shipment. We synchronize everything with the sales plan and the possibilities of the warehouse, so that the goods arrive on time, without operational peaks - at lowest total costand not just the lowest purchase price.

What you gain:

• lower transport costs per unit and fewer emergency deliveries,
• reduced risk of shortages in transit and more reliable delivery dates,
  
• faster and simpler order approvals (clear variants and cost justifications),
• schedules consistent with the season and promotions, without overloading operations.

In marketplaces (eg Allegro, Amazon) visibility and sales depend on two things: The product must be available, and the shipment must come out on time. When shortages or delays occur, your store lowers its position in the ranking, and thus the funds invested in its promotion are wasted. Nadii prevents this: forecasts demand and delivery times in each channel, reserves stock for key offers, combines advertising campaigns with real availability, and when the risk of shortage increases — suggests a breakl ub reduction in advertising budget, accelerates the replenishment and chooses the best way to fulfill the order (own warehouse, external logistics operator or fulfillment by Amazon — Fulfilled by Amazon). As a result, the listing maintains visibility (including the Buy Box — the default purchase offer), and shipments fall within the required times without operational “peaks”.

What you gain:

• stable ranking/Buy Box,
• less cancellations and penalties,
• better return on advertising spending,
• foreseeable delivery times.

In e-commerce, sales, marketing performance, marketplace service, shopping, and logistics often play on different KPIs: return on ad spend vs SKU availability, ranking/default offer (Buy Box) vs lead times, commission margin vs delivery cost.

The effect? Lack of consistency of effects: the campaign draws traffic to a product that is missing; the listing loses visibility due to delays; the warehouse is overloaded because the start of the promotion overlaps with deliveries. The Nadii app is a common, multi-user dashboard in the organization with the genesis of the result “from click to package”: it shows whether the drop in sales is a forecast error, poorly set exposure minima, supplier latency, limited packing/courier throughput, marketplace rules (SLA penalties), bookings for channels. Each recommendation allocation or relocation of stock, order, adjustment of the campaign budget, change in the pace of promotion, determination of priority of execution and recommendation to choose the path (own warehouse, external operator, implementation through the platform) — has a cost justification: lost margin, cost of excess, cost of transport, cost of advertising, impact on ranking/Buy Box and cash.

All decisions are justified and documented: it is known who and why changed the decision. Data and decisions can automatically flow into BI/Data Lake tools and advertising and marketplace systems; roles and permissions allow management to see the macro picture and operations to see specific actions and alarms only where intervention makes sense.

What you gain:

• One data source: from marketing to fulfillment — no more parallel “versions” of metrics.
• Accessibility Correlated Campaigns: You don't pay for traffic to unavailable products.
  
• Faster, consistent allocation, pricing and shipping decisions across all channels.
• Predictable impact on P&L: margin after commissions, advertising and logistics costs in one model.
  
• Better ranking and fewer penalties thanks to SLA control and quality of execution.
• Compliance and control: full change tracking and automatic reports defined at the beginning of the collaboration — with views for each management level (C-level, managers, operations)