Background and initial situation

A medium-sized B2B company that manufactures industrial machinery was faced with challenges in the sales process. Sales staff often needed quick access to product information, price lists and customer data in order to respond to inquiries and create quotations. However, retrieving this information manually often led to delays and impaired the efficiency of the sales team.

Aims of the project

The main objective of the project was to optimize sales processes by enabling sales staff to access relevant information quickly and efficiently. Specific objectives included:

  • Reducing the time spent searching for product and customer data.
  • Increasing the sales team’s responsiveness to customer inquiries.
  • Improving the accuracy and timeliness of sales information.
  • Relieving sales staff of administrative tasks.

Solution implementation

To achieve these goals, the AI was integrated into the company’s existing sales systems. The implementation process followed a clearly structured plan:

a) Needs analysis and planning
  • Identification of the most frequent requests: By analyzing historical data, the most frequent requests for information, such as product details, price lists and customer data, were identified.
  • Defining the integration points: The IT department identified the relevant systems, including the Customer Relationship Management (CRM) system (e.g. Salesforce) and the Enterprise Resource Planning (ERP) system (e.g. SAP).
b) Development and integration
  • Creation of call workflows: Development of specific workflows to answer frequently asked questions, such as retrieving product information and customer data.
  • Technical integration: The AI was seamlessly integrated into the CRM system and the ERP system.
c) Training and knowledge database
  • Data import and structuring: Historical sales data and frequently asked questions were used to expand the AI’s knowledge base.
  • Regular updates: Regular updates to the knowledge base were scheduled to ensure the relevance and accuracy of the information provided.

Application example and process scenario

Scenario: Sales employee needs product information

  • Step 1: A sales representative asks for product details via the internal chat system.
    Sales employee: “AI, can you provide me with the specifications of the new industrial machine model X123?”
  • Step 2: The AI processes the request and retrieves relevant product information from the ERP system.
    AI: “One moment please, I’m retrieving the product details from the ERP system.”
  • Step 3: The AI provides the requested product details.
    AI: “Here are the specifications of the industrial machine model X123:
    – Power: 500 kW
    – Weight: 10,000 kg
    – Dimensions: 5m x 2m x 3m
    – Price: 150.000€
    Would you like more information about this model?”
  • Step 4: The sales representative needs more information.
    Sales employee: “Yes, please send me the current price lists and stock levels.”
  • Step 5: The AI retrieves the current price lists and stock levels and provides the information.
    AI: “Here are the current price lists and stock levels for the X123 model:
    – Price: 150.000€
    – Stock level: 15 units in stock
    Would you like further assistance?”

Results and benefits

After implementing the AI, there were significant improvements in sales support:

  • Reduced response times: The average processing time for sales inquiries decreased by 70%.
  • Increased responsiveness: Sales representatives were able to respond more quickly and accurately to customer inquiries.
  • Improved information accuracy: Sales staff had access to up-to-date and accurate information at all times.
  • Reduced workload for the sales team: Sales staff were able to focus on sales activities as administrative tasks were efficiently automated.

Conclusion

The integration of AI into the company’s sales processes led to a significant increase in efficiency and satisfaction among sales employees. By automating repetitive tasks and providing up-to-date information, valuable time was freed up and the quality of sales work was significantly improved. Future enhancements could include the implementation of additional language support and the use of advanced analytical tools to further optimize sales strategies.