The rapidly digitizing world has granted today’s business leaders unparalleled insight into customer behaviors and preferences.
Knowing how to use this data is just as important as having it all.
This week research firm Software Advice sat down with Zendesk Vice President JD Peterson to discuss strategies for tackling this mass of data. Here’s what he had to say.
What Gets Measured Will Improve
Peterson started the conversation with tips for metrics and ratios. Above all, he said companies should look at customer satisfaction – or how satisfied that person with the resolution they received. Next, he recommended factors that contribute to that score, such as first human response and time to resolution.
Call deflection is also a really important metric for cost control purposes. to measure those successes, he recommended a self-service views to ticket volume ratio.
Let’s Share
Increasingly customer service, marketing and sales break out of their silos to align strategies. Data is a great way to do this.
“Years ago customer service was looked at more as cost of doing business and not a revenue generator and not connected to the rest of the business. But more and more people are realizing how valuable that customer asset really is and how can people leverage that information in sales and marketing,” Peterson said.
He recommended starting with a sales CRM and customer service software integration. This way, customer service agents can see whether or not that person is engaged in an active sales cycle. Likewise, marketing and sales can gauge customer sentiment before they send out a big campaign.
Socially-Minded
Finally, Peterson talked about data analytics as it applies to social. Customer service technology for social media can pull every conversation about the brand into one report that shows trends over time. This includes things like repetitions in feature requests that could be shared with product development and marketing.
Check out the entire video here: http://youtu.be/R-VGRAcLEYg
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I agree with you that what’s measured can be improved. Now, the challenge is to measure things right so you can have the right plan to improve solutions for your business. Then, there’s another issue of interpreting data accurately so you come up with the right analysis to come up with the right plan. The problem is – there’s not a lot of data scientists out there who can filter through all that information you gather about your customers. Just a thought.
@Shaleen – you’re right: complex data analysis can be a challenge. I’d recommend picking one or two key metrics and mastering those before moving on to a bigger set of data.