Defining Artificial Intelligence
The term Artificial Intelligence (AI) is used to refer to two things. First and foremost, AI is a scientific discipline that investigates the potential for intelligence of machines. Humans have dreamed of creating Artificial Intelligence for centuries, but the targeted, academic research to actually do so has only existed since 1956. Second, Artificial Intelligence refers to machines or computer systems that exhibit intelligent behavior. Intelligent machines and systems are already used in a variety of different areas. In recent years, the vast majority of such intelligent machines and systems have been created through Machine Learning methods, so that nowadays one might say that in essence AI = ML + x.
OPPORTUNITIES OF ARTIFICIAL INTELLIGENCE
In retail and E-COMMERCE
Increase profit margins and identify new revenue drivers by employing AI solutions.
Save resources by automating processes along the entire value chain.
Optimize the customer experience
Create sustainable customer experiences and retain customers through Data-driven solutions.
Potential of AI in retail and E-Commerce
A study by the BMWI identifies 27 areas of application for Artificial Intelligence in the retail sector alone. In terms of customer experience, AI can not only be used in virtual fittings or visual product searches(to give just two possible examples), but also in intelligent dunning procedures. The Internet of Things (IoT), RFID sensors, digital price tags and mobile Internet access come together to create completely new possibilities to customize and individualize the customer journey in stationary retail.
In local franchise stores, robots can be used in consultation or for cleaning. While the head offices can benefit from AI algorithms for dynamic price optimization, personnel deployment planning and even in selecting and designing product ranges. As for logistics and transport, AI can aid in optimizing supply chain operations, route planning and deliveries.
Moreover, the potential for using AI to your advantage is not limited to retailers. Wholesalers, B2B traders and especially online retailers and stores also benefit from Artificial Intelligence.
The use of Artificial Intelligence can lead to enormous increases in efficiency and yield across all areas. Digital assistants can help reduce costs and save resources. Brand loyalty can be strengthened through personalized offers and additional functions based on customer segmentation and the evaluation of customer Data. Entirely new demographics can be opened up by developing new, Data-driven products.
Areas of application of AI in Retail & E-Commerce
Retail and e-commerce companies have access to large amounts of Data that offer huge potential. In the following, we will introduce you to some of the fields in which Artificial Intelligence can be put to good use in e-commerce as well as commerce in general:
Successfully detect and prevent instances of attempted fraud in online shopping and stationary trade in real time.
Precise sales forecasts let you automatically determine optimal order quantities and maximize margins.
Realization of cross- and up-selling potential as well as conversion rate optimization in e-commerce thanks to Data-based recommendation systems.
Increase trade margins by determining the optimal price using dynamic price optimization.
Free up and optimize customer service and back offices by deploying virtual assistants and digital robots in customer communication.
Identify customers at risk of churn ahead of time and retain them with personalized offers and services.
Reference projects of our customers
The Data & AI experts at Alexander Thamm have already successfully implemented more than 1.000 projects, including numerous projects in retail, wholesale, B2B trade and online commerce.
Sales forecasts for food
- Transparent white-box approach for the client
- Independence of external providers ensured via an in-house solution
- High cost savings
Recommendation system for cross-selling
- 75 % of all recommendations are rated as helpful by sales experts
- A single algorithm for recommendations at multiple customer touchpoints
- Ability to further develop the recommendation system through know-how transfer
Optimization of Supply chain management
- Significant, progressively increasing whip effect reduction along every level in the supply chain
- Reduction of out-of-stock situations despite simultaneous reduction of inventory
- Central calculation of order proposals facilitates the transition to vendor-managed inventories
Demand forecasting for inventory optimization
- Increased forecast accuracy at all sales locations and for the most important product groups
- Increased availability of parts (service level) and targeted control of inventory turnover
- Lost sales reduced by 50 %
Efficient product range streamlining
- The complex process of assortment streamlining can be carried out in just a few minutes
- Expertise and Data-based analyses complement each other in the best possible way
- The user can easily and clearly test different scenarios and select the optimal solution
Optimization of the production quantity
- The total quantity for the pre-production of goods could be increased by 43 % while maintaining the same level of residual risk
- The prototype unifies the quality of heterogeneous demand signals from different markets
- The level loading prototype is embedded in a well documented R-Package
Opportunities for using AI in retail & e-commerce
New Business Models
Unlock new demographics using digital products and channels of distribution.
Significantly reduce expenditure of resources through process automation.
Customer Experience verbessern
Identify and react to customer needs with the help of Data-driven solutions.
DATA & AI PROJECTS FOR RETAIL WITH [at]
Their main goal is to test Use Cases as quickly as possible – from the concept phase to the prototype using real Data. In the Data Factory, Use Cases are industrialized into finished products. The absolute main focus is on scaling and the sustainable generation of added value – as such, the user is just as much the focus here as well. In our DataOps we continuously operate and maintain your platforms and machine learning algorithms.
AI PROJECTS WITH THE [at] DATA JOURNEY
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 comprehensive Data Strategy forms the basis and the framework for generating added value from Data–what we refer to as Data2Value. Our Data Lab is all about speed! Their main goal is to test Use Cases as quickly as possible – from the concept phase to the prototype using real Data. In the Data Factory, Use Cases are industrialized into finished products. The absolute main focus is on scaling and the sustainable generation of added value – as such, the user is just as much the focus here as well. In our DataOps we continuously operate and maintain your platforms and machine learning algorithms.
3 REASONS FOR CHOOSING YOUR DATA & AI EXPERTS FROM [at]
Leader in AI and Big Data
Whitebox instead of Blackbox
Our individual models and algorithms ensure transparency and, in contrast to finished product solutions, can be further developed independently at any time.
AI expertise in retail and e-commerce
Since 2012 we have successfully implemented numerous projects in retail, B2B trade and e-commerce for various clients.