Optimized Pricing
Adjust your prices automatically to the demand of individual customers (groups) or other external factors.
AI in Retail
AI in the Retail Industry
We assist companies in the retail industry in effectively leveraging Data and AI to enhance products and services, optimize processes, and identify new business models.
Trusted by Industry LEaders
Your Experts for Artificial Intelligence in Retail
How AI Optimizes Retail and Commerce
AI is transforming the world of e-commerce, retail, and logistics. Artificial Intelligence (AI) in retail is changing the way companies conduct business, plan processes, and market their products. Through AI in retail, shopping experiences can become increasingly personalized – both online and offline. In e-commerce, AI algorithms can personalize the entire shopping process and provide tailored purchase recommendations, such as recommender systems in e-commerce or for shopping carts in online shopping. AI in retail also improves numerous everyday processes such as workforce planning and logistics. In customer service, intuitive AI chatbots and robotic assistance systems enhance the customer experience. Whether it’s AI in online retail or AI in brick-and-mortar stores – the technology offers numerous opportunities to optimize processes, better understand customers, and ultimately increase sales.
By optimizing retail and logistics through faster and simpler processes, AI in retail allows employees more time to focus on customers, both online and offline. Self-learning systems in AI retail handle repetitive tasks like inventory tracking and data transfers. The possibilities that AI in retail and commerce offer are diverse and promising. However, to tackle complex tasks like predictive analysis and forecasting future events such as sales figures, AI requires large amounts of high-quality data.
Leverage the opportunities of AI in retail, for example with a CustomGPT chatbot or the AI Email Assistant, and consult with our experts at statworx to unlock the full potential of AI in your business.
Valuable Uses Cases of Data Science and AI in Retail
Sales Forecast
Optimize your marketing, ordering and production decisions based on reliable sales forecasts.
Customer Churn
Identify customers who are willing to churn so that appropriate countermeasures can be taken in good time.
Product Recommendations
Identify customers who are willing to churn so that appropriate countermeasures can be taken in good time.
Supply Chain Management
Optimize your order, inventory and production management based on demand and supply forecasts.
Personalized Marketing
Increase the effectiveness of your advertising measures by placing your ads in a personalized way.
Quality Control
Use modern techniques such as computer vision to automatically evaluate the quality of products.
Supplier Management
Use artificial intelligence to review supplier data and identify, evaluate and select new suppliers.
Artificial Intelligence (AI) in Retail
AI in retail significantly expands the optimization possibilities for companies. By analyzing large data sets, retailers can make more precise predictions and create personalized shopping experiences. Another way to optimize retail through AI is by using machine learning algorithms to analyze customer preferences and buying behaviors, delivering tailored product recommendations. This can help reduce customer churn. As a result, AI in retail not only leads to more satisfied customers but also to higher sales figures.
Another application area for AI in retail is inventory management. With AI, inventory levels can be monitored and optimized in real-time to avoid overstock and shortages. This not only saves costs but also ensures that customers always find the desired product.
Artificial intelligence also plays an increasingly important role in brick-and-mortar retail. From automated checkout systems to intelligent shelving systems that continuously monitor inventory and trigger reorders if necessary – the possibilities are nearly limitless.
Learn more about the application possibilities of AI, for example in logistics and from our case study, at statworx.
Ein weiteres Einsatzgebiet von künstlicher Intelligenz im Einzelhandel ist das Bestandsmanagement. Mithilfe von KI im Einzelhandel können Lagerbestände in Echtzeit überwacht und optimiert werden, um Überbestände und Engpässe zu vermeiden. Dies spart nicht nur Kosten, sondern stellt auch sicher, dass Kunden immer das gewünschte Produkt finden.
Auch Künstliche Intelligenz im stationären Handel spielt eine immer größere Rolle. Von der automatisierten Kassenabwicklung bis hin zu intelligenten Regalsystemen, die den Bestand kontinuierlich überwachen und gegebenenfalls Nachbestellungen auslösen – die Möglichkeiten sind nahezu unbegrenzt.
Erfahren Sie mehr über die Anwendungsmöglichkeiten von KI, zum Beispiel von KI in der Logistik und aus unserer Case Study, bei statworx.
Optimization of Retail Disposition
In this exciting project, we developed a model-based correction mechanism to prevent abnormal ordering processes during the Christmas season.
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Sales Forecasting with Deep Learning
In this exciting project, we developed a sales forecasting engine based on deep learning models to predict the expected sales for the next three months.
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Price Elasticities in Retail
In this project, we collaborated with our client to develop a method for estimating store-specific price elasticities and influencing factors.
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Marketing Analysis
To reliably assess the individual impact of marketing channels on our client's core business, we developed statistical models based on historical marketing and order data.
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Next Basket Prediction with Deep Learning
In this project, we developed an innovative recommender system for basket prediction based on deep learning.
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Customer Churn & Retention Prediction
In this project, we developed an automated system for managing customer churn and reactivation.
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Anomaly Detection in Retail Data
To ensure optimal data quality, we developed a model for our retail client that automatically detects and corrects unusual data points in sales data.
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Sales Forecasting in Retail
In this proof of concept, we developed a statistical forecasting model for a client in the retail sector to predict sold units at the merchandise group level.
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Pricing Analytics in Retail
In this project, we supported an international retail corporation in the introduction of pricing analytics, both methodically and operationally, over a period of more than a year.
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Recommender System in E-commerce
To enhance the user experience in the online shop justDrink, we developed a recommender system for Feldschlösschen AG, the largest brewery and beverage retailer in Switzerland, which recommends relevant products to customers based on their shopping cart.
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Price Simulation in Retail
In this project, we developed a price simulation tool for our client that predicts the expected sales volume in the coming weeks based on the price and various other influencing factors.
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An AI Chatbot for everyone: How hagebauGPT boosts Efficiency and Creativity
We developed an internal AI chatbot for hagebau, enabling employees to securely chat with data and efficiently handle time-consuming tasks.
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Our strength
Our ecosystem enables a holistic view of data & AI.
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Tools, Partner & Technology
10+
years of experience in Data Science, ML, and AI
100+
clients from 10 industries and growing
85+
experts from more than 17 fields of study
1,000+
successfully implemented Data and AI projects
AI Retail: Optimizing Customer Service and More
The term AI Retail stands for the application of artificial intelligence in retail and encompasses a variety of technologies and solutions. By using AI Retail, retailers can increase their efficiency, reduce costs, and improve the shopping experience for their customers.
An exciting example of AI Retail is the use of chatbots in customer service. These intelligent assistants for AI in retail can handle inquiries around the clock, take orders, and even provide product recommendations. By automating these processes, companies not only save time and resources but can also achieve higher customer satisfaction. Another example of AI in retail is the analysis of sales data using AI algorithms. These can identify patterns and trends that human analysts might miss, allowing retailers to better respond to market changes and adjust their strategy accordingly.
With a tailored AI strategy that combines AI training, AI consulting, and data science consulting, enormous opportunities emerge for companies to tap into their unexplored potential. Discover more about the benefits of AI Retail at statworx and how we implement AI solutions for businesses.
Our services
AI Consulting
Our consulting services focus on both technical and methodological skills, data literacy, and data culture, utilizing interactive and inspiring learning methods. We provide training for beginners, specialists, and executives.
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AI Starter Offerings
Are you just beginning your data and AI journey? We offer various workshops, training sessions, and ready-to-use AI solutions that are perfect for taking the first steps with data science and AI.
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AI Solutions
We develop data science and AI solutions tailored to your requirements. We support you from the initial idea to the productive solution and ensure smooth operation thereafter.
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AI Trainings
Whether technical or methodological skills, data literacy, or data culture - our formats rely on interactive and inspiring learning methods. We train beginners, specialists, and executives.
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Contact your Experts for Data and AI in Retail
01
Free consultation
Discuss your challenges and goals in the area of Data & AI with us.
02
Tailored offer
Receive a customized and transparent offer.
03
Presentation & contract award
We present our approach to all relevant stakeholders.
04
Onboarding with project team
Our dedicated project team takes care of your needs.
Frequently asked questions and answers
How can AI optimize pricing in retail?
AI enables automatic price adjustments based on individual customer demand behavior or external factors. This leads to dynamic pricing that can increase both sales and customer satisfaction.
What role does AI play in sales forecasting?
AI can provide reliable sales forecasts, allowing companies to optimize their marketing, ordering, and production decisions. By analyzing large datasets, future sales figures can be predicted more accurately.
How does AI enhance the customer experience in e-commerce?
In e-commerce, AI algorithms personalize the entire shopping process. Recommender systems offer tailored purchase recommendations, helping customers find what they are looking for more quickly, thus improving the shopping experience.
What advantages does AI offer in quality control?
Modern techniques like computer vision enable automated assessment of product quality. This leads to more efficient quality controls and can help identify and sort out defective products early on.
