In a recent article at Contact Center Pipeline, Jay Minnucci discusses “an introductory approach to enhancing frontline leadership skills.” From Minnucci’s perspective, a “comprehensive training program is the ultimate goal” for contact center leadership, but an introductory approach is a reasonable place to start. With this strategy, you can offer content in three areas: basics, metrics, and technology. Regarding the metrics, it is important for your contact center supervisors to have a full grasp of the critical numbers that they focus on every day. Many can tell you the objectives and the consequences, but they should also understand the calculations that supply each metric. This level of detail can provide supervisors with a better picture of overall performance. Successful supervisors can provide “clear feedback during coaching session. They get the what and the why…they get the how much.”
Saulnier outlines “five fundamental components that need to be in place to provide an excellent customer experience.” ...Each of these components is clearly critical to long term success in the contact center; however, the fifth component is particularly compelling. Read More. http://www.inovasolutions.com/blog/post/implementing-call-center-reporti...
For the seventh year, DMG provides the Contact Center Performance Management Market Report including details about “vendors, products, technology, market trends and challenges, benefits, return on investment, competitive landscape, market share, market projections, adoption rates, pricing, and best practices.” Inova Solutions is one of a handful of featured vendors that are capable of providing real-time performance management solutions.
With respondents indicating interest in receiving callbacks, this technology seems to be a viable option for improving customer satisfaction as well as improving standard contact center metrics such as average hold time and longest call waiting. Borowski outlines three potential ways to integrate the technology.
Anyone who works in a call center knows about the peaks and valleys in call volume, “no matter how many Customer Service Representatives (CSRs) you have available, it's impossible to meet the current demand for your services.” McGarahan makes the logical case that call volume spikes can be either planned or unplanned.
In my last post, I covered McGarahan’s recommendations for mapping both planned and unplanned peaks in call volumes at your contact center. Identifying patterns is really only the first step; you also need to take steps to efficiently manage the peaks and valleys. McGarahan also offers several tips for managing service demands. - See more at: http://www.inovasolutions.com/blog/post/surviving-call-center-peaks-and-...
An article in the April 2014 issue of CRM Magazine headlines “Contact Center Satisfaction Dropped 10 Percent in 2013.” There are several possibilities for why this might be the case: general customer fatigue and frustration with the slow economic recovery, delays in new technology deployment by companies, and higher expectations by customers.
There is a lot of talk about big data and metrics in all industries today, and the contact center world is no exception. An article in the April 2014 CRM Magazine highlighted one of the weaknesses of this new push for more data: “our view of data often doesn’t extend further than numbers.” In the article, “Data Versus Knowledge,” Denis Pombriant writes that the numbers we often think of as data are quantitative, which is only one type of data.
Telecommuting used to be a novel concept in the workplace, with the option to work somewhere other than the office being a rare privilege. No longer the case today, remote call center agents are increasingly common in a variety of industries and the contact center is no exception. In the March 2014 Contact Center Pipeline issue, Scott Murphy discussed the topic in his article, “Overcoming the Challenges of Managing an At-Home Workforce.”
The article, “Big Data Prompts ‘Analytics Everywhere’ Solutions,” highlights the well-known challenge that much of the big data solutions target a small group of employees rather than the larger number of employees in business areas who can apply and use the metrics to change behavior.