Optimized Pricing
Adjust your prices automatically to the demand of individual customers (groups) or other external factors.
AI in Retail
AI in Retail
We help retailers harness artificial intelligence to enhance customer experiences, automate processes and develop new data-driven business models – across retail stores, e-commerce and integrated omnichannel strategies.
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AI in Retail
Unlock the value of AI in retail
Retail is evolving faster than ever. Rising customer expectations, intensifying competition and increasingly complex supply chains require real-time, data-driven decision-making. Artificial intelligence enables retailers to streamline processes, personalize shopping experiences and unlock new revenue opportunities.
As a leading Data & AI consultancy, statworx helps your organization successfully deploy AI in retail to enhance products and services, improve operational efficiency and build sustainable competitive advantage. Whether you are looking to apply AI in stationary retail or e-commerce, our experts support you from strategy through to production implementation.
Practical applications of 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.
Why Artificial Intelligence is becoming essential in retail
Retail is undergoing fundamental change. Customers expect personalized shopping experiences, fast delivery, tailored product recommendations and consistent service across channels. At the same time, staffing, logistics and inventory costs are rising, while competition from digital-first players continues to intensify.
AI gives retailers a data-driven way to address these challenges. Rather than relying solely on experience and intuition, modern AI systems analyze large volumes of data in real time, helping organizations automate processes, forecast demand more accurately and better understand customer needs.
AI is no longer limited to isolated automation initiatives. It is increasingly becoming a strategic capability for modern retailers, creating value across the entire value chain – from procurement and logistics to marketing, sales and customer service.
Increasing Revenue and Enhancing Customer Experience with Computer Vision
We developed a computer vision suite powered by deep learning models that automatically enhances product descriptions and generates targeted product recommendations.
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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
15+
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
Challenges when implementing AI in retail
Many retailers already have access to large volumes of valuable data but are not yet able to realize its full potential. Disparate IT systems, fragmented data sources and insufficient data quality can make successful AI adoption difficult. Retailers must also address demanding requirements around data protection, scalability and the integration of new AI applications into existing processes.
Typical challenges we encounter in retail projects include:
- Fragmented data landscapes and data silos
- Insufficient data quality and inconsistent data structures
- Complex system landscapes across stationary retail and e-commerce
- Limited scalability of existing solutions
- Data protection, compliance and governance requirements
- Lack of an AI strategy and clear prioritization of suitable use cases
As an experienced Data & AI consultancy, we help you address these challenges systematically – from strategic planning and building the right technical infrastructure to successfully deploying production-ready AI applications.
A well-thought-out AI strategy enables companies to clearly define their specific goals, identify areas of application and manage the use of AI technologies in a targeted manner. This ensures that all AI initiatives are coordinated with overarching corporate goals and that a solid infrastructure, reliable data base and the necessary expertise are available. Strategic planning minimizes risks, increases acceptance and lays the foundation for sustainable success with AI.
Our advice on AI strategy forms the basis for the data-driven and AI-based transformation of your company. Together, we will work out how you can strategically implement the transformation and select the most promising deployment options for your company.
Artificial Intelligence in e-commerce and stationary retail
The way AI is applied in retail varies by sales channel. E-commerce primarily draws on digital customer data, while stationary retail often focuses on store operations, product availability and operational processes. Retailers with an omnichannel strategy benefit particularly from intelligently connecting both worlds.
AI in retail: 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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Artificial Intelligence in e-commerce
Artificial intelligence in e-commerce helps you optimize the entire customer journey with data – from product discovery and personalized recommendations through to checkout. Using historical purchase data, user behavior and additional real-time signals, AI can personalize recommendations, improve search and automate campaign management. AI models can also increase conversion rates, optimize basket value and forecast demand more accurately.
Typical applications include:
- Intelligent recommendation engines
- Personalized product recommendations
- Customer journey optimization
- Intelligent product search and conversion rate optimization
- Dynamic pricing
- Demand forecasting and basket analysis
Talk to our AI in retail experts
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.
AI in retail: FAQ
What are typical use cases for AI in retail?
Artificial intelligence is used in retail for applications such as personalized product recommendations, demand forecasting, dynamic pricing, customer analytics, intelligent product search, and inventory and supply chain optimization. The AI applications that deliver the greatest value depend on your business model, available data and strategic objectives – we are happy to help you identify the right priorities.
How can AI be used in e-commerce?
Artificial intelligence in e-commerce helps businesses optimize the entire customer journey. Typical applications include personalized product recommendations, intelligent search, dynamic pricing, automated marketing and accurate demand forecasting. The goal is to improve the shopping experience, increase conversion rates and strengthen long-term customer loyalty.
What are the benefits of artificial intelligence in stationary retail?
In stationary retail, AI can optimize product availability and inventory levels, improve workforce planning and provide deeper insights into customer flows. Technologies such as computer vision and intelligent store analytics also enable automated processes and data-driven decisions that can reduce costs while improving service quality.
What are the prerequisites for using AI in retail?
Successful AI adoption requires a reliable data foundation, clearly defined use cases and suitable technical infrastructure. A well-designed AI strategy and effective integration into existing processes are equally important. We help you establish the necessary foundations and successfully implement the right AI applications.
Which retailers can benefit from AI?
AI in retail can create value for organizations of any size – from mid-sized retailers to international retail groups. Companies with large data volumes, complex supply chains, omnichannel strategies or intense competitive pressure across physical and digital channels often stand to benefit in particular.
How does statworx support AI projects in retail?
We support retailers across the entire AI lifecycle – from identifying high-value use cases and developing a tailored AI strategy to technical implementation and production operations. Our teams combine deep expertise in Data Science, Machine Learning and Data Engineering with extensive experience from successful AI projects in the retail sector.
