Case Study: Euronics

Increase sales with intelligent market analysis

Read in this case study how our multichannel customer Euronics successfully uses the market observation solution XPLN to solve the challenge of time-intensive market and price research with a very high degree of automation.


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Extract from the case study:

How is it possible to maintain a comprehensive overview of the prices of the competition, and decide whether a price adjustment is necessary for your own products? Manual and time-consuming market research is out of the question for a retailer with an extensive product range. EURONICS therefore relies on the SaaS platform XPLN, which automatically provides an overview of the market prices of its products and the product ranges of the EURONICS competition.

Prior to the introduction of the new solution, EURONICS members were able to receive price information on competitor products from headquarters once a week. However, this data was neither comprehensive nor current enough for attractive pricing. The basis for optimal pricing of products is reliable data updated on a daily basis – and therefore a higher refresh rate of price information is crucial for modern pricing strategies. This increased refresh rate could only be achieved cost-efficiently with an automation tool.

When selecting a suitable application, EURONICS used the data quality and timeliness of the web crawling as a basis for decision-making. The cloud-based software solution XPLN was able to convince on both these points.

Increased performance thanks to fast and efficient repricing

Using a well-maintained database consisting of individually configurable price rules and the current market situation, XPLN determines an optimal price for each individual product offered. This proposed competitive price can then be transferred either automatically or manually to the company’s own web shop, ERP or other interfaces.

XPLN provides EURONICS with the competitive prices of around 100,000 products, several times a day. Based on configured rules that depend, for example, on the respective brand or product area, a dynamic and competitive price is suggested, which the dealer can then adopt for his products. Based on this crawling, around 30,000 products receive a new price on every day. This price takes into account the market environment and the dealer’s own set of rules.

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