Call Center Scheduling Featured Article
Call Centers Adopt Data Analytics to Improve Call Center Scheduling
There may be no corporate function that throws off more data than the corporate call center. Agent performance is measured as every contact is counted, routed, scheduled and scored. Throughout the history of the contact center, much of the analysis of that data has been quantitative in nature like calls received, average hold time, call length, resolution rate.
"Over time, companies added more sophisticated workforce management tools including global scheduling information to help with network call handling, scheduling, real-time adherence-but the data collected was agent performance- and efficiency-related," said John Magliocca, principal consultant for contact center service at outsourcing and management consultancy ISG, in a recent cio.com article.
That's beginning to change. Corporate call centers and call center providers are embracing new analytic tools to dig deeper into the big data they generate. Agents are being asked to handle a wider breadth of issues from more channels, including contacts from social media and online forums, which require advanced skills, better training and real-time guidance. Companies that have been disappointed with the off shored call centers are looking to emerging end-to-end CRM tools to save money on operations.
Software being implemented today takes unstructured voice recordings and analyzes them for content and sentiment. There are efforts to put contact data to work to best understand the current mood of the customer and information that can immediately mold client strategy, but until recently the systems were not robust and the information wasn't useful.
"Companies are applying text and sentiment analysis to this unstructured data, and looking for patterns and trends," said Deepek Advani, vice president of predictive analytics for IBM (News - Alert), which has implemented its Text Analysis and Knowledge Mining (TAKMI) tool at its own call centers. "Many companies are integrating this call center data with their transactional data warehouse to reduce customer churn, and drive up-sell and cross-sell. Call center logs can provide invaluable insight on what customers were calling about, and can also provide insights for future product requirements."
Most contact center operators are implanting emerging call center analytics that bring together real-time and historical data to isolate revenue-related calls, identify agent best practices, predict root causes of their dissatisfaction, or identify what characteristics of a contact lead to costly repeat calls.
Magilocca is keeping an eye on e-learning systems that can proactively determine a call center employee's biggest professional hang-ups by analyzing his/her responses to customer inquiries and suggests training modules to improve performance. Not all the new applications are big-ticket items as low-cost social media listening tools are enabling contact center managers to actively search words and phrases on Twitter (News - Alert) to identify brewing customer complaints or global issue.
Also, change management will become a big issue in the integration of the new systems and processes. The more sophisticated analysis must actually deliver more than the more rudimentary analyses of the recent past. Companies will also have to figure how to effectively use the information they generate. The analytics have to drive action, not just insight. It isn't enough to count issues and score sentiment; new solutions have drive agent behavior change or transformations of CRM strategies.
The customer contact industry remains hyper focused on the bottom line that buyers have to be confident that analytics will take out costs and identify new sales opportunities.
Edited by Carrie Schmelkin