Retail

What are the challenges?

The retail sector is on the eve of significant value creation with data science. To remain relevant, they will have to understand the consumer better and provide an omnichannel service. Physical stores struggle with interaction with customers. The timely and correct supply of physical outlets and direct delivery from a web shop also leads to logistical issues. These challenges lead to two important perspectives: optimization with the aid of data science and operations research, namely the supply chain of the company (the ‘back-end’) and the operation on the shop floor or online environment (the ‘front-end’).

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What do we have to offer?

Retailers collect a large amount of data from all sources on both sides (barcode scanners, POS systems, POS, etc.). They can create a lot of additional value by combining this data with external data sources, in combination with the right AI techniques. Think of image and face recognition, Natural Language Understanding or prediction modelling.
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Price optimization

Good price optimization can lead to double digit sales growth if properly organized. Which combination of products do consumers choose, which elasticities apply, which products can you increase in price without losing volume? Combination of internal and external data (competition, weather forecasts, etc.) and the right models an lead to a significant increase in turnover.


Sales forecasting & optimization of the supply chain

The basis of retailers is a good sales forecast at a sufficiently granular level. Combination of internal and external data, with the good machine learning algorithms, will lead to an adequate supply of stores or a webshop. Deployment of the right employees is the basis for many decisions.


Recruitment: workforce matching of demand & supply based on AI

Retailers with many employees face the challenge of finding enough trained staff every year. These employees then need to be trained and to achieve optimum performance. A lot of money can be saved in the recruitment process, by using AI in analyzing resumes and backgrounds, employee profiling, etc. In the area of employee training, AI can also be used very meaningfully.


Order batching and order release

A large part of the operation costs for most of the warehouses comes from the picking process. Most of the warehouse management systems (WMS) on the market do include a standard order batching strategy. Nevertheless, Pipple has achieved large savings on picking distances by developing and implementing customized solutions that fit perfectly to the operation.


Identify and control process dynamics by simulation

Optimization, algorithms and optimized decision making contribute the most to the overall performance when applied to the bottleneck of a process. But it is not always clear what part this is, and it might even change over time. By combining optimization models with simulation techniques, we can finetune the decision making of our algorithms even before they are implemented.


Other solutions we offer within retail:

  • inventory management and optimization
  • automatic productdetail enrichment
  • anomaly & fraud
  • customer experience optimization
  • customer profiling
  • recommendation engines

Client Stories in Retail

New Retail Client Stories will be published soon..

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Are you next?

Speak to our Retail specialist at +31 (0)40 3033 252