Returns management as a service
Our returns management as a service includes an interlocking, self-developed system of tools and AI implementation. The classification app, the buyer portal, the customer analysis, the recommendation system, the palletizing app and the price optimization are part of the returns processing.
Returns Management Goals
- Preventive measures to avoid returns
- increase customer satisfaction
- Offer returns of articles and pallets online
- Efficient handling of return and exchange processes
- Optimization of goods receipt and processing through returns management
Step by step for goods classification
With the help of the specially developed classification app, the goods are classified step by step through easy operation. The relevant information with decision questions and scales is determined by a questionnaire, because this enables an effective and efficient classification of goods.
When the goods are classified by the returns management, the items are given an identification number and they are evaluated in a points system. The point system works on a scale from 0-100, where 0 is the worst quality (C-goods for spare parts) and 100 is the best (A-goods in the packaging).
Automated upload of product information
The collected product information is collected by the classification app in the buyer portal and automatically uploaded. Returns management automatically creates detailed product views with photos, scores and descriptions.
The selected returned item and the associated product information always correspond 100 percent to the specified data, which creates trust and long-term customer loyalty.
The buyer portal optimizes the sales process for returned goods through various implementations. This includes projected sales valuations for fast and slow movers.
In addition, a customer analysis is carried out, a recommendation system is used, a palletizing app is used and price optimization is carried out to improve returns management. These measures help to make sales more efficient and targeted.
Adapt prices and stock to demand
The collected sales data is used to determine which goods, items, packages and pallets are selling faster and slower. Based on this analysis, prices and offers can be adjusted to adjust prices and stock to demand.
A continuous supply chain is maintained.
The determined factor determines where the goods are stored. For example, slow-moving items are stored on the shelf based on the determined value, because it contributes to efficient use of storage space.
Automated customer-specific quotation generation
In the buyer portal, the buying habits of the customers are analyzed in order to offer them the appropriate goods and to carry out an automated customer-specific offer generation. The analysis is based on buying habits such as quantity, quality, type of goods, but also on country-specific preferred returned goods.
Automated customer-specific quotations are created. The result is an automated offer that is based on the customer’s needs because a package is put together that is optimally matched to the desired size of the truck.
Transport optimization and cost reduction
With the help of the palletizing app, our specially developed transport optimization and cost reduction in returns management are implemented by carrying out several steps in parallel by scanning the unique identification number.
First, the pallet size and position is defined for the goods and then the pallet is loaded accordingly in order to optimally fill the truck in the further process. The goal of transport optimization in returns management is to transport as many goods as possible on pallets.
In order to use an ideal combination of pallets, a selection of different pallet sizes is used, which ultimately optimizes the transport costs for the customer.
Point system for more precise price determination
In most cases, the returns industry works with categories A, B & C, which is also the basis for the price. These categories are quite rough, which sometimes overestimates or underestimates the value of the goods. For this reason, we have created a point system for our returns management to determine prices more precisely.
The point system goes up to 100, which allows a more accurate assessment of the condition and a more precise price determination. The data for price optimization is drawn from the classification app, which allows us to offer our customers more precise price for the returned goods.
Reactive returns management involves handling customer returns after they have been received. No proactive measures are taken beforehand to reduce returns.
Preventive returns management refers to proactive measures taken to reduce returns. This involves identifying and eliminating the reason for returns at an early stage.
When selling returns in online mail order, one should provide clear product descriptions and condition ratings. This will help to achieve a positive recommendation and a good buying experience.