Cloud and Analytics will be Contact Center Focus for 2020

 

Published: March 2020

"At Cisco, we strive to use the latest engagement technology to transform our customers’ experience,” says Colin Choo, Cisco IT Contact Center Solutions Consultant & Strategy Lead. For our contact centers in 2020, this effort will mean a big focus on data analytics, artificial intelligence, and machine learning (AI/ML) for our Virtual Demand Center. We will also take the first steps to migrate our own Cisco Contact Center platform deployment to the cloud. Here’s a view into our vision and plan for this year.

Cognitive Collaboration to Improve Customer Experience

A key part of this companywide initiative to improve CX is bringing all customer data together into a single “collection” of connected sources of truth, including the data that exists in our contact centers. “With information accessible in one place, we will be better able to serve customers with greater accuracy, efficiency, and relevance,” says Mary Mazon, Cisco IT manager. “Consolidated customer data also makes it easier to run analytics to gain insights for business, operational, and CX improvements."

When we combine insightful data with AI and ML, we can begin to weave context and intelligence throughout the entire customer journey, transforming our customer experiences to be more personalized and proactive. Cisco calls this the cognitive contact center.

We will explore how to enhance this experience with insights gained from the customer journey mapping and predictive analytics solutions offered by Cisco Webex Experience Management (formerly CloudCherry, recently acquired by Cisco). This solution helps contact centers improve customer interactions by giving agents full visibility into customer feedback, metrics, and previous experiences.

Figure 1. Example Webex Experience Management Dashboard

 

Through our partnership with Verint, the Virtual Demand Center is already benefitting from interaction analytics by generating additional sales contacts. In this case, our agents proactively reach out to customers who have been identified as being interested in a Cisco solution, but who haven’t yet communicated with a Cisco salesperson or channel partner.

As AI/ML and natural language understanding (NLU) capabilities continue to mature, we will be able to offer a conversational interactive voice response (IVR) feature with Cisco’s Unified Contact Center Enterprise (UCCE) Release 12.5. “This feature is made possible by Cisco’s partnership with Google, which allows us to tap into Google’s powerful Cloud Contact Center AI platform,” explains Choo.

Imagine calling into a customer helpline and instead of going through a tedious series of questions, you are greeted by name, followed by an open-ended question: “How may I help you?” The intelligent virtual agent is a direct means for self-service and, when required, connects you to the most appropriate agent based on algorithms that take into consideration all the information captured from your natural conversation with the virtual agent.

Figure 2: Conversational IVR serves callers faster than a menu-based interaction

 

The Cisco Enterprise Voice Assistant (EVA), powered by Voicea, another recent Cisco acquisition, adds to our NLU toolset. EVA can transcribe an agent’s call with the customer. After the call, the transcription is available to the agent for extracting notes to close or follow up on the case. In addition, these transcriptions can be fed into analytics solutions to produce valuable business insight.

Our Cloud Migration Begins

Today, we own our on-premises Unified Contact Center Enterprise (UCCE) infrastructure, which spans six geographical locations and serves more than 6,700 agents distributed across nearly 30 locations. This infrastructure supports all Cisco business functions, including sales, marketing, partner services, employee experience, and technical support.

In 2020, we will begin migrating select contact center groups to Webex Contact Center, Cisco’s native-cloud-based contact center solution. “This solution creates a single, global instance in the cloud to route customer interactions and will give us more flexibility to respond quickly to changing business and operational needs,” explains Mazon.

In the initial migration phase, we will choose smaller, specialized contact centers to learn best practices for migrating other locations in the future. We also expect to route contact center calls between groups on Webex Contact Center and UCCE-based contact centers, which will help us learn how to operate effectively in a hybrid on-premises/cloud environment.

"We expect this hybrid environment to remain in place for two or three years as Cisco continues to enhance the intelligent routing features in Webex Contact Center,” says Choo. During this time, contact centers on UCCE can also take advantage of the cloud-based Customer Journey Analyzer analytics and reporting solution, which was previously offered only with Webex Contact Center.

Figure 3: Cloud-Premises Hybrid Architecture for Cisco contact center

 

"Once our Webex Contact Center environment is in full production mode, we will be able to deploy new contact center locations rapidly,” says Choo. “Currently, it can take as long as 12 months to design, order, and install the necessary circuits and equipment in an on-premises environment. In the cloud, we expect to complete this effort in a matter of days.” Our UCCE platform will still host the larger part of our contact center agents, depending on specific use cases and size of the contact center.

Reaching the Value Point

Cloud, AI, analytics--these technologies have been buzzwords in the contact center industry for some time. But, only in the last couple of years have they reached a level of maturity that delivers practical and tangible business value. At the Cisco Virtual Demand Center, we see 2020 as the year that we start to build momentum in adopting these Cisco technologies. And, we expect to discover new use cases and benefits that will help propel Cisco’s customer and employee experiences to the next level.

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