In Shifting the Paradigm of Contact Center Interaction Tracking, we spoke of a paradigm shift that needs to be considered in standard contact center metrics. For the sake of all great social experiences, let’s revisit one of the most common and basic measures of contact center success – the service level.
Relying on service level to measure customer satisfaction
Oddly enough, service level has always been somewhat of a misnomer and often wrongly applied.
Service level was created to satisfy a base driver since contact centers needed a way to quantify how well they looked after their callers. And thus was born the 80/20 rule of quantification – where 80% of calls are answered within 20 seconds.
Makes sense, doesn’t it? Speak directly with your customers within a certain amount of time, within their threshold of patience, and everyone will be happy. Maybe not!
Service level today is so ubiquitous that hosted service providers and support organizations set their contracts to meeting service level agreements (SLAs) with financial repercussions tied directly to that service level metric.
While contact centers may have shifted those parameters over the years with a 90/10 or 70/30 ratio as the measured bar of success, it’s become tougher to generally apply that rule to customer communications.
At its fundamental level, meeting that quantified threshold does not directly equate to providing “good service” to your customer base.
What is good service? It is entirely held in the eye of the customer and how they feel about their unique individual experiences with your enterprise including how they perceive interactions with your brand. Service level was an incredibly indirect metric to equate waiting with dissatisfaction but that is not the only factor.
Measuring customer satisfaction – back then and now
Years ago, in the voice-only world, where the 80/20 rule was created, this metric along with mailed surveys from the marketing department would be the standard to gage customer satisfaction. However, both were separate entities that had virtually no correlation other than to say: “You can’t blame us that survey scores are low. We’re answering the phones quickly”.
Survey tools today have come a long way to capturing that customer feeling. However, the tendency of customers is to only complete a survey if their experience was negative and they feel the need to report a behavior or unsatisfied outcome.
This is a reactive process with lengthy delays before action can be taken. The damage often has already been done and their likelihood to recommend (Net Promoter Score- NPS) has been reduced. Historically a negative customer experience would simply make interesting conversation over coffee.
Today is a brave new world where technology affords us a better chance to gain visibility into the fundamental definitions of good customer service.
But with the advent of social media, it’s important to start looking at social media data, since social has become the means to vent and report poor experiences with businesses or otherwise. Folks do like to complain! This pseudo-friendship world increases the audience that will hear about any shortcomings your business may have. The ability to “share” and “retweet” grows that audience exponentially if the reader is moved by the initial statement.
Fixing customer experience before it is too late
That just means that today you simply must get it right because everyone will hear about it if you don’t. Unfortunately, that ideal is unachievable; perfection is unrealistic; and mistakes will undoubtedly be made. So, the question becomes, how can I mitigate the risk associated to bad customer experiences being broadcast throughout social media?
Leveraging social media data
Today we have the technology to view and access social media data through social media interfaces. A targeted push to collect social media profiles (via Twitter “follow”-ships” or Facebook likes, to name a couple examples) allows you then to collect and use social influence as a decision-making parameter when prioritizing their incoming interactions.
Those with a larger social network may have a higher priority to satisfy to hopefully leverage a “post” about positive experience as grass roots marketing or to lessen the broadcast impact of a possible negative experience. It is then up to the business to balance customer value and social influence in that prioritization.
Deploying intelligent routing that listens for social media data
Waiting in a queue and missing service level targets still has impact on the overall experience. But technologies today, such as intelligent routing, leverages customer value and social influence; virtual queuing and overflow routing all exist to eliminate that wait, reducing the overall impact of a service; level metric is the be all satisfaction statistic for contact centers. Intelligent prioritization lets you dictate which customers get faster service, thus reducing negative blow back towards your brand.
Relying on Net Promoter Score to make better decisions
So, what will fill that void in the future? The clue may have been dropped in an earlier statement. Net Promoter Score (NPS) should be the metric that drives your business decisions. “How many of our clients would recommend us to a friend?” We should make sure they all do, and keep that in mind for all our business decisions.
The technologies discussed herein all provide the ability to collect directly or indirectly data elements to produce a score at a client level or directly improve their experience.