Contact center interaction management solutions have historically taken a retroactive approach: examining past transactions to form judgments on the value of customers today. In many contact centers, callers are still routed to the longest available agent. More advanced contact centers go one step further, using skill-based routing to send callers to the agent who is best able to handle the call, typically based on the reason for the call and how the agent has been “graded” for specific skills. But a trend that not only maximizes the value of customer relationships, but also drives higher levels of revenues and profits, is that of predictive analytics.
A recent report from research firm Opus Research, “Predictive Analytics Report: Using Big Data to Improve Multichannel Customer Care,” shows that top enterprises, including companies like IBM and Oracle, now rely on analytics to assess risks as well as opportunities. The same approach can have equal benefits for contact centers. With the right predictive analytics tools, for example, companies can automate system and agent behavior changes that increase first-call resolutions, sales conversions, revenues and customer satisfaction and retention. Months or years of data from one or more contact center systems is collected and connected, to analyze it for insights into what factors drive performance and to profile agents and teams using measures that are important to the business.
In their report, Opus includes four ways that contact centers can use analytics with big data to gather insights, and in turn make better business decisions:
1. Efficiency: Analytics tell contact center managers how to properly staff each of their contact center locations, ensuring optimal staff for web, social and phone outreach from customers.
2. Customer retention: Analytics surfaces high-value and at-risk customers, identifying those that require special treatment by an agent with special capabilities.
3. Revenue enhancement: Another advantageous feature of predictive analytics is recommendation engines, which determine customers with high propensities to buy certain products and make sure they receive the right offers. This increases company revenues.
4. Effectiveness: Predictive analytics frees agents to do their jobs better, by cutting out the more mundane pieces of the customer interaction process so that agents can focus on providing a pleasant customer experience.
Opus’s research has found that use of predictive analytics is still an emerging trend, with much room for growth. But when properly applied to large amounts of data in contact centers, predictive analytics produce extremely beneficial results, including boosting customer satisfaction, reducing fraud and making agents more efficient.
CC-One has some very cool predictive analytics-driven call routing solutions.
