The Other Side of Customer Journey Analytics

The Other Side of Customer Journey Analytics

By Mike Bourke, Senior Vice President, GM Workforce Optimization

Customer Journey Analytics is one of the hottest topics of discussion among those of us leading the quest to deliver the best possible customer experience. It’s a bit of a mix of high impact revelations made possible by a new way of thinking and lofty idealism about what’s possible under the right circumstances. The current school of thought regarding customer journey analytics, although largely unrealized as of yet, appears to have much promise:

  • The ability to deliver a personalized customer experience consistently across all channels and points of interaction
  • Understanding your next best action to achieve enterprise goals such as driving cross-sell opportunities and higher customer loyalty
  • Understanding your customer’ preferences and information needs so you can proactively address them

No doubt customer journey analytics can yield great benefits. In a cross-vertical study entitled Customer Journey Analytics and Big Data, McKinsey found that customer journeys are 30% – 40% more predictive of customer satisfaction and churn than data from individual customer touch points. That’s high value and allows better decisions to be made about customer treatment.

However, traditional thinking about customer journey analytics overlooks a potential huge benefit from tracking the history of customer interactions: it ignores the outstanding opportunity to help better manage the agent workforce that still comprises about 70% of the cost in most contact center operations. We just need to track temporal patterns in combination with cross-channel interaction content and behavior. Predictable timing based on historical statistics can be an extremely valuable input to the forecasting models of your workforce management system and permit better real-time agent scheduling. With better knowledge of the timing and magnitude of future call volumes, contact centers can staff an appropriate number of agents with the skills that will be needed, better balancing the cost of the workforce with the quality of service provided.

Let’s look at some simple examples. In the McKinsey study above, they looked at some rudimentary customer journey analytics for a large retail bank. They found that 45% of customers initiating a webchat ultimately called the contact center. Imagine going the next step in this analysis and determining the delay from webchat to contact center call. That would be really valuable data to inform the WFM system. If a spike were observed in the webchat channel, you could likely count on a corresponding spike in less than an hour in the voice channel. From a staffing perspective, it would be like foretelling the future!

McKinsey also found that 23% of customers that abandoned a web registration ultimately called an agent. This is certainly a simplistic example, but nonetheless, if the number of web registrations were to spike, expect the number of calls into the contact center to spike with a delay and magnitude that can be determined by customer journey analytics. With more sophisticated insight into the journey across specific pages on the website to understand the customer’s thought process, you could more accurately predict whether and when call volumes are likely to change in the contact center for various call types.

In short, there is an unexplored but potentially very valuable synergy between customer journey data (including branch/retail, field, email, mobile/SMS, web, webchat, IVR, social and others) and your workforce management tools. As the science of customer journey analytics becomes more sophisticated, we will see big data from these sources being increasingly used with WFO, for example:

  • Real-time agent staffing and skill demand can be foreseen to some degree by the journey in other channels including social-media, peer-to-peer and self-service
  • Increasing use of text analytics in text-based self-service channels can determine topics for quality management in the voice channel
  • Real-time guidance on the agent desktop regarding next best action should be based on the historical customer journey and interaction content
  • Performance management KPIs should be partially determined by customer journey challenges that must be quickly rectified by the agent
  • Workforce Management can be applied in more branch and retail environments to ensure the availability of the right number and skill sets of employees
  • Back Office workforce process issues can be quickly detected by examining problems in the customer journey such as multiple calls to check case status

It’s a brave new world that will combine customer journey analytics and WFO. Expect to see Aspect continuing to lead the industry in each of these areas individually and as a powerful combination.