Harnessing CX Automation for Elevated Experiences

Executive Summary

Contact centers typically operate at the extreme edge of capacity, balancing customer expectations against the imperative to control costs. Bridging this capacity gap has historically proven elusive for operations teams, often forcing compromises in either service quality or agent performance, until artificial intelligence (AI) emerged as a genuine business tool. To efficiently enhance the customer experience (CX), centers need to automate—and quickly. For the first time, extensive automation is achievable without wholesale disruption. AI makes it possible to create consistent, reliably excellent customer experiences.

Automation Lags in Contact Centers

Automation is difficult—and rare—in contact centers. Despite the common perception of centers as assembly lines for customer interactions, most processes still rely on people following scripts, guidelines and prompts to move inquiries along. Processes are designed with speed and completion in mind rather than a focus on encouraging positive outcomes.

There is a pervasive presence of legacy technology, which stands apart from other software in an enterprise technology stack. Centers have long had separate data and communication platforms, with silos baked into many processes and data resources that have been hard to break down. In some cases, early attempts to increase automation have actually resulted in degrading CX (in the form of lower customer satisfaction measures) rather than improving it. An example is the entire history of interactive voice response, followed by the first generation of conversational chatbots (pre-AI) that made consumers angry rather than satisfied.

Interactions are becoming more complex, thanks to myriad consumer channel choices that make it harder to design processes. Similar requests can take vastly different pathways and are often entwined with multiple requests or inquiries in a single interaction.

Self-service has improved, adding a positive level of automation to the front end of many centers. Receptivity to this technology reflects Ventana Research’s assertion that by 2027, 60% of customer interactions will be fully captured and resolved within automated self-service channels, expanding to three-quarters by 2030. The software helps smooth the process of informing agents of the customer’s current status once the interaction breaks through from self-service to the agent’s handling.

However, when a customer request cannot be contained within self-service, it is difficult to design processes that cover all eventualities. Issues that cannot be handled by machines are harder for people to untangle and require more judgment in the moment.

There is also resistance to change fueled by costs and the perceived immediacy of the center’s goals. Because service is viewed as a cost center rather than a revenue generator, enterprises are conservative when it comes to adopting leading-edge technology tools. This binds CX organizations with resource constraints. And finally, there is a focus on immediacy rather than long-term planning. A strategic and tactical divide isolates contact center leadership from other CX stakeholders. Service teams focus on swift resolution: closing issues at maximum speed. Contrast this with marketing and sales teams that are starting to view contact center interactions as opportunities to grow business and revenue. These views are in tension.

Automation Matters to Brands

In today’s market, managers cannot hire their way out of the problem.

Contact centers consistently struggle with the imperative to elevate CX outcomes under resource constraints. In today’s market, managers cannot hire their way out of the problem. Hiring is constrained by cost, but also the scarcity of skilled workers and the time it takes to get people ready to face customers. It is also unrealistic to expect to squeeze more productivity from existing staff. These concerns challenge enterprise goals for protecting the brand image and using customer experiences to extend the brand’s reach.

AI has emerged as the solution. Bots that augment workflow processes for humans make workers more productive alongside automated systems, reducing the workload. Using automation in this way doubles the benefit—creating new efficiencies while also increasing labor capacity.

As technologies converge across the enterprise, wide utility makes it more likely that an interdepartmental consensus will support automating processes more broadly. Examples include:

• AI and generative AI can have a transformative effect on efficiency across an organization. The delivery of automatic summaries for post-call work or issue handover and real-time knowledge suggestion for issue handling have a genuine impact in the contact center. The positive results can also be seen in marketing and sales efforts, as well as in analytics and back-office processes.
• Omnichannel and digital engagement, responding to consumers who expect to be able to engage with businesses across a diverse range of channels and modes. Technology for digital engagement boosts self-service through containment without escalation to an agent while also providing data for analysis of customer intent and behavior.
• Workflow automation to infuse AI into enterprise and contact center platforms for easier and speedier task completion. Workflows automate processes that eat up labor resources—such as transaction processing, appointment scheduling, tracking shipments and fulfillment.

From a brand perspective, elevating CX should not just be about reducing call times or increasing containment. There must be a wider aim that focuses on the whole enterprise. Achieving CX automation by injecting AI into business processes and connecting data across departments improves outcomes in the contact center and beyond.

Automation Starts with an Open Platform

Today’s automation needs AI, and the most effective route to AI is to instill it at the platform layer of the stack rather than one-off in each application.

Today’s automation needs AI, and the most effective route to AI is to instill it at the platform layer of the stack rather than one-off in each application. The platform is the foundation of all apps atop it, making it critical to structure it around data and AI at the core. If AI operates at the platform level, an enterprise can automate large portions of—or, in some cases, the entire—customer life cycle instead of the isolated components.

An open platform offers a high degree of customization, expansive integration capabilities and access to application programming interfaces. This creates a flexible environment to use AI to solve the most pressing problems. It also allows the choice of preferred applications rather than forcing a disruptive, wholesale tech transformation, making changes in applications downstream more tolerable.

Open platforms allow for mixed on-premises and cloud environments, facilitating access to the latest AI-based applications. Additionally, enterprises can use the best, most relevant commercial open-source or proprietary models for any task or process. This flexibility ensures an enterprise remains at the leading edge of available, fast-moving AI technology, enabling contact centers to be as “future-proof” as possible.

Automation Enables Speed and Agility

Through automation, enterprises minimize the gap between what they need to do and the available capacity to do it. An open architecture approach is arguably the best way to integrate human and automated labor. Using existing processes, now automated and faster, enable an enterprise to expand worker capabilities without adding costs. There is less learning and change for agents, leading to a faster time-to-value for AI application deployment.

Special-purpose automation applications – bots – can be deployed quickly and trained continuously on real-time behavioral data that moves through the platform’s data hub. The result is a de facto dissolution of existing silos without necessarily replacing apps or overhauling existing processes. The processes that already work are simply automated.

Especially on the front end, automation allows for innovative impact on telephony provisioning and interaction routing. Enterprises have a choice of existing telephony (“bring your own telephony”), taking on cloud routing or other options. Calls can be passed among or between channels, people or bots, depending on the context.

In the past, routing was almost exclusively focused on efficient and timely interaction handling. Now, it’s also about finding moments of leverage to boost loyalty or spending. Automation tools can use context to make smarter decisions about the optimal pathway or routing choice, producing more pathways for each interaction. For example, context is useful in making intelligent routing decisions such as:

• Based on history, should this interaction be routed to an agent skilled in retaining canceling customers?
• Does the context around a customer’s bot interaction suggest a particular agent experienced in this area or a targeted upsell?
• Can the issue be routed to an intelligent virtual agent (IVA) and enable self-service without escalation to an agent?

CX Automation is Strategic

Improvements in CSAT, first contact resolution, loyalty or lifetime value have repercussions on corporate growth and revenue.

Even if the CX organization confines changes to the contact center or front end, enhancements are still beneficial to the entire enterprise. Improvements in CSAT, first contact resolution, loyalty or lifetime value have repercussions on corporate growth and revenue.

Making an automation platform “open” enables an organization to connect sales, marketing and service teams across the enterprise, linking them to processes that spur orchestration of desired interactions and outcomes. Adding flexibility by automating interactions and workflows improves total time to value and ROI from the broader aspects of the platform, spreading the benefits among multiple departments and cost centers. Viable cost-saving scenarios include automated summarization and reduced after-call work; self-service containment; and post-interaction workflows between service operations and the back office.

Automating Reliably Excellent Customer Experiences

CX automation can optimize operations in pursuit of better customer outcomes. These outcomes are both tactical and strategic, letting an enterprise optimize and orchestrate interactions for growth, revenue or other metrics while simultaneously controlling costs. It is a true “doing more with less” approach through streamlined operations. The result is a consistent and repeatable model for excellence, where high-quality customer experiences become the norm, not an exception or even a goal.