Securing supply is essential for growth in recommerce. But buying more and selling faster do not automatically mean more profits. An integrated pricing approach connects buying prices, selling prices, and inventory to improve portfolio profitability and anticipate changes in product value.
In recommerce, a business can meet its sourcing, sales, and inventory targets while overall profitability declines. A consumer electronics business, for example, may see its sourcing team secure more devices, its sales team increase volumes, and its warehouse team push to clear inventory. The challenge arises when each team makes decisions independently, without considering the combined impact on profitability.
Our view is that buying prices, selling prices, and inventory should be managed as one system. The objective is to achieve the strongest portfolio contribution, accounting for capital tied up and the risk of declining resale values.
1. Secure the right supply, not simply more supply
For many recommerce businesses, access to attractive used products is a major growth constraint. The temptation is to buy almost everything available rather than miss a sourcing opportunity. Yet market-wide scarcity and excess stock of individual models can coexist.
If the same business acquires more smartphones from one generation than it can sell at planned prices, discounting to move that stock may reduce margins and divert demand from neighboring models. Those models may then sell more slowly and require discounts of their own. A sourcing success can become a profitability problem across the range.
Our approach is to build the inventory mix that supports profitable growth rather than simply maximizing intake. The buying-price ceiling starts with expected net resale revenue over a realistic selling period, minus refurbishment, logistics, expected returns, and holding costs, as well as a risk allowance and the target contribution. It should also account for any markdowns needed to sell additional volumes.
That ceiling is not automatically the right offer. The actual buying price should reflect target inventory, storage and refurbishment capacity, and trade-in customer’s response to the offer. Paying more can be justified for scarce, high-demand models, but not necessarily for variants already well stocked.
2. Optimize price relationships, not isolated price points
Suppose an older smartphone sells for €329 and a newer one for €399. Reducing the newer model’s price to €349 narrows the gap from €70 to €20. This lower price may attract new customers, but it may also shift purchases away from the older model, reducing margin on the discounted device while leaving more of the older model in stock.
We assess these choices across model generations, condition grades, and specifications. Own- and cross-price elasticities measure the response to a product's own price and the effect on alternatives. Where individual variants generate limited data, meaningful product groups provide a better basis for analysis than apparent precision at item level.
The aim is not to prevent customers from switching between products. It is more important to select price combinations that improve total contribution after accounting for margin losses, demand shifts, and remaining inventory.
3. Price for the remaining sales window
Inventory levels should inform pricing. For electronics, this means looking beyond how long a product has been in stock. A device in excellent condition may lose appeal when a new model enters the market, support for new operating system versions ends, or when security updates stop. Each of these events can affect demand differently.
We therefore connect stock coverage with forecast demand and the product lifecycle. If inventory represents 12 weeks of sales at the current price, but a significant decline in demand is expected in eight weeks, businesses need to act immediately. This means evaluating alternative prices, adjusting buying offers, and setting inventory targets for the remaining period.
Clear markdown rules define when to intervene, how to assess results, and when exceptions to standard margin targets are justified. An earlier markdown can preserve more value than holding out for a margin that will no longer be achievable.
Model-specific accessories need the same discipline. Phone cases for an outgoing smartphone generation should be assessed against future device sales and standalone demand for those accessories. Targeted offers or relevant bundles can help generate sales while sufficient demand remains. However, their effectiveness should be measured by their contribution to overall profitability, not just the number of cases sold.
4. Define the commercial logic before automating
A forecast estimates what may happen at a given price; it does not decide what the business should optimize. We recommend combining buying and sales forecasts, clear commercial rules, and optimization models that evaluate buying and selling prices together with their effect on inventory.
These decisions need shared data covering transactions, inventory, costs, competitor pricing, and product lifecycle events. Rules should cover buying-price ranges, price gaps, stock targets, and markdowns. Matching a competitor's price only makes sense if it improves expected portfolio profit, not just sales of the affected item.
A pilot with selected product groups and controlled price tests is a practical starting point. Sourcing, pricing, and inventory teams should assess results together using portfolio contribution, stock coverage, inventory age, and capital productivity. Otherwise, a better algorithm risks automating conflicting objectives.
Connect the decisions to capture the value
Recommerce pricing starts before a product is bought and extends beyond the item being sold. The opportunity lies in linking what to buy, how much to pay, and how to price the resulting assortment over time. The best price is the one that works with the rest of the portfolio.
