Worldwide Brewing Company Improves Logistics, Operations, and Customer Service with Data Science Solution

Company Overview

This company is a worldwide brewing company and leader in the beer industry.

As part of their commitment to outstanding delivery operations, a logistics division at a worldwide brewing company launched a survey to understand how their customers felt the company’s drivers were doing. At accounts with unsatisfactory survey results, the company would conduct customer visits to try and improve the relationship and avoid customer churn.

But the process to gather customer sentiment was very manual which meant efforts to address poor ratings at many accounts were initiated too late. On top of this reactive process, a 10% survey response rate did not provide enough context for the company to understand indicators that led to poor scores.

Instead of waiting for unhappy customers to share their dissatisfaction, the company wanted to predict which customers were likely to churn and understand the drivers behind a poor rating so they could take proactive steps to improve delivery operations and customer satisfaction numbers.

Machine learning models and advanced analytics techniques allow the company to take a more proactive approach to customer satisfaction and lowering customer churn.

By introducing predictive analytics into their dashboards, the company has a more reliable list of accounts that may be at risk of churning. This means they can make visits to at-risk customers before they become real problems.

The model also provides more insight into the “why” behind bad ratings and customer churn. Understanding specific KPIs that lead to unsatisfied customers allows the company to offer personalized solutions on an account level as well as make overall process improvements that will positively impact the business.

With stronger data and analytics, the company is equipped to improve logistics efficiency, delivery operations, and customer service.