Once upon a time, the charter of customer service was to put the customers’ needs first. But it cost money. So much money, in fact, that customer service started to focus less on their charter and more an important goal: to control costs. As a result, call center metrics were born. By talking to the customer less and hanging up faster, customer service could save money.
But customers called and complained. They called and called, until they finally stopped calling. So, customer service began focusing on a new goal: to make customers happy. And customer satisfaction metrics were born. But customer satisfaction was not easy. Making customers happy required more talking—and more money.
To save money, self-service was born. But it wasn’t easy for the customers to help themselves, so they became even less satisfied. Customer service was then told to sell stuff to customers. But selling stuff required more talking—and more money.
Customer service wanted to do the right thing but got caught in the struggle between keeping costs down and keeping satisfaction and revenue up. And to this very day, customer service struggles with this dilemma.
I expect your organization hasn’t lost complete focus of your customers. However, I also expect that you probably have a difficult time managing all your diverging and competing goals. For example, how can you keep your average handle time (AHT) low when you’re expected to increase revenue? The extra time spent cross-selling kills your AHT metric.
As a result, service organizations are changing the metrics they use to assess contact center performance. Traditional metrics like AHT are important, but they must be recognized for what they are: measures of tactical performance, not value performance.
If agents are incented to end calls quickly and “resolve” calls on the first try (but really don’t), satisfaction metrics suffer greatly, even though AHT and first-call resolution (FCR) might appear to be performing well. Research by the Customer Care Alliance shows that service issues with three or more contacts leave only 6 percent of those customers satisfied.
Until now, organizations struggled with aligning competing goals, either leaving their agents to cope or by instituting generic rules. In both cases, the interaction takes place without a rational consideration of overall revenue, retention, satisfaction and cost goals. It’s an amazing phenomenon, considering the customer interaction holds so much value.
But now, with real-time decisioning, you can align your service goals to meet all your objectives on a customer-by-customer basis. Real-time decisioning gives you the ability to change customer behavior, agent behavior and process behavior while interactions are taking place.
Here’s how real-time decisioning works:
- You define your specific performance goals, such as retention rates, self-service success rates, cross-sell revenue rates and cost targets. These goals are tracked and managed.
- You connect the system to your enterprise applications, CRM applications, self-service channels, databases and other systems. Connecting the real-time decisioning platform to these types of applications and data sources is fast, and typically takes a few weeks.
- The system continually monitors the real-time stream of events that are generated by the flow of customer and process interactions within the enterprise.
- The real-time decisioning platform automatically builds and maintains real-time predictive models that track and explain the specific factors that drive your key performance goals. On a real-time basis, the shifting patterns of customer and process behavior are continually discovered and prioritized.
- You make real-time adjustments to your business processes to improve your performance relative to your goals. Some of these adjustments will happen within the business process in real time; others will happen through offline changes to people, process or technology.
By tying real-time decisioning to the improvement of specific performance goals, an organization can add intelligence and dramatically influence every enterprise business process. Here’s some examples of what you can do with real-time decisioning. You can:
- Correlate attrition drivers with individual customers to guide your agents to take the right actions to reduce customer defection and churn.
- Dynamically display cross-sell offers to agents when the potential cross-sell profit is worth the total handle time.
- Eliminate self-inflicted call volumes by identifying the “reasons behind the reasons” for the most common calls.
- Identify service issues that most frequently drive additional calls, and direct agents to extend handle time to prevent additional calls later (FCR).
- Find correlations between customer satisfaction and cross-sell acceptance to predict cross-sell opportunities.
- Predict customer need and dynamically route calls, in turn decreasing overall handle time and improving customer satisfaction.
A communications company used real-time decisioning to compare its customer churn with the length of time customers had been with the company. It found that new customers most frequently cancelled service in the first seven to 30 days. And it found that there was a high proportion of calls from customers within their first seven days. As a result, the provider proactively addressed new customers with targeted service information and lowered its churn rate.
A financial services company was able to identify and score individual agents against FCR metrics and cross-reference FCR success with such elements as customer segment and product line to identify the specific areas of weakness for each agent. With pointed training, the organization saw its FCR rate improved.
Don’t let your business become “the enterprise that couldn’t” because technological limitations, cost constraints or conflicting goals led you to lose sight of your customer. Real-time decisioning is one of the most important technological innovations to drive successful customer experiences, as well as your objectives.
