How customer service is improved through analytics

Keeping customers happy is easier said than done when it comes to serving millions (or even billions) of customers over a fiscal year. Still, in this socially-driven era of communication, every firm is obligated to improve customer service by any means possible. Finding opportunities to do so has been made possible with the help of data-driven analytics.

Improving travel with big data

Serving 100 million passengers annually with budget air service, keeping track of customer satisfaction, and finding opportunities to maintain peak customer service without raising costs is a major challenge for airlines like Southwest. To cope, the airline takes advantage of Big Data to identify social media opportunities to engage with its customers and solve issues on a case-by-case basis. The information is then fed into its global analysis of patterns, which they use to prevent future customer concerns or mitigate complaints across its fleet of 674 aircrafts. The goal is to better predict, identify, and prevent complaints, not just address customer concerns as they occur.

This example also holds true for road travel among the BMW Group and rental car firm Hertz. Both firms have utilized Big Data analytics to identify concerned customers in the service end of their businesses. In BMW’s case, improving customer service depends on both improving the vehicle maintenance process, but also identifying opportunities to improve vehicle design and prevent necessary maintenance. With Hertz, the company looks to Big Data to help identify and sort through customer feedback. Using emails, text messages, and online surveys, Hertz finds ways to improve the car rental experience.

Big Data’s impact on food service

Another opportunity in data analytics and customer service comes with one of the largest food service companies in the world. McDonald’s serves millions of customers each year and uses Big Data as a way of understanding priorities in the fast-paced drive-thru sales experience.

In analyzing food service satisfaction, the challenge is scale and complexity. Programs must account for the type of food ordered, the time of day, weather, time of year, and many other variables. McDonald’s leverages this vast amount of data to find new patterns and determine experimental instances to try and improve the dining experience for its customers, while accommodating for the many different cultural and regional differences that emerge in the process.

The data discovered through this large-scale analytics operation is curated to account for differences and maximize the value it can offer to franchises in menu offerings, training methods, procedural changes, and other customer satisfaction improvements. Coupled with social operations, this data analysis in turn enables McDonald’s to make something as simple as selling food into the 24-hour experience it can, depending on how customers each interact with the brand and experience the food and service throughout each day. It’s a tall order, but Big Data helps facilitate this 24-hour brand experience that centers on improving satisfaction.

Keeping customers happy with accurate metrics

Big Data continues to impact pattern analysis, opportunities, and other factors in the day-to-day necessity of ensuring customer satisfaction. From identifying brand improvement opportunities to discovering pain points in the product itself, the possibilities for improving customer service are endless. By using data-oriented information to make more informed decisions on improving supply chains and service systems, companies ultimately add value to their customers’ experiences.

About Emre Yayıcı

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