Retail

The customer is always right – know your customer

Retail is - like hardly any other industry - in a time of digital disruption. Products are omnipresent, substitutable, available at all times and price pressure on retailers and producers is greater than ever. For the new digital customer, merchants are virtual, almost impossible to differentiate and are easily replaced if the selection, speed of service or price/performance ratio do not meet expectations. In order to stand out from the mass of offers and dealers in the future, retailers must synchronize analog and digital channels in order to be able to offer each consumer an individual and coherent shopping experience across all channels. However, providing this type of shopping experience requires a high degree of flexibility throughout the supply chain. Mail-order or online inventory is often managed in a different warehouse system than store-based inventory, so products may not be available where the customer wants to buy them. However, to ensure a seamless Omnichannel experience for customers, it is essential to align demand, planning and inventory across channels. This is where data analysis comes in and helps retailers improve the Omnichannel experience through the targeted use of data.

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David Schmaderer

Data Analytics in Retail

Data Analytics can be implemented with great business potential for retailers - regardless of their size or sales channel. Data Analytics fills the gap between the different sales channels, creates a 360-degree view of the customer and helps you to offer each customer an individual shopping experience. Thanks to data-driven analyses, personalized offers can be made to the customer, behavior forecasts can be derived and the use of resources can be intelligently controlled. Most retail companies already have the right data sets for this: sales, pricing and scheduling data are the cornerstones for forward-looking analysis. The WDL can show you how Data Analytics can be used for your business management as well as to increase customer satisfaction, sales success and long-term customer loyalty.

A data analytics project with the WDL usually involves three agile steps:

1. Proof of Concept (PoC) - 4 weeks
We identify a suitable use case together with our customers, which is then validated on the basis of the customer's data within a few weeks. The added value becomes visible and serves as the basis for the decision for ongoing use.

2. Implementation - 4 weeks
We create an individual and user-oriented dashboard with which the Use Case can be permanently established within the company.

3. Automation - Ongoing
When transferring to automated regular operation, all relevant core systems are connected to the system and the results of your analyses are available to you at all times.

Use the power of data analysis for your business today!

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