Improve the Customer Experience with Data Science as a Service

by   |   February 5, 2015 5:30 am   |   0 Comments

Chris Wareham, Senior Director, Product Management, Adobe Analytics

Chris Wareham, Senior Director, Product Management, Adobe Analytics

In a previous column, we discussed how to use data science as a service to improve internal workflows. This approach can improve information sharing, wait times, employee productivity, and more. These changes improve internal processes and overall job satisfaction. But many organizations do not like to invest in technology simply for the sake of improving internal processes. So, let’s talk about how using data science as a service affects the customer service experience and, ultimately, the bottom line.

Many enterprises struggle with the concept of how using data can affect customers’ impression of the brand and their long-term loyalty. But clients that are extremely happy with your service are unlikely to try out a competitor. So good customer service is worth a premium, especially in this day and age, when fewer local businesses truly know your name. Using analytics packages that allow you to understand your customers like a local neighborhood business would offers you a huge competitive advantage. As my analytics colleague Ben Gaines wrote, “Almost invariably, your customers do not see your brand as a collection of channels: web, mobile, call center, point of sale, etc. You are one brand, and customers expect to be known however they interact with you.” This is the core reason for using analytics and making the insights available as a service: to provide a window into how your customers interact with your brand, at scale.

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Decades ago, we were lucky enough to be able to know every customer who walked through our doors – their names, their spouses, their financial situation, and what they might be likely to need. Business owners could easily service their customers because they saw them often enough to predict what they may need. Changing demographics and the growth of the Internet have increased the opportunity to gain customers outside of our local area and improve our bottom line. However, in this democratization of business opportunity, we’ve lost the ability to know our customers. Now, predictive analytics and data science as a service provide organizations with the ability to have the best of both worlds – data allows you to know your customers without having to limit yourself to a niche group. Data enables a relationship that hasn’t been available to most companies for years.

Your customers’ perspective of and experiences with your brand often determine how likely they are to return for another purchase as opposed to trying a competitor instead. Attaining a new customer can cost up to seven times more than keeping one you already have, and 71 percent of customers say they have left a company due to poor customer service. So the key to customer retention that can strengthen your business may well lie in optimizing your customer service experience from end to end. Data science as a service can help achieve these goals.

To put the potential business value of data to good customer service into perspective, consider the following example: You check into a hotel that is a part of a chain you stay with regularly. You give them your rewards number. You go up to your room. A few hours later, you access the hotel Wi-Fi and check your email. You see an email from the hotel chain with the subject line, “We haven’t seen you in a while.” You chuckle to yourself because as you are reading about how the hotel hasn’t seen you in a while, you’re literally sitting in their hotel, using their Wi-Fi.

Imagine if instead, you received an email offering you a free appetizer at the hotel restaurant. Isn’t that something you’d value more? And wouldn’t you be more likely to marvel at how they predict and help meet your needs, and visit them again? Maybe most importantly, wouldn’t you be likely to eat at the restaurant? It’s convenient and – hey, you have a coupon now! The right data analytics package makes all this possible. You can use data to make your organization a rock star in customer service. That will increase your bottom line because people can’t resist working repeatedly with companies that provide excellent customer service.

Using data tools that surface customer information in workflows helps remove barriers to truly knowing your customer. Data also can provide knowledge that is actionable, as in our hotel example above, allowing you to improve customer relationships while also improving revenues. Using data to better understand and serve your customers is a powerful strategy that will increase return on marketing investments, improving sales figures, and your bottom line. Plus, your customers will truly enjoy working with your company. Isn’t that a goal we all should have?

As senior director of product management for Adobe’s Analytics Solution, Chris Wareham directs the teams responsible for mapping strategy and driving the innovation and growth of Adobe Analytics.

Wareham has nearly two decades of high-tech experience. In addition to more recent roles at Omniture, Micromuse, and IBM, he started his private sector career at Lucent Technologies, where he helped develop mobile telecommunications networks in Caribbean/Latin America and Asia/Pacific regions. Prior to that, he served as a squad leader in the US Army’s electronic warfare service. He holds dual Bachelor’s degrees from the University of Kansas, and was his class salutatorian at the Defense Language Institute, where he studied Arabic.

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