The 5 Most Important Customer Service Technology Solutions – as Scored by the Users

When Technology is both Panacea and Pitfall

For the Customer Service Excellence research program, we wanted to identify the most essential customer support applications. So, we first measured technology adoption. That is what contact or call center software applications were most used.

There's no shortage of contact center software. So we were less interested in publishing a voluminous list of systems and more interested in identifying which of them are the most effective. So, we then asked survey participants to rate each application (on a 10-point scale) in terms of effectiveness. For those technologies rated above a score of 8 we asked why they were effective. For those scored below 7 we asked why they were ineffective.

The data delivered some unexpected results. Most customer support applications were rated as both effective and ineffective by large numbers of participants. Even those applications with the highest scores had large numbers of low scores and vice versa. This suggests that most systems could be effective or ineffective depending on how they are used. We broke down the top five contact center technology rankings based by archetype.

Top 5 Customer Service Technology Solutions

Research shows the top 5 customer service technology solutions as scored by users.

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Below are some additional insights for each of the top cited customer service technology solutions.


Customer Relationship Management Software

CRM software is the customer system of record. Its primary contact center function is case management automation. But most CRM systems also offer Voice of the Customer, omnichannel engagement, customer self-service, business intelligence and much more.

The Best-in-Class described their customer service CRM system as mission critical and essential to their work. Several suggested they couldn't do their jobs without it. Many Medians and Laggards described CRM as an administrative burden, designed more for manual data entry than automation. For these later agents, the application hindered their performance more than it helped.

We know from a wide body of knowledge and over three decades of experience that CRM is adopted when it serves agents and customers, and not just management. We know the top factors for CRM adoption are ease of use, an intuitive user interface, a rewarding user experience, process automation and contextually delivered business intelligence.

When CRM software raises staff productivity and performance goals it is wildly successful. However, if it is just a data entry system so management can report on daily work activities, then agents realize few benefits, wide scale adoption is challenged, and ROI is anemic.


Call Routing and Telephony Technologies

A good onramp starts the customer service journey right. That happens when call routing software quickly transfers customers to an agent suited to resolve their issue. The agent is then greeted with a screen pop showing the customer provided information as well as the customer 360 degree view. This solution contributes to the goals of increasing customer satisfaction while at the same time contributing to call center imperatives for higher efficiency and lower cost to serve.

Call routing systems place incoming calls in queues and forward them to an agent based on defined rules. Efficient and optimized call routing is built on a combination of the right methods and technologies.

Call routing methods use rules-based decision engines or algorithms to route each caller to the best customer service representative. Call routing technologies manage the interaction between the telephone network and the agent's desktop. When call centers apply the best combinations of call routing methods and technologies, they increase agent productivity by 5 to 7% and lower contact center costs by 2 to 4%.


Customer Self Service

Most customers now prefer to access self-service channels as their first point of contact for many types of questions or cases. Most contact centers are responding with self-service support channels designed to automate high volume, low-complexity cases. The result is a win-win for customers and support organizations.

Achieving self-service success starts by using the right tool for the job. The four most used self-service applications are FAQs, knowledgebases, chatbots and communities.

Customer Self Service Topology

The challenge with customer self-service technologies, as shown by the differences between the Best-in-Class and their lower performing peers, is getting self-service right; a determination made by customers.

Self-service apps satisfy customers when they are purpose built for specific customer support scenarios and deliver a rewarding user experience. The user experience is most often built with social technologies and user-centered design.

Customer self-service systems fail when they are more interested in reducing costs than satisfying customers and not maintained or kept current. In fact, keeping self-service channels up to date is the biggest ongoing challenge. If customers can't quickly find what they are looking for or if they must sift through volumes of irrelevant or obsolete content the self-service effort fails.


Contact Center Analytics

Call center analytics include dashboards, information reporting, speech and text analytics. The Best-in-Class leaders show that call center analytics are most successful when they are designed to connect data, insights and action to improve agent, customer and business outcomes.

While the Best-in-Class operators cited analytics as their top tool for continuous process improvements, their lower performing peers were more often data rich but information poor. To their credit, the underperformers understood the value of data but struggled to transform it into actionable intelligence.

The research found analytics were rated effective when they focused on the most important measures and delivered actionable insights to agents and managers that would otherwise never have been unearthed. They also delivered more value when they included insights to improve customer interactions and relationships, and were not just focused on operational cost savings objectives.


Artificial Intelligence

AI adds value to most other support systems. It makes call routing more efficient, case resolution more timely, chatbots more conversant, customer sentiment more detectable and analytics more predictive.

AI works best when connected with agents. It aids agent productivity with guided service fulfillment, next-best-action recommendations, suggested knowledgebase articles, case resolution responses and personalized offers. It can even suggest how to use customer data to deliver differentiated customer experiences.

It can measure trends, forecast staffing requirements and enable proactive customer support by identifying customer problems before they occur.

AI for Customer Service

Among the Best-in-Class cohort, AI was described as a game changer and driver of continuous improvements. Contact center leaders are using AI-infused software to personalize customer engagement, deliver faster resolutions, lower cost to serve, increase customer satisfaction and scale customer support operations. It's an overarching and underlying technology that delivers an improved agent experience, better customer satisfaction and lower labor costs.

Popular CRM systems such as Microsoft Dynamics 365 with its Azure Machine Learning and Salesforce with its Einstein have removed technical barriers and put AI capabilities into the hands of business analysts and power users.