call center metrics

Finding an Easy Formula to Do the Math is a Challenge for Contact Centers

When you google “contact center metrics,” there’s no shortage of suggestions to peruse. Lists of varying numbers of suggested metrics to be monitored pop up on the screen: 7, 13, 20, 27.  But which are the right ones for a company’s specific environment? The across-the-board metric cited is First Contact Resolution (FCR), which is a standard that just about every contact center views as critical to maintain and improve.  Similarly, Customer Satisfaction ratings, while not always quite as simple to define, are also a universal target to be monitored.

But it gets murkier from there. Many other commonly cited metrics, such as service level or average handle time, are not always directly comparable across channels; and evaluating teams that share some — but not all — queues is not always a precise process.  An ICMI study revealed that 39% of contact center leaders struggle to identify and measure key performance indicators.

A deeper understanding of metrics and how to calculate them helps a business set the right targets and reach goals to support its mission and vision. Each measure used to help determine how teams are performing needs to be understandable and actionable to individual agents, supervisors and management alike.  When all parties agree on what is important, a company can consistently track performance and see where to improve processes and training to help its agents do better.

Having this level of clarity on goals and metrics and knowing how they’re tracking towards those goals, creates employees who are more engaged with their work and empowered in their roles. A Dale Carnegie infographic shows that companies with more engaged employees outperform companies without engaged employees by 202%, and have customer retention rates that are 18% higher, according to loyalty strategy research by Colloquy.

Setting goals to measure performance can be somewhat tricky. Targets should not be so difficult to attain as to make them daunting for agents. There must be flexibility and compromise in determining how to balance between goals that appear to compete with one another, such as average handle time – where saving and time and reducing cost is paramount – and customer satisfaction, especially in cases that involve more complex interactions. When creating scoreboards to measure agent performance, businesses need to ensure that goals are instantly comprehensible and ready to act upon. They also need to make sense mathematically in tracking drivers across all contact channels including traditional, social, and mobile.  It’s helpful to use the same classification system across all interactions and equip agents to use it consistently.

Of course, simply knowing which metrics to use and how to score them is not the be-all, end-all for optimizing agent happiness. Going back to Google, one would find an astounding 147,000+ results for “benefits of a happy contact center agent”. The major areas of focus in these listings range from the obvious: “why agent satisfaction is important,” to the ubiquitous “fun things to do to keep agents happy” and the more specific evaluations of software and services to promote agent satisfaction.

Companies must be proactive in their approach to building models that are consistently accurate in predicting probabilities and outcomes in their contact centers. Models that are less than precise lead to failure to maintain desired service levels and result in cost overages. Businesses need to find innovative but proven methods to calculate the proper variables and the right things to look for in developing analyses that result in accurate forecasts.

Data abundance and complex operations make it challenging to develop, implement, and present clean, clear reports and on-target analyses. Over the next several months, agent-first solution provider Sharpen Technologies, developers of an always-on contact center platform built for the enterprise, will present a comprehensive series of complimentary webcasts on CrmXchange.

The four sessions are designed to demystify the process of determining the right metrics, show businesses how to measure and accurately analyzing contact center performance, and to implement those analyses across the operation so the entire organization stays focused on excellence. It will culminate in a discussion of how to put together the most efficacious math models for contact center executives and managers to glean actionable insights.

The first webcast in the series, “Attributes of Solid Contact Center Performance Metrics – and Attributes of Poor Ones”  will take place on Thursday, March 5.

The second,” Learn How to be Great: Helping Agents, Supervisors, and Execs Perform,” will be presented on Tuesday April 21.

The third session, “Setting Performance Goals and Scorecards,” comes up on Thursday, August 13.

The final presentation “Building Great “What-If” Models and the Resulting Analyses for the CEO” will be delivered on Tuesday, October 20.

All webcasts will be jointly presented by Ric Kosiba, Chief Data Scientist and Adam Settle. Chief Product Officer, Sharpen Technologies. Ric’s vast background of expertise goes back two decades to Bay Bridge Decisions Technologies which he co-founded in 2000. In that role, he developed the contact center industry’s first “what if” decision engine, a complex set of algorithms designed to forecast proper staffing levels. Adam is an experienced education professional skilled in Sales, Coaching, Team Building, and Training. He combines his extensive knowledge with hands-on experience as a trainer at Apple and Angie’s List.

Register now at no cost for the individual presentations or the complete series. Each webcast is at 1:00PM ET. If you cannot attend the live presentation, a link to the recorded session will be available within 24 hours.

3 Contact Center Metrics Improved by Predictive Analytics

Predictive analytics predict future events by combining various techniques that analyze historical and current patterns. Predictive voice analytics can have a major positive affect on integral contact center metrics, including customer retention, follow-up call success and quality assurance.

Customer Retention

One of the customer service industry’s main goals is customer retention, and experts believe that it costs more to acquire a brand new customer than to keep an existing customer. Predictive voice analytics, which analyze the customer’s voice during customer-agent interactions, can determine if the customer is at high risk for ending their relationship with the company altogether. It can then inform the agent that they need to put more focus on retaining the customer. On the flip side, predictive voice analytics can also tell which agents aren’t doing enough to keep the customer coming back. This is more effective than random checking for quality assurance, which can take a long time to identify poor-performing agents.

Follow-up Call Success

Often, the first contact with a customer isn’t the one that has a positive outcome (i.e. a sale); it’s the follow-up call that proves to be more advantageous. However, it’s difficult to know which customers are a priority for follow-up contact. Instead of leaving it up to your agents to determine which customers are worth a follow-up call, predictive analytics can analyze past interactions and study voice features to determine if the customer’s tone and behavior predicts a favorable outcome during the next interaction (like making a payment or finalizing a sale). Predictive analytics can create a ranked list of customers, organized by their likelihood to say “yes.”

Quality Assurance

Predictive analytics are a richer way of assessing quality assurance than traditional methods. Routine QA testing often ignores customer patterns, and it is also unable to learn in real-time. Predictive analytics, however, can analyze all types of data, both structured and unstructured, to give a well-rounded view of agent behavior and how it impacts the customer. All customer-agent communication is assessed in-the-moment, allowing the contact center to get an accurate view of agent performance immediately instead of having to wait several weeks.

Contact centers can’t just gather metrics to assess their current performance and then call it a day. They must also use what they’ve learned from the past to create goals for the future. Predictive analytics can help shape those goals realistically.

 

 

Contact Center Dashboard and Metrics

Software is an essential component of a high-volume contact center. From being an important element of sales to managing complex tickets, CRM dashboards and metrics play a vital role in your contact center.

3 Important Types of CRM Dashboards

  1. Key Performance Indicators Dashboard

The KPI dashboard allows the contact center to identify trends using data that’s been collected over a long period of time. Relevant metrics include average seconds to answer, call resolution, cost per contact, and service level.

  1. Call Status Dashboard

The call status dashboard monitors important metrics that can change from minute to minute, including call abandonment, call status, call volume, and current service level. Active and waiting calls is part of the call status dashboard, measuring the volume of calls to the percentage of callers waiting to talk to an agent.

  1. Contact Center Metrics Dashboard

The contact center metrics dashboard provides the analytics required to manage the contact center as a whole, including call status and call resolution. The goal of this dashboard is to help management and agents coordinate when a call “storm” is on the horizon.

4 Chief Metrics to Measure

–Average Handle Time: Measure the amount of time spent per call, including on administrative duties like submitting a call report. This metric can be used to measure both an individual’s performance and the overall performance of all the contact center’s agents.

–Call Abandonment: Measure how many customers disconnect before they’re connected to an agent. According to SoftwareAdvice.com, if a customer can’t resolve a problem or reach an agent in three key presses, they’re likely to hang up. By monitoring this metric long term, you’ll be able to see patterns that can be fixed with additional staff or technical adjustments. By monitoring this metric in real time as well, it will help you identify problems that are currently happening, which could prevent a small number of dropped calls from becoming a bigger problem.

–Call Resolution: Measure the outcome of calls to determine how well inquiries are being resolved, specifically whether or not they’re being resolved during first contact. The call resolution metric is a barometer for contact center efficiency and customer satisfaction. While there are some problems that may take multiple calls to resolve – like a complex technical issue – this metric’s red flag is the number of current open tickets.

–Service Level: Measure your contact center’s ability to follow through on arrangements made in the service level agreement (SLA). SLAs promise to answer X percentage of calls in X seconds. This must be measured in real time so that you’ll know right away if there’s a problem. Service level can be affected by a number of issues, like an unexpected surge in call volume, unexpected service outages, or a shortage of agents. In some contracts, financial penalties or loss of contract can occur if SLAs aren’t met.