Automobile

Turbocharging Sales and Procurement with Advanced Analytics for a German Automobile Giant

06

Engineers

06

Months

60%

Increase in data efficiency

Overview

A leading German automobile manufacturer was facing a number of challenges with their sales and procurement teams, including lack of real-time analytics and inadequate predictive modeling.  We developed a solution which was a success and helped the client to improve their sales and procurement capabilities. The solution was scalable and flexible, and it could be easily adapted to meet the needs of the client.

Services

Data Engineering, Machine Learning, Visualization

Technology

Python, Apache Kafka, Apache Spark, PostgreSQL, React, Tableau, Docker, AWS.

Location

Berlin, Germany

Challenges

  1. Inefficient Data Management: With a massive sales and procurement team spread across various regions, managing and updating pre-sales data was a considerable challenge. This led to inconsistencies and inefficiencies, hampering decision-making and customer acquisition efforts.
  2. Lack of Real-time Analytics: The absence of real-time analytics made it difficult for the sales and procurement teams to adapt swiftly to changing market trends, thereby affecting sales performance.
  3. Inadequate Predictive Modeling: Without predictive sales models, the team struggled with forecasting sales accurately and identifying potential customers effectively, resulting in missed opportunities.

Solutions

  1. Streamlined Data Management: We developed a comprehensive data management platform that allowed the sales and procurement team to update pre-sales data in real-time across different regions. This improved the accuracy and consistency of data, enabling better decision-making.
  2. Real-time Analytics Dashboard: An intuitive, user-friendly analytics dashboard was built to provide real-time insights into sales performance, market trends, and customer behavior, helping the team respond swiftly to dynamic market conditions.
  3. Predictive Sales Models: Leveraging machine learning algorithms, we developed predictive sales models integrated into the platform. These models accurately forecasted sales and identified potential customers, thus aiding effective customer acquisition.

Modules implemented

Data Management

Enables the sales and procurement team to update and manage pre-sales data across regions

Real-time Analytics Dashboard

Provides real-time sales performance insights and market trends

Predictive Sales Model

Uses machine learning algorithms to forecast sales and identify potential customers

High Level Design Architecture

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The Result

The implementation of our solution boosted the sales team’s efficiency by 40%, driven by real-time, data-backed insights, and predictive models which significantly improved customer acquisition rates.

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