Creating a prototypeAI-Powered 
Sales Assistant

Project Description: AI-Powered Sales Assistant

Development of an AI-powered sales assistant that analyzes sales data and provides targeted recommendations for sales representatives. The focus is on utilizing advanced AI and data analysis methods to identify patterns in sales data. A PIM system (Pimcore) will be used as a supporting data hub to facilitate structured access to the analyzed data, provided via a REST API.

Background and Motivation

The client sells advertising spaces in supermarkets and stores historical sales data in their in-house SAP system. To efficiently analyze this data and convert it into actionable recommendations, an AI solution is being developed that uses machine learning algorithms to detect patterns and success factors (e.g., industries, weekdays, times).

The PIM system serves as a central repository for the processed data, ensuring that information is structured and standardized, and made available via an API. This allows the sales assistant to optimally access the necessary information and process it in real time.

Core Features of the Prototype

  • Advanced Data Analysis: Application of AI algorithms on historical sales data to identify patterns and correlations crucial for successful sales.
  • Predictive Model and Recommendations: Development of an AI module that generates actionable recommendations based on the analyzed data to support sales representatives.
  • Data Structuring via PIM System: Use of the PIM system (Pimcore) to store analyzed and structured data, providing a consistent data base via a REST API.
  • User-Friendly Frontend: Development of an intuitive interface that visualizes the results and recommendations from the AI, making them easily accessible for sales teams.

Technical Requirements

  • Data Analysis and Machine Learning: Development and training of machine learning models (e.g., neural networks, decision trees) to identify patterns in sales data.
  • Integration of the PIM System: Configuration of a PIM system as a data platform, allowing access to analyzed data via a REST API. This ensures that the AI models can access a clean, structured data base.
  • Backend and API Development: Development of an API to facilitate communication between the PIM system, the AI application, and the user interface.
  • Frontend Development: Creation of a user-friendly and intuitive interface for sales representatives to present recommendations and visualizations from the AI.

Required Resources

  • Data Scientists and AI Specialists: Professionals to develop machine learning models and analyze and interpret data.
  • PIM Experts and Backend Developers: For the integration and configuration of the PIM system, as well as for API development to provide data.
  • Frontend Developers: To develop an intuitive user interface for easy use of the recommendations by sales teams.
  • Test Environment: Provision of a test environment with SAP data for analysis and development of AI models.

Approach and Milestones

  • Data Analysis and Concept Development: Evaluation of existing SAP data and development of AI models to identify initial patterns and insights
  • Integration of the PIM System: Implementation and configuration of the PIM system to structure the analyzed data and provide it via a REST API.
  • Development of the AI Module: Training and optimization of machine learning models based on data in the PIM system.
  • Frontend Development: Development of a user-friendly interface to display analysis results and recommendations.
  • Testing and Optimization Phase: Conduct tests with historical sales data and optimize recommendations.

Success Criteria and Outlook

Success will be measured by improved conversion rates and increased efficiency in sales. The prototype aims to demonstrate that the AI solution can identify significant patterns and actively support sales. In a future phase, additional data sources (e.g., weather data) could be integrated to further refine recommendations and better account for external influences.