Workforce Optimization Ushers in the Real-Time Contact Center

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Enterprises increasingly recognize the need to listen to customers and prospects across voice and digital channels to obtain a comprehensive view of their experiences. Speech and text analytics, also known collectively as interaction analytics, provide a firsthand, unfiltered view of what transpires between customers and an organization. Interaction analytics collects data from free-form, open-ended dialogues; it can also mine customer data from the web and social media to extract information about customer sentiment. Enterprises are leveraging interaction analytics to replace outdated methods (surveying, focus groups, etc.) of capturing feedback from customers.

Interaction analytics has become an increasingly important source of data for customer journey mapping because it provides a multidimensional view of the customer experience. It reveals which touchpoints customers used to interact with an organization, what route they took, how long each part of their journey lasted, and where the journey ended. Interaction analytics provides the soundtrack for understanding customers’ perception of what happened as they traversed channels by capturing sentiment and emotion and, by extrapolation, the amount of effort expended. As an input to customer journey analytics (CJA) solutions, interaction analytics enables companies to listen to their customers and take a data-driven approach to identifying the appropriate course of action. CJA solutions paint a holistic picture of each customer’s interaction with an organization, from the first touch through the last, allowing enterprises to evaluate a substantial portion of the customer journey.

Another emerging strategy for managing a personalized customer experience is the use of predictive analytics. Using data mining, statistical techniques, and machine learning to identify relationships, patterns, and trends, a predictive model can be built to anticipate future events or behaviors, as well as their potential business impacts. Speech and text analytics are being enhanced with predictive analytics capabilities to enrich and personalize each customer interaction. Predictive analytics can be used to understand what customers need and want, and then kick off real-time agent guidance, next-best-action recommendations, or optimal marketing/sales offers. Predictive analytics can also be used internally to identify and understand the drivers of agent churn and to recommend intervention.


Contact centers are not going away in the foreseeable future, but DMG expects them to change. Here are a few of our predictions about contact centers and the likelihood of each:

  1. RPA/bots will automate an increasing amount of work currently done by agents in contact centers within the next five years (1.0 probability).
  2. Machine learning will be incorporated into many contact center applications to improve their performance and reduce dependence on IT resources within the next five years (0.9).
  3. Speech analytics will replace the traditional QA process in the next eight years (0.7).
  4. CJA solutions that capture, analyze, and identify opportunities for improvements will emerge in the next six years (0.65).
  5. In the next six years, AI will drive omnichannel routing to ensure all interactions get to the right people in the organization for resolution, while also taking into account the cost of handling each transaction (0.35).
  6. Contact centers and back offices will merge in the next 10 years (0.3).
  7. Self-service solutions will eliminate the need for live agents in the next 10 years (0.1).

The overarching themes shared by these seven trends are productivity improvement, enhanced quality, and reduced costs, driven by AI-related functionality. What’s new today is the use of technology to work smarter, not harder, instead of just motivating agents and supervisors to perform their jobs faster and do more with less.

For contact centers, AI and automation will reduce the need for low-value agents. AI-enabled bots and IVAs will deliver information and provide answers more quickly and accurately than poorly trained agents, and they’ll do so more cost-effectively; this will profoundly change market dynamics. As the quality and effectiveness of self-service solutions improve, the number of contact center seats will decline. This will reduce dependence on outsourcers, particularly low-end offshore providers.

Companies will need to rethink and redefine the role of “agent,” as they will need fewer of these resources. The remaining agents will handle sensitive and complex service and sales situations. Transaction handling will be personalized, matched to the ideal resource and intelligently routed to highly sophisticated agents who have a new generation of servicing solutions at their fingertips to achieve optimal outcomes for the customer and the organization. It’s been a great run for the WFO sector, and the best is yet to come. 

Donna Fluss is president of DMG Consulting. For more than two decades she has helped emerging and established companies develop and deliver outstanding customer experiences. A recognized visionary author and speaker, Fluss drives strategic transformation and innovation throughout the service industry. She provides strategic and practical counsel for enterprises, solution providers, and the investment community.

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