As Covid19 accelerates Contact Center transformation, why are so many companies struggling to transform?

“Digital Transformation” is not a new concept. Cost-effective, cloud computing has made digital transformation an increasingly hot initiative since 2013, but success rates have been consistently low, with less than 30% succeeding.

When Covid hit in 2020, everything changed. As the world was thrust into a global pandemic, business verticals were decimated, but a massive catalyst for Digital Transformation was also created, especially in the Contact Center. Businesses were forced to rapidly respond to the crisis and contact centers evolved or shifted practically overnight.

Customer digital interactions increased globally by a massive 60% on average between Dec 2019 to July 2020.

In the span of just 6 months, Covid forced companies to transform their contact centers practically overnight.

Some organizations’ transformative efforts prior to and during the pandemic have been very successful. Many companies continue to struggle though, with how to transform their environment and what it requires. These companies are finding themselves in a perpetual limbo, mid transformation, with changing goals, timetables, and unfulfilled promises. Some are still trying to identify the right technology, vendors, platform, approach, even where to begin.

In this article, we will identify what these challenges are, and how to overcome them.

Contact Center Transformation - By means of migration to the cloud

A common misconception is that simply by moving away from legacy, on-prem based platforms and leveraging a cloud-based contact center platform (CCaaS or CPaaS) equates to CC digital transformation. This often includes other aspects going to the cloud as well, such as storage, compute, peripheral applications, DBs, and data-lakes.

Micro-services architecture and iterative updates, means the solution is constantly evolving, updating and never (rarely) fully down for maintenance or while deploying feature updates and requests to meet customer’s growing, changing needs. This enables Cloud based Contact Center platforms to be supportive of a more responsive Agile or DevOps approach. On the surface this sounds good... and is often a key component to transformation. But it’s incomplete.

Contact Center Transformation - By means of going Omni-Channel

A more comprehensive approach includes understanding that Contact Center transformation includes not only evolving the platform but understanding and applying the evolving needs of the customers and engagement. End users have been shifting away from voice calls for years and adapting to a variety of preferred digital channel formats for interaction, with most Omni-Channel environments offering eight channels on average. These include voice calls, social media, self-service, web chat, visual IVRs, video chat, IOT, personal voice assistants, SMS, co-browsing, and virtual agents. Supporting some to all these channels independently by different dedicated agent queues or cross-training between some queues, but still within a siloed approach, enables a platform to support multi-channel. Most new platforms support a convergence of these channels into one, cohesive multi-threaded channel array called Omni-Channel. Omni-Channel platforms have been around for nearly a decade but began to gain momentum & increase in popularity around the same time digital transformation in the Contact Center have, which really isn’t a surprise given how closely linked the two concepts are.

The largest difference between a multi-channel platform and Omni-Channel, is the latter often forces companies to revisit the customer journey.

Omni-Channel deployment done correctly, means breaking down the silo barriers of individual channels, and leveraging a customer’s multiple interactions in real-time, as a single, cohesive conversation. The benefits are two-fold. From the customer perspective, they can start their journey via one channel (i.e., web chat or chat bot), and if they need to continue the conversation in another channel (i.e., voice or video chat), the journey picks up where the prior channel left off. Virtual agents and real-time transcription and analytics ingest customer context and deliver it to the continuing channel for the agent’s benefit. This mechanism also enables companies to see the entire customer journey from cradle to grave more completely. This leads to overall reduced AHT (Average Handle Time) for agents, while also reducing stress and frustration for the end user and thus creates a more enjoyable experience for both. This approach creates a better mechanism to support more complex customer scenarios and often leads to a higher amount of FCR (First Call Resolution).

One of the leading drivers in Omni-Channel over recent years, has been to increase voice deflection by further empowering end users with self-service capabilities, and creating better IVR or customer interaction experiences. Conversational AI solutions have been at the foreground of this area. By re-visiting the customer journey and modifying the agent and company interactions around the customer needs, companies begin to envelop the meaning of what it means to transform their contact center business. But this is where companies often stop, and herein lies the problem.

To Transform ones’ Contact Center, you must look Beyond the Contact Center Platform itself

Historically, the way businesses often approached LOB needs and solution requests was like this:

1. LOB needs a new solution and submits a request to the IT teams.
2. IT finds or creates a solution to satisfy LOB requirements.
3. IT confirms with the LOB(s) that all feature & solution requests have been met… then
4. IT & LOB work to operationalize the solution before it goes live.

Some companies have tried to apply the same approach to transformation, and this is where it often fails.

So, what is the right way, and what are the 30% of successful companies doing differently to succeed?

To Transform oneself, you must Re-imagine oneself

IT and LOBs stakeholders need to partner and work together, much more closely than in the past. Identify any and everything that’s worked well thus far, the strengths of the current Contact Center, but also all the challenges, pain points and opportunities for improvement. Where to start? Apply a Front to Back approach. Walk through and understand the customer journeys for each LOB and break them down thoroughly. How do customers connect to business today? How could or should they connect if there were no barriers for engagement or technical limitations? Create functional requirements for each of these reimagined customer journeys and convert them into solution requirements.

The shift from customer journey to agent journey

Just as you re-imagine all the ways and manners in which customers could utilize omnichannel to connect to agents, companies need to re-think how their agents are interacting with customers, and all the pre and post call work. How can they leverage solutions such as virtual agents to provide all customer channel interactions in a cohesive stream for the agent? How can real time transcription and analytics assist agents such as use of AI based coaching in real time? Intelligent RPA to automate mundane post call work tasks to reduce AHT of each call during and after the call? As companies focus on improving the journey and interaction for both customers and agents alike, the results are typically happier customers and agents, with shorter AHT, less call abandonment, improved FCR, and better NPS or CSAT scores. Now, we’re beginning to feel the effects of what proper contact center transformation can do. But there’s still more work to be done.

Customer Journeys & Agent Metrics

Popular CCaaS, CPaaS and CAI (Conversational AI) platforms have made significant strides in Real-Time transcription, monitoring, analytics, QA, and agent coaching capabilities; with CAIP (Conversational AI Platforms) emerging as a solution differentiator in this space.

CAIPs are a new breed of layering technology which can be applied to popular on-prem and cloud-based CC platforms. CAIPs focus heavily on using AI & ML to provide customer self-service, actionable insights based on real time STT, and automation for agents. Gartner estimates the value of CAIP revenue to be $2.5 billion in 2020, growing at a pace of 75% year over year.

Older generation call-analytic tools were only capable of providing analysis post call, often up to 1 hour after the call, or even the next day after batches of calls were processed that night. The next generation of these tool performed more real-time transcription and analytic capabilities, and the NLU/NLP components could tag words and context and trigger events or actions such as Fraud alerts while the call was engaged. Todays’ leading real-time tools are context aware, can more accurately identify sentiment & intent, and rely heavily on AI and ML to provide dynamic, adaptive agent-coaching and LOB actionable insights. Companies leveraging such tools have opportunities for incredible depth of understanding and data mining of customers and improve NPS and CSAT scores. LOBs can also optimize WFO and WFM for agent performance metrics and interactions with far more comprehensive analytics than ever before; enabling companies to fine tune agent routing options, keep hold times and average handle times in check and manage more effective and efficient staffing. Companies need to explore how to best take advantage of these tools else their potential become wasted or underutilized.

Addressing the Back End

Once the front end has been tackled, back-end processes and workflow automation must be addressed. Think of a contact center as a bullseye target.

The core Contact Center platform is at the center. This could be on-prem, or in the cloud. Next are outlier components; Call Recording, WFO/WFM, Conversational AI, Fraud Detection, etc. These could be separate components that integrate via API for example, or all be part of one cohesive single-vendor solution.

The next outlier ring are 3rd party applications, systems, DBs and data lakes the Contact Center needs to interact with. These include CRM Integration, ERM and SAP enablement and process optimization, use of intelligent RPA and other means of process & workflow automation. Ensuring claims management is handled more efficiently, including leveraging proactive performance monitoring systems which provide active remediation, and intelligently integrate with and contribute to the claims management systems for automating ticket open/closures.

Only when companies can reimagine how their contact center works, from the customer and agent journeys on the front line, to improving workflow process, automation, and integration on backend, will companies truly reap the rewards of a successful transformation. Their customers and agents will thank them, and their quarterly earnings will reward them.