In recent years, the rapid advance of new data and mobile applications has created a heightened threshold for customer expectations. ASAPP and a suite of forward-looking Chief Experience Officers (CXOs) who represent companies with over $450 billion in market value met to discuss how machine learning (ML), speech recognition, and natural language processing (NLP) are generating higher agent productivity, efficiency, and cost reductions.
Four key AI-centered insights arose from the CXOs who see 2021 as an opportunity to realize the promise of artificial intelligence to radically improve customer experience (CX).
1—Automation creates opportunity for emotive, human-driven service
On the surface, “automation” and “human-driven” seem like two opposing forces. A legacy approach considers automation solely to enable customer self-service, taking human agents out of the customer journey. While self-service will persist in specific applications, automating contact center agents’ repetitive tasks allows a focus on what matters most: providing excellent customer service and representing a brand positively.
AI is opening new avenues to create personalized experiences for customers. With an AI platform, agents know what the customer is facing at a given time, their history with the company, and their communication preferences. Automating their administrative tasks in note-taking and multitasking enables agents to be stronger brand ambassadors in spending more mental energy providing an emotive, high-touch, response to customer needs.
2—AI-driven real-time insights is the next big opportunity for supervisors and coaches
Previously, an in-person presence at call centers afforded managers the ability to monitor and assist agents shoulder-to-shoulder. But in today’s digital workplace, managers have turned to less streamlined methods of using webcam and Slack to support agents. This approach has made it harder for managers to supervise and coach teams, and the introduction of new digital systems has added increasing complexity for front-line agents.
CXOs are beginning to see the promise of ML, NLP, and automatic speech recognition technologies to power live voice transcription. These AI technologies enable managers to supervise and support agents in real-time, guiding agents at the moment they need assistance. After each customer engagement, ML-generated reports and summaries allow managers to digest previous interactions, understand where agents are facing challenges, and improve agent performance. With the AI analyzed data, managers can adjust strategy and coaching in real-time to nimbly respond to the business challenges they face.
In the near future, CXOs expect the confluence of ML, NLP, and automatic speech recognition technologies to provide insight for the next golden opportunity: determining caller intent to more rapidly detect what a caller needs, assess their emotional state, and have them automatically routed to the appropriate agent.
CXOs are excited by the opportunities AI presents. They expect this technology to help their organizations be much more productive and at the same time, differentiate themselves by providing exceptional customer experience.
3—Measure what matters for holistic data-driven decision making
Thanks to the advance of ML, businesses are able scale pattern recognition and automation from their own data. In 2021, the businesses we speak to are going beyond “bean-counting” to unearth correlation-driven insights for strategic business decisions. Outliers and anecdotes are steadily coming together to illustrate, for example, that mobile device users are more willing to have synchronous conversations than desktop users—an insight which may affect routing processes. To detect these patterns, CX teams are looking to ensure that they have individuals with the knowledge to contextualize the data and to build systems to reliably measure it.
However, in the effort to become a digital-first business, building a comprehensive data lake remains a challenge. Businesses are still struggling to compile timely, quality data at a granularity that can be integrated with other data sets. The preservation, and architecture, of legacy systems has led to continued data silos that makes it hard for decision-makers to see the big picture in the customer journey. CX leaders should demand more from their IT teams and service providers to streamline this data to successfully arm businesses and teams to make changes.
And it’s not just technical IT teams who have a responsibility in building this data treasury. All employees have a role in ensuring that the business is flagging data for data driven decision making. The first step begins in making a cultural mind shift to view data as an important corporate asset.
4—Today’s AI and digital technology shouldn’t be used with yesterday’s paradigm
Many of the à la carte solutions found in today’s contact centers were built for a different time. In decades past, businesses relied on outsourcing to balance costs and scale service which often came at the cost of the customer experience. In the 2010s, IVRs and chatbots offered a way to triage workloads but rarely provided a stellar experience for customers. Today, many contact centers are left sustaining a costly myriad of legacy systems that were not designed for a cohesive customer experience. A real transformation to improve customer experiences requires a rethink of how the customer journey operates.
At ASAPP, we’re doing this by putting a focus on making people better with AI. This has meant a change in everything we create from the ground up for vertically integrated AI and human productivity. We’re changing how we measure ourselves, and interact with customers. For example, IVRs and legacy systems may deliver cost savings, but they may actually exacerbate customer frustration. An analogy I like to use when describing this new paradigm for CX is like building a train to fly. Instead of spending the significant and inefficient resourcing to make trains fly, at ASAPP, we’re building an airplane.
Chief Experience Officers are excited by a future driven by AI: making organizations highly productive and effective by augmenting human activity and automating the world’s workflows. I can’t wait to see what new insights we’ll unearth at our next meeting.