Call center analytics refers to the processes and tools that organizations use to gain business performance insights. Management can track and improve various service metrics, including call times, employee performance, efficiency, and customer satisfaction.
By processing unstructured data from different sources into useful reports, organizations that use call center analytics can formulate customer-centric strategies for their contact centers.
Types of Contact Center Analytics
1. Contact Center Speech Analytics
Speech analytics can help call center agents manage the customer experience by learning from positive and negative customer interactions and how to mitigate customer issues through coaching and training learned from speech analytics.
2. Contact Center Text Analytics
Text analytics provides an analysis of the transcription of text interactions between a customer and an agent. Text analytics works for e-mail, Twitter, Facebook, and other text-based media. Text based interactions can be improved by identifying weaknesses in automated responses and improving the AI experience before an agent transfer is required.
3. Contact Center Desktop Analytics
Desktop analytics involves monitoring desktop activities of call center agents and system performance. By analyzing desktop activities, it is possible to achieve significant process improvements for the call center.
Organizations can use desktop analysis alongside call monitoring to improve call center security, capture inefficiencies, and identify phone agent coaching opportunities.
4. Contact Center Cross-Channel Analytics
Cross-channel analytics seeks to understand which paths or channels combine to drive customer conversion. This includes understanding what paths are popular within and across channels and finally provide detailed analysis of specific visitor paths. By finding this path, marketers can concentrate advertisement and marketing efforts along that path or create other avenues just like it. Also, analysts can understand the impact of each channel and how they work together.
5. Contact Center Self-Service Analytics
Self-service analytics evaluates customer experience in the organization’s self-service channels. Users can drill and discover improvement areas for a whole range of customer self service solutions and gain a full picture of the underlying efficacy, automation rates, and sentiment of these customer self-service tools.
6. Proactive Analytics
Through proactive analysis, management can evaluate and identify ways to communicate effectively with customers. Proactive analytics allow businesses to make changes that improve by seeing developments as they occur in real time. This can mean taking advantage of a sudden surge in a specific products’ popularity or reducing production when sales decline as it happens instead of after. This method should be the standard approach of information gathering and subsequent decision-making.
With proactive analytics, you can harness the power of your data to project trends in your industry and adjust to your audience’s key pain points.
What are call center analytics? SuccessKPI.com provides organizations with call center analytics that give management full visibility across all channels. Learn more here: