Bridging the Gap - From Call Center Metrics to Bottom-Line Objectives
1 Nov, 2007
By: Pat WhelanMuch contact center data, while vital to the contact center’s ongoing success and management, does not translate easily into metrics that corporate management can use to measure the success of their campaigns and manage efficiently for improvement. So much information is generated in the contact center that it can be difficult to determine how to analyze the metrics that matter – to know where measurable improvements can be made.
Additionally, much of the reporting data that emerges is delivered in batches to corporate managers. This method of batch delivery does not lend itself to making flexible, rapid assessments and course corrections. The combination of massive information flow and summary batch reporting can make it difficult for corporate managers to bridge the gap – connecting the dots – between the performance data in the reports they receive daily and the key success metrics toward which they must manage.
Is the Solution More Data?
Corporate managers are interested in broad, success-focused indicators like: How much money are we collecting and how much does it cost us to collect it? What are our customer satisfaction levels? What is our renewal rate? These measurements typically fall into three general classes: service level, quality of service and operational efficiency. Working to keep afloat in a sea of data, they might reasonably ask the question – “How does this data relate to our success metrics?” Raw data itself is not fundamentally useful. What key stakeholders typically need is information, delivered in a timely, accurate and clear fashion. Corporate managers need to make connections – to understand clearly how a change, say, in abandonment rate, can affect a customer satisfaction number, or how a longer handle time might actually impact collections results.
The most successful organizations are those that can extract real information – information that helps them rapidly, flexibly plan and improve – from the sea of data generated in the contact center. One solution is to use more targeted data, data that managers can connect to real-world operational objectives and use to optimize campaigns. Some of that data is available now in a growing number of contact centers.
Today, evolving automated communications solutions are changing how organizations interact with customers. These systems can be delivered using a Software as a Service (SaaS) hosted model.
Regardless of the efficiency and security of the delivery model, like any new system, these automated communications solutions also generate new classes of data as they operate – real-time customer response data that they aggregate and report on using a wide range of online information delivered through a secure browser interface. Is this just noisier data to pass in front of management eyes, or is there real value in this new type of data – value that can translate to making good operational decisions in a timely fashion?
On-Demand Data from Automated Customer Communications Systems – Actionable and Immediate
Descriptive metrics from automated communications solutions can include a variety of data about what communications channels customers prefer, to data measuring customer response to different voices and voice styles (e.g., male versus female, old versus young, rapid pace versus deliberate), different scripting styles (conversational, formal), responses to contacts at different times of day to retry strategies and more. If the solution permits, even more granular measurements can be generated by traps or “checkpoints” at specified points within the communication itself. Analysis of these checkpoints can offer a basis for tuning and revision that improves quality of service and operational efficiency.
As an example, customers may be dropping off from your communications before the information has been fully delivered. How many of them? At what point in the communication? And what steps can we take to quickly correct this situation so more customers will listen to more of our communication and take action? Customer response and interaction data can provide critical information about how many (and which!) customers chose to speak to an agent, how many chose to accept an immediate offer or, in a collections setting, perhaps pay immediately through the application.
Call center management can collaborate with their automated communication partner to evaluate this data using the partner’s deep set of best practices, based on delivering billions of communications in a variety of situations and the call center’s domain knowledge. They can then analyze the results using the partner’s reporting suite and codify the results of the analysis. There is proven visibility and operational benefit to be had in aggregating and analyzing this new class of data – real-time customer response data.
In fact, reporting on this type of data offers managers a real opportunity to improve both operational efficiency and customer interaction quality. Given the ever-increasing tempo of competition, the ability to manage and analyze these new sources of customer information can provide a competitive advantage.
One other source of value is that more sophisticated vendors may provide many of the reports (as noted) on-demand, through a secure Web based interface. The immediacy of this report data can be critical. Starting a new campaign? Want immediate visibility into results? Click a secure Web link and view progress as it happens. See a sticking point? The on-demand SaaS model enables many changes to be made on the fly or very quickly.
When starting a new campaign, organizations set in motion a process that can touch many thousands or even hundreds of thousands, of customers. Viewing actionable reports on progress and results on-demand contributes to the ability to make changes for improvement quickly and flexibly for maximum impact.
Adding Automated Communications Data for Improved Performance and Visibility
Encouraged by the broader acceptance of automated customer communications solutions, many contact centers are adding customer response and preference data to their analytics and reporting mix. Organizations typically know certain historical facts about customers – for example, what credit score they have or what phone plan, what business they may have done in the past with the organization or other relevant, historical data.
Adding real-time response data as provided by an automated communications solution, organizations can uncover valuable information about present customer behaviors and preferences. It’s important to remember that while managers are generally informed by the past, they must execute on the present and future.
Applying This New Data in the Real World – A Case Example
A large Midwest utility used the data generated by a checkpoint report to improve its operational efficiency and quality of service.
Daily, this utility used an automated customer communications solution to contact tens of thousands of customers and review their billing status. Reporting from the system showed that there were a large number of customers who terminated the connection without reviewing their billing status and responding. Experienced managers might certainly make a number of useful speculations as to why this was happening – however, with the data supplied by its automation solution, managers were able to analyze the issue and make a quick, effective change.
Analysis of checkpoint data generated by the automation solution indicated that more than half of the customers who terminated the conversation did so at the point where the communication requested the last four digits of their Social Security number to verify their identity (since this was a billing communication). A reasonable hypothesis was formed that many customers were reluctant to reveal this information, and instead terminating the call.
After some discussion, the utility agreed to test a less intrusive form of verification – the customer ZIP code. Applied across a randomized set of customers, this seemingly simple change immediately resulted in greater than 20 percent lift – that is, 20 percent more of the entire contacted population listened to the full billing status communication and responded. The utility was able to modify customer behavior in an operationally significant fashion by applying analysis of this new data to suggest the creation of a challenger program.
Connecting Those Dots
As management information systems improve and the technology used for monitoring call centers becomes more sophisticated, contact centers are applying new ways of evaluating their customer communications strategies. By using this new, actionable source of data delivered through on-demand reporting, corporate managers can generate strategies that immediately impact their bottom-line objectives and success metrics. Both the new data itself, as well as the immediacy of its reporting, can help bridge the gap between contact center data and actionable management information.
