Using Data To Improve Your Customer Service

Using Data To Improve Your Customer Service

Table of Contents

 

Every organization is collecting, processing, and archiving the massive amounts of data its users generate, so they can improve customer service more efficiently and consistently design services, products, and even rules that make possible a continuous customer experience. At the same time, however, many managers are already analyzing and taking actions that might benefit from the downloaded value data could provide to their businesses, without realizing it.

This tip sheet from Support Bench is an easy guide for learning to choose the right sources of data. What types of data would be helpful, how to interpret it and what to do with it? Based on Google, here are six methods to use, and some simple practices to get you started.

1. Data Created By A Consultant

The useful thing about data created by a consultant is its quick transfer from one source to another. While this applies to customers as well as to them: you don’t have to log into a spreadsheet to see what happened during a particular service or product upgrade.

You simply download the complete data without any modifications or themes. Then run the data through a website and a calendar. Research your number of requested upgrades, and refresh the calendar as and when you need new ones.

2. Data Created By Customer Engagement

Overcoming resistance to change, consumers can be very good at identifying which processes they like and dislike. A customer-engagement survey or survey answered anonymously will tell you about exactly what they don’t like. This is the information you can use as you work with new products and services on your payroll.

3. Data Created By Consumer Research

Google’s Webmaster Tools asks for feedback from users on new sites. User testing can help your website stay relevant and flexible, not only through new features but also through balancing existing options and the need to keep the site up to date.

4. Data Created By Master Or Assistant Data Collection And Analysis

Scalability of data collection and analysis should be easy, at least if you can squeeze it out of various sources of source, whether it’s big data sets or hard data sets. Try using raw statistics as well as predictive models. No matter the scale, the team at Google will work toward your goals and accept some red flags along the way.

5. Data Created By A Technical Dev team

An organization’s own technology department may create their own code when needed. But this data includes things that should benefit your business more generally, such as system configurations, hardware usage, custom patterns and so on.

The data should be easy to analyze and maintain. You should try to keep the audit software open to outside experts. Take time to start using this data for outside initiatives, too.

Information obtained in or through using data, even if your purchase of and use of it comes from a supplier, a vendor or a service provider, is information that could be very valuable to you. I recommend doing a batch of this to your complete list, starting with this to help you keep a low technical barrier to entry and even do analysis features.

6. Data Acquisitions And Contracts

Whether you acquire it or contract it, by tapping into analytics or Big Data, you will be able to know about what your users are doing, what their goals are and what might be different for them.

What are some simple tips to use data to improve your customer support? Please share your suggestions below!

Happy data gathering!

Support Bench unifies customer support, success, experience, knowledge management, and account management into one simple platform. Do more, with less, to maximize your retention and improve customer service.

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