Data & AI projects in retail
A BMWI study identified 27 areas of application for artificial intelligence in retail alone. In the customer experience, for example, AI can be used in the context of virtual try-on, visual product search, but also in the intelligent reminder process. The Internet of Things (IoT), RFID sensors, digital price tags and mobile internet create entirely new opportunities for stationary retail to personalise and individualise the customer journey.
In addition AI in logistics optimise supply chain operations, route planning and deliveries.
AI applications are not limited to retailers. Wholesalers, B2B retailers and, above all, online retailers and online shops also benefit from artificial intelligence.
We have used our experience from over 1,000 projects in the last 8 years to develop a holistic system for data & AI projects - our Data Journey. A consistent data strategy forms the basis and the framework for generating real added value from data.
Projects of our customers
The experts at Alexander Thamm have already successfully implemented over 1,000 data & AI projects. These include numerous projects in retail, wholesale, B2B trade and online trade.
Food sales forecasts
- Transparent white-box approach for the customer
- Creation of independence of external providers through in-house solution
- High cost savings
Recommendation system for cross-selling
- 75 % of the recommendations are rated as helpful by the sales experts
- One algorithm for recommendations at multiple customer touchpoints
- Enabling the further development of the recommendation system through know-how transfer
Optimisation of supply chain management
- Significant reduction of the whip effect, which increases as the level in the supply chain rises.
- Reduction of out-of-stock situations despite simultaneous reduction of stocks
- Central calculation of order proposals enables transition to vendor-managed inventory
Demand forecast for warehouse optimisation
- Increase forecast accuracy at all sales locations and for the most important product groups
- Increase in parts availability (service level) and targeted control of stock turnover
- Reduction of lost sales by 50 %
Efficient assortment adjustment
- The complex process of assortment cleansing can be carried out within a few minutes
- Expertise and data-based evaluations complement each other in the best possible way
- The user can easily and clearly try out different scenarios and select the best solution
Optimisation of the production volume
- The total quantity for pre-production of articles could be increased by 43 % without resulting in a higher residual risk than before
- The prototype combines the quality of heterogeneous demand signals from different markets
- The Level Loading prototype is embedded in a well-documented R package
Artificial Intelligence in Retail & E-Commerce
Application areas of AI & Big Data
Retail and e-commerce companies have large amounts of data that offer huge potential. In the following, we present some fields in which artificial intelligence can be used in e-commerce and retail in general:
Detect and successfully combat fraud attempts in real time.
Enable customers to have transparency and predictability over their own finances through analytics and data-driven banking.
Realisation of cross-selling and up-selling potentials and optimisation of the conversion rate in e-commerce through data-based recommendation systems.
Determine the optimal price and increase trading margins through dynamic price optimisation.
Relieve and optimise customer service and back office by using virtual assistants and digital robots in customer communication.
Identify customers at risk of churn and retain them through targeted approaches and offers.
OPPORTUNITIES OF ARTIFICIAL INTELLIGENCE IN RETAILING
Enormous increases in efficiency and revenue can be realised in all areas through the use of artificial intelligence. Digital assistants can help to reduce costs and save resources. Customer loyalty can be strengthened through personalised offers and additional functions based on the evaluation of customer data and customer segmentation. Entirely new target groups can be tapped by developing new, data-driven products.
New Business Models
Improve customer experience
Get advice without obligation
Data & AI Projects Insurance & Finance