To those of you who have been wondering about or considering implementing virtual queuing into your call center, I hope you found the previous blog posts on the topic useful. For ease and reference:
Part 1: Wait on hold or wait in line? THAT is the Call Center Question.
Part 2: How to calculate pulling the trigger on long call center wait times.
Part 3: Prioritizing unhappy customers, one call center’s approach.
But at an average implementation cost of $318,000, plus $32,500 in annual maintenance fees (according to a 2006 Forrester study), I would be remiss if I did not offer a solution to those of you who do not happen to have the budget for such an investment. Many of the business partners I work with share your budget and wait time challenges. Some partners of Customer Relationship Metrics, who are committed to improving service and satisfaction levels with wait time, have been very successful using more conventional methods.
Here are a few of their secrets:
1. Aligning staffing with call volume – This “secret” may fall into the “well, duh!” category, but that doesn’t explain why many call centers continue to be slaughtered each and every Monday by a predictable hike in customer calls. If it’s a budget issue preventing you from acting, a simple day of week or hour of day analysis (such as the one below) can help you justify a peak volume pay differential, over-time, etc.
2. Educate your agents on what drivers the perception of resolution – Approximately 40% of customer-perceived failures in achieving call resolution are related to how the agent communicated, not the process, not their actions. Find post-call surveys where customers reported resolution, pull those calls from your call recording system, listen to them and look for patterns.
3. Give customers what they want – and be quick about it! We all know that few things irritate customers as much as waiting on the phone to get to an agent. Once those customers get to an agent they may be short-tempered, confrontational, passive-aggressive and a slew of other pleasantries for agents to contend. Simple regression analysis can be helpful in identifying how to de-escalate these customers. This type of analysis was explained in a previously published blog post titled, “We got calls in Queue!” How Call Center Agents “should” respond to longer wait times…a Case Study in Call Center Analytics.
