Keeping customers happy has never been more vital to businesses- of all sizes.
That’s because the voice of the customer has never been louder; your customers have the power to bring you more business—or drive it away—via recommendations or rants that are amplified by social channels.
But if, as the old business adage goes, “you can’t manage what you don’t measure” how do you know if your customers are happy and what data can you best use to track it to grow your business?
The proof is in the analytics
Until recently many businesses knew very little about their customers. Now, through technological advances, the introduction of analytics and the wider understanding of using the “big data” to competitive advantage, customer data can be harnessed and used effectively.
By understanding how your customers behave and interact with your business, you are able to better serve, and profit, from the interactions. But it’s easy to be overwhelmed with the huge volume of customer data available and to decide how best to use it to reshape operations and build better customer relationships.
Analytics can play a critical role in delivering efficient customer support and, ultimately, satisfying your customers. Organizations actively using analytics tools in their support operations record a 12% faster first-response time to customer inquiries and completely resolve inquiries 16%, according to the most recent Zendesk Benchmark report. By allowing the business to monitor the interactions between customers and support agents using analytics allows the business to understand customers more, develop better strategies and improve the business.
By looking at the context of interactions – anecdotal evidence as well as quantitative date – it also supports progression of each support agent’s performance and helps with future staffing and training decisions.
Where to start?
Start simple and start with what we know makes customers happy. Zendesk’s ongoing customer research has taught us that a fast first response and a prompt resolution are consistently what customers’ rate highest in what they want from companies. They’re also really easy to track and to monitor and can teach you really valuable things.
Track response times and try to spot patterns; is there a time of day when it speeds up significantly, is there a day of the week that is slows to a crawl, how does the time of month affect responses?
How to understand it
Then do a bit of digging, context is really powerful and when set against data with often gives the greatest insights. For example you might notice that in the week after monthly payments are taken there is an increase in call volumes which slows response times? Do you have a ‘peak time’ of calls during the day?
In addition, by using analytics, you can raise the profile of customer service within the business by clearly explaining the value and progress of your work.
Both of those indicate that customer service could be made more effective. If there is a particular shift of employees that are responding quicker than other teams that could indicate higher proficiency or understanding. And that’s just one piece of trackable data.
You can survey customers to find out if they were happy with the service they received. You can monitor positive and negative mentions across social media. And that’s only the really top-line information; you can drill down into data to keep track of your most valuable customers or how the different tiers of support compare to each other.
Drive change & change the numbers to your benefit?
By marrying data with context, your business can find out what’s working, what’s not and put in place processes to boost or amend either. If you know that the 3rd week of the month is the busiest you can put in place extra resource that week. If you know that a certain group of people are excelling above others you can use their knowledge to train others, or try to hire based on their key attributes.
In addition, by using analytics, you can raise the profile of customer service within the business by clearly explaining the value and progress of your work. The support team can also use this data to justify and drive change within other aspects of the business if and where needed.
What not to track?
One of the most tempting things to look at when you first access customer service analytics is “cost per ticket”. It’s a good hard fact that is easy to explain to anyone in the business and feels like you’re working on offering value for money. But that’s why you should avoid it. It doesn’t show value it shows costs.
Your customer service staff could be telling your customers that they can’t help and hanging up, leaving unhappy customers unlikely to come back, but handling it all very quickly and really driving down “cost per ticket”. Not very plausible, but you wouldn’t know either way from cost data without context.
Trust yourself and your team
Knowing what makes your customers tick is really what’s going to point you towards the analytics that will serve you best. It’s not one size fits all, if your business is all about giving a bespoke experience with the personal touch a speedy resolution won’t be high on your objectives.
However, if you work in e-commerce the most beneficial data might be the most common subjects of the enquiries so you can start a self-service platform or FAQ to shoulder some of the burden. When it comes down to it the only universal metric of customer satisfaction is if you’re making money and keeping customers coming back.
Great customer service is a constant improvement process, particularly as your business and customer base grows. Using customer insights will shape and drive the business, ultimately giving your customers the service that what they want and deserve.
