In the costly world of customer experience management, companies are constantly pushing the boundaries to encourage and empower customers to embrace self-service. Why? Because “it’s great for everyone”, or so the narrative goes.
With self-service, the customer is able to resolve issues themselves with little effort, companies’ service costs are considerably reduced, and customer satisfaction increases with knock-on benefits to loyalty and profitability. However, with self-service increasingly eliminating simpler contacts, the interactions that contact center associates do handle tend to become more complex over time, often requiring greater investigation, more troubleshooting, and higher skills, all of which come at a greater cost.
As service palettes and features become more extensive and complex, successful resolution of these more complex contacts requires extensive knowledge of a number of factors, including systems, changing business rules, exceptions, troubleshooting steps, and navigation of knowledge bases, many of which have been developed over time, with usability taking second place to information proliferation.
Which Technologies Are Ready for Today’s Contact Center Challenges?
Emerging technologies, such as AI and chatbot technologies hold great promise in this area but are not yet fully mature. They also introduce the additional challenge of finding the right balance between virtual engagement for transactional contacts — such as billing inquiries or duplicate statements — and more personal customer engagements for complex situations and more valuable customers.
These challenges are heightened for nearshore and offshore contact center operators, where it can be tough to replicate the nuanced touch and feel for complex product propositions that come more easily to onshore agents, who quite often are customers of the services they support day in and day out.
For these reasons, many companies are increasingly relying on Dynamic Decisions Trees (DDTs) as powerful tools to deliver better customer experience, lower operational cost, and help customer service associates resolve complex issues.
DDTs are not new. In fact as far back as July 1964, the Harvard Business Review published an article on the emerging use of decision trees as a new technology, leveraging its application in decision making in capital investment for a chemicals company, Stygian Chemicals Management.
Fast forward 54 years and we see an explosion of smart decision tree applications built alongside knowledge management tools, designed to help customer service associates navigate through complex processes, determining the next steps based on customer responses.
Associates select the appropriate decision tree based on the customer profile and call reason and are presented with the questions/troubleshooting steps in the optimal order. Responses are not only used to determine the right next steps for customer resolution but are also summarized and populated within the comments section of the CRM tool, ensuring accurate contact history capture.
Decision trees are also now commonly being used in development of virtual agent chat solutions, or botshore as one BPO player recently termed the concept.
The DDT Impact within the Contact Center
Industry providers are working hard to develop ever more effective DDTs enabling customer service associates to resolve issues at the first attempt, with minimum customer effort, to generate the highest levels of customer satisfaction.
And their effectiveness is striking, especially in environments where speed to competency and early lifecycle associate attrition are critical factors impacting first call resolution (FCR).
Analysis of FCR performance for one major cable provider has shown that that deployment of decision trees for complex troubleshooting and repair call results can result in FCR significantly higher than similar calls where agents did not use decision trees, with repeat calls falling by as much as two-thirds in certain cases.
The customer satisfaction and cost benefits are obvious, with research revealing a strong correlation between low voice of the customer (VOC) scores and contacts where decision trees are not used, or a wrong decision tree was selected.
The benefit of decision trees on speed to proficiency for new customer service associates is also striking. One major BPO has been able to reduce time to proficiency by 30% when decision trees were introduced in training and consistently used in early stage production by new associates.
As the customer service world continues to evolve, the demand for human interactions for higher complexity interactions, at the lowest possible cost will continue to intensify. The increased deployment of AI and virtual agent solutions will only intensify the demand for very high quality interactions for those contacts where human interaction remains the best alternative. This presents both a challenge and an opportunity for nearshore contact centers, which are well placed to deliver on both quality and cost.
Indeed the fusion of nearshore associate skills with decision enabling technologies and outcome analytics are a potent elixir that it is difficult to ignore.