Use cases
How AI is penetrating sales
Artificial intelligence (AI) makes it possible to automate sales processes, accurately predict trends and create personalized customer experiences. Opportunities arising from the use of AI in sales include, for example
- Dynamic pricing and sales forecasts
- Customer loyalty and churn management
- Optimization of sales processes
- Customer classification and segmentation
- Purchasing behavior and sales forecasts
The AI use cases in sales at a glance
Problem: Prices are often set statically and without sufficient and regular consideration of market dynamics.
Solution: AI analyses market data, customer behaviour and competition to suggest optimal, dynamic prices in real time.
Benefits: Higher margins, improved competitiveness and personalized offers.
Problem: Sales forecasts are still often based on traditional methods.
Solution: AI uses historical and current data to create more precise and flexible sales forecasts.
Benefits: Better planning reliability, targeted use of resources and well-founded strategic decisions.
Problem: Potential customer churn is often recognized too late. This results in lost sales or high costs for customer recovery.
Solution: AI identifies customers at risk at an early stage and makes recommendations for measures to improve customer loyalty.
Advantages: Lower churn rate, stronger customer loyalty and stable sales.
Next Best Offer
Problem: Sales teams often do not have the capacity to develop tailored offers for all customers.
Solution: AI analyses customer data, purchasing behaviour and preferences to make personalized product or service suggestions.
Benefits: Higher closing rates, increased sales and improved customer satisfaction.
Problem: Selecting suitable products for customers is time-consuming and often not targeted.
Solution: AI takes into account seasonal trends, regional factors and customer data to recommend optimal investment goods.
Benefits: More efficient customer approach, targeted offers and higher sales.
Problem: Traditional approaches to segmentation, such as gold, silver and bronze categories, are often too coarse.
Solution: AI analyses customer data and creates finer segments based on many parameters, e.g. sales potential or purchasing behaviour.
Benefits: More precise targeting, more efficient sales strategies and better customer loyalty.
Problem: Sales teams often spend a lot of time on less lucrative sales opportunities.
Solution: AI evaluates sales opportunities based on historical and current information and prioritizes the most promising leads.
Benefits: Greater sales efficiency, increased close rates and maximized revenue.
Problem: You need a lot of experience to predict your customers’ behavior. For new sales employees, this means a steep learning curve.
Solution: AI analyzes historical and current offers, sales, competitive situations, the connection with regional and seasonal conditions and much more in order to predict your customers’ future purchasing decisions.
Advantages: Better planning, more efficient sales campaigns and increased sales.
Stay future-proof
Tailor-made offers at the right time, quick responses and forward-looking support
According to a study (ECC KÖLN, Hello Word – Künstliche Intelligenz in Marketing & Vertrieb, Cologne, 2023), around 80% of respondents from the marketing and sales sector expect a clear competitive advantage for their own field of work. The majority of all study participants (56%) have already introduced AI solutions.
Further use cases
Discover exciting use cases from different areas of the company and be inspired by how other teams find and implement innovative solutions. This exchange opens up new perspectives and creates valuable synergies for joint growth.
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