How Speech Analytics Helped These Three Contact Centers

WebRTC and cloud felt like the belles of the Enterprise Connect 2013 ball (read about Avaya’s new Collaborative Cloud and involvement in WebRTC here). No matter the clever quips from analyst Sheila McGee-Smith, veteran technologies like contact centers felt a little overshadowed.

Which is a shame to me, for two reasons. Contact centers and how you manage your customers’ experience are only growing in importance. In contrast to some of the hype-ware on display at EC13, innovations such as contact center analytics are delivering in a major way for organizations today.

As part of a panel on social and analytics in the contact center on Thursday, Avaya was capably represented by Tyra Hattersley, a speech analytics engineer who shared several stories about the gains enjoyed by users of our Avaya Speech Analytics. ASA is a fully-integrated solution that provides call recording, search and call text analysis (analytics). It can also work with other vendors’ call recording gear, said Hattersley.

You can download Hattersley’s slide deck here, or just read my summary of the benefits each of these customers enjoyed:

1)Improve employee performance. One customer, a tax agency in the EMEA region, was looking to monitor all of its calls in order to perform a full-scale audit of why residents called and how effective their agents were today, and how they could improve their service. Using ASA, the agency figured out that agents were inadvertently boosting call volume by 30% because they were suggesting residents to call back to check on the status of their requests. Agents were also failing to suggest self-service options such as Web payments to callers. The agency was able to create new policies that cut their inbound calls by 16% and moved another 23% of callers to self-service options such as its improved Web site.

2)Boost revenues. Debt collection is a highly regulated industry. Agents must be precise in their language, not just for legal compliance, but also to maximize their effectiveness. One large debt recovery agency that used ASA was able boost its effectiveness at discovering which agents were incorrectly stating key phrases by 500%. This translated to better “Promise to Pay” rates among debtors, as well as boosted revenue. And it also reduced the number of fines this agency had to pay from agents failing to stick to their scripts.

3)Save money. Another ASA user, an EMEA-based travel retailer, wanted to minimize the cost per customer booking. Its Web site was not performing well – only 60% of travel bookings were completed at the site, below the industry average. As a result, the company was getting 4,500 calls per week related to the Web site, which cost the company an average of $5.05 per call. Using ASA to do a root cause analysis, the company was able to confirm that diverted web bookings was the primary reason why they failed to complete. That led the firm to enhance the right parts of its web site to help customers book their travel online without phone assistance. That slashed the number of expensive calls to its agents.

Related Articles:

Next-Generation IT: What Does It Really Look Like?

From mainframes to virtualization to the IoT, we’ve come a long way in a very short amount of time in terms of networking, OS and applications. All this progress has led us to an inflection point of digital business innovation; a critical time in history where, as Gartner puts it best, enterprises must “recognize, prioritize and respond at the speed of digital change.” Despite this, however, many businesses still rely on legacy systems that prevent them from growing and thriving. So, what’s the deal?

I attempted to answer this in a previous blog, where I laid out as entirely as I could the evolution of interconnectivity leading up to today. What was ultimately concluded in that blog is that we have reached a point where we can finally eliminate dependency on legacy hardware and hierarchical architecture with the use of one single, next-generation software platform. The call for organizations across all industries to migrate from legacy hardware has never been stronger, and the good news is that technology has evolved to a point where they can now effectively do so.

This concept of a “next-generation platform,” however, isn’t as simple as it sounds. Just consider its many variations among industry analysts. McKinsey & Company, for example, refers to this kind of platform as “next-generation infrastructure” (NGI). Gartner, meanwhile, describes it as the “New Digital Platform.” We’re seeing market leaders emphasizing the importance of investing in a next-generation platform, yet many businesses still wonder what the technology actually looks like.

To help make it clearer, Avaya took a comparative look at top analyst definitions and broke them down into five key areas of focus for businesses industry-wide: 

  1. Next-generation IT
  2. The Internet of Things (IoT)
  3. Artificial intelligence (AI)/automation
  4. Open ecosystem
  5. The customer/citizens experience

In a series of upcoming blogs, I’ll be walking through these five pillars of a next-generation platform, outlining what they mean and how they affect businesses across every sector. So, let’s get started with the first of these: next-generation IT.

Simplifying Next-Gen IT

As IT leaders face unrelenting pressure to elevate their infrastructure, next-generation IT has emerged as a way to enable advanced new capabilities and support ever-growing business needs. But what does it consist of? Well, many things. The way we see it, however, next-generation IT is defined by four core elements: secure mobility, any-cloud deployment (more software), omnichannel and big data analytics—all of which are supported by a next-generation platform built on open communications architecture.

Secure mobility: Most digital growth today stems from mobile usage. Just consider that mobile now represents 65% of all digital media time, with the majority of traffic for over 75% of digital content—health information, news, retail, sports—coming from mobile devices. Without question, the ability to deliver a secure mobile customer/citizen experience must be part of every organizational DNA. This means enabling customers to securely consume mobile services anytime, anywhere and however desired with no physical connectivity limitations. Whether they’re on a corporate campus connected to a dedicated WLAN, at Starbucks connected to a Wi-Fi hotspot, or on the road paired to a Bluetooth device though cellular connectivity, the connection must always be seamless and secure. Businesses must start intelligently combining carrier wireless technology with next-generation Wi-Fi infrastructure to make service consumption more secure and mobile-minded with seamless hand-off between the two technologies.

Any-cloud deployment: Consumers should be able to seamlessly deploy any application or service as part of any cloud deployment model (hybrid, public or private). To enable this, businesses must sufficiently meet today’s requirements for any-to-any communication. As I discussed in my previous blog, the days of nodal configuration and virtualization are a thing of the past; any-to-any communications have won the battle. A next-generation platform built on open communications architecture is integrated, agile, and future-proof enough to effectively and securely support a services-based ecosystem. Of course, the transition towards software services is highly desirable but remember not all hardware will disappear—although where possible it should definitely be considered. This services-based design is the underlying force of many of today’s greatest digital developments (smart cars, smart cities). It’s what allows organizations across every sector to deliver the most value possible to end-users.

Omnichannel: All communication and/or collaboration platforms must be omnichannel enabled. This is not to be confused with multi-channel. Whereas the latter represents a siloed, metric-driven approach to service, the former is inherently designed to provide a 360-degree customer view, supporting the foundation of true engagement. An omnichannel approach also supports businesses with the contextual and situational awareness needed to drive anticipatory engagement at the individual account level. This means knowing that a customer has been on your website for the last 15 minutes looking at a specific product of yours, which they inquired about during a live chat session with an agent two weeks ago. This kind of contextual data needs to be brought into the picture to add value and enhance the experience of whom you service, regardless of where the interaction first started.

Big data analytics: It’s imperative that you strategically use the contextual data within your organization to compete based on the CX. A huge part of next-generation IT involves seamlessly leveraging multiple databases and analytics capabilities to transform business outcomes (and ultimately, customers’ lives). This means finally breaking siloes to tap into the explosive amount of data—structured and unstructured, historical and real-time—at your disposal. Just as importantly, this means employees being able to openly share, track, and collect data across various teams, processes, and customer touch points. This level of data visibility means a hotel being able to see that a guest’s flight got delayed, enabling the on-duty manager to let that customer know that his or her reservation will be held. It means a bank being able to push out money management tips to a customer after seeing that the individual’s last five interactions were related to account spending.

These four components are critical to next-generation IT as part of a next-generation digital platform. Organizations must start looking at each of these components if they wish to compete based on the CX and respond at the speed of digital change. Stay tuned, next we’ll be talking about the ever-growing Internet of Things!

Avaya Predictions for 2017 Services Trends: Top Focus is on Smart Customer-Centric Engagement

Recently, we asked six Avaya services experts to help us reflect on the past year and to peer ahead into 2017. Our panel:

  • Richard English, Managing Director, Avaya Professional Services
  • Camille Lewis, Product Management Director, Avaya Client Services
  • Barbara Sidari, Customer Engagement and Executive Cadence, Avaya Client Services
  • Thomas Brennan, Vice President of global support services, private cloud and managed services delivery
  • Michael Sale, Director Online Engagement, Avaya Client Services
  • Dan Pratt, Senior Director, Business Transformation and Strategy, Avaya Client Services

According to our six experts, our predictions for these 2016 trends proved to be spot on—and they will continue to be a force in 2017:

  • Use of hybrid/private cloud

    will continue to dominate for large enterprises until public cloud providers can demonstrate that compliance to privacy/security regulations such as HIPAA can be achieved. However, Public Cloud is quickly becoming a flexible and effective delivery model for the midmarket.

  • A flexible delivery model

    to achieve growth in modular steps that helps IT maximize ROI and support rapid business scaling has been, and will continue to be, extremely successful. Taking some of the burden off the enterprise enables IT managers to focus on more strategic corporate initiatives.

  • The need for person-to-person human touch

    will continue to rise. It will become critical in 2017 as unassisted support and self-healing systems grow smarter in identifying trends and problems before they happen and engage in machine-to-machine maintenance for resolution. The use of video will be more widely used, providing personalization and higher customer satisfaction.

The panel thinks that 2017 will mean an increasing focus on smart customer centric engagement when it comes to service. In 2017, it’s all about using analytics and even smarter technology to increase customer satisfaction (CSAT) scores, loyalty and revenue—and to achieve a better return on investment.

The Avaya panel sees these three trends emerging in 2017:

  • Transforming legacy systems and increased customer use of omnichannel will streamline the customer journey to increase customer satisfaction, loyalty and revenue.

    For example, many retailers will transform their Contact Centers into profit centers. The shopping experience for their customers starts on the mobile device or web-based applications—retailers want it to end with an order placed. The customer will experience a seamless transition from mobile to voice (or to web chat or video) without having to repeat who they are and what they want to purchase. The agent will already know the value of the customer to their company and will provide a personalized shopping experience.

  • Analytics, Internet of Things (IoT), and big data will enhance the experience of the Customer Journey.

    The predictive and preemptive active workflow will match people to people, machine to machine, as preferred by the customer for maximum satisfaction and profit. For instance, service vendors will use data captured from customer service requests, alarms, outage history, and project volume to identify risks and take appropriate actions to proactively mitigate issues. Utility companies can leverage web-based applications to proactively communicate to customers the status of affected service areas via maps on smart phones, reducing the burden of customers calling the service center to report an outage. Similarly alarm companies will analyze alarms and preemptively fix them before the consumer arrives home.

  • Demand for holistic application service management will grow as siloed and disparate cloud applications shift focus from managing assets in the field to delivering on business processes.

    Enterprises will need a dashboard that provides a single pane view by business process vs CPU performance. The workforce needs to be trained to leverage all the data in a way that includes human touch.

The year 2017 promises to be very exciting as service transforms and demonstrates its value by preemptively fixing issues before they become problems. It is imperative that knowing the customer and providing what they want, as well as the human touch, will become ever more critical in a big data world. After all, it’s all about the customer experience!

What do you see emerging in 2017? Drop me a note at sithomso@avaya.com

Leveraging Big Data to Fine Tune Customer Experiences

Whether you realize it or not, big data is at the heart of practically everything we do today. Billboard companies, for example, are now leveraging eye tracking and traffic pattern analysis to gauge interest among drivers. Chances are one of those drivers owns a 4G-enabled vehicle that can track such things as performance and maintenance history. That person can also now record and analyze their utility usage via smart home solutions—anywhere, anytime. On a more critical level, doctors can now record and analyze patients’ heartbeats and breathing patterns to develop life-saving predictive algorithms.

In today’s smart, digital world, big data has opened the floodgates to never-before-seen possibilities. It has the power to course-correct potentially devastating outcomes, and it’s become a necessity for continually refining the customer experience. If you ask us, though, the best customer experiences today are supported by customer journey analytics.

The Need for Customer Journey Analytics

Customer journey analytics is a process that requires tracking and analyzing the way customers use a combination of available channels to interact with an organization. These channels range from human interaction (like speaking with a contact center agent) to fully automated interactions to assisted service (like live chat and co-browsing).

The need for customer journey analytics is simple: data solutions of the past simply won’t meet the next-generation customer needs of today and the future. Consider that just 10 years ago, channels like Web chat and social media were in their infancy (Facebook had only been around for two years). At the same time, the world’s first smartphone had only been on the market for one year. A lot has happened to transform the customer experience in a very short amount of time. As companies move forward in today’s age of rapid tech innovation, they must be armed with the right data strategy.

As mentioned, customers today use a vast number of channels and devices to interact with the brands they love. Each channel and device offers its own set of diverse scenarios for linking to other channels and devices, making no two customer experiences the same. Companies must be able to understand customers’ actions on any given channel or device in order to infer insights and create anticipatory engagement at the individual account level. For instance, why did one customer choose to purchase a product in a retail store verses online? Or, why did a customer end a live chat session before his or her inquiry was handled?

This level of understanding requires a comprehensive view of the data gathered from all channels and interactions that proceeded the moment in question. Customer journey analytics is a process designed to provide this comprehensive view and deliver deep benefits organization-wide—so much so that 60% of all large organizations are expected to develop customer journey mapping capabilities by 2018, according to Gartner.

Making Customer Journey Analytics Work for You

Companies need a data-driven customer approach to survive—and it needs to be effective to thrive. Many companies, however, struggle with taking their customer data and turning it into actionable results. In fact, a 2015 study conducted by PwC found that 43% of companies obtain little tangible benefit from their data, while 23% derive no benefit whatsoever.

To effectively apply your data, you must first determine what you wish to achieve with your data in the first place. In other words, what key objectives do you hope to achieve or improve upon by using big data (or specifically, customer journey analytics)?

Not sure? Here are four core initiatives to start you on a path to maximize your customer journey analysis efforts:

  1. Enable self-service.

    Self-service options—especially mobile—are rapidly increasing in popularity. Just consider that in 2015, Apple users downloaded over 51,000 mobile apps per minute. Also last year, 90% of customers used their smartphones in stores to make price comparisons, research specific products, and check online reviews.

    In today’s mobile-first world, businesses should leverage customer journey analytics to develop a sophisticated and integrated mobile experience—one that seamlessly integrates self service into their mobile app via visual, in-app self-service options. Conversely, this experience should offer customers callback options (either immediate or scheduled), as well as mobile chat (automated or agent-assisted) and video service. In addition to offering a stellar mobile UX, businesses should ensure backend capabilities that intelligently route customers to agents based on available context in order to drive relevant, meaningful interactions.

  2. Improve resource matching. We live in a world today where cars can park themselves and doctors can 3D print new organs, yet we still struggle with routing callers to the right subject matter experts. The time for next-generation routing is now, and it all starts with improved resource matching—specifically, attribute-based matching. This means matching customers with agents based on rich context, business KPIs, and organizational goals across all work items, channels, and resources to drive segmentation, increase prioritization, and determine the best course of action per customer.

    This also means choosing the right resources for each customer, regardless of where the resources reside within the organization. The right subject matter expert, for example, could be a contact center agent, a supervisor in your billing department, or your VP of sales. Customer journey analytics provides a 360-degree view of available resources organization-wide to support this level of attribute-based matching.

  3. Increase agent awareness. Not only is it important to collect the right information, but it must also be presented in a way that is visually understandable and easily accessible for agents. Imagine, for example, an agent being able to see where a customer has been on the company’s website over the last month, as well as that person’s live chat interactions last week. Imagine an agent being able to quickly see that a customer sent an email two days ago regarding a recent bill, or reached out via SMS because the company’s mobile app wasn’t working properly. Imagine if agents could gain this 360-degree, comprehensive view all in just one or two clicks of a mouse.

    Data is continuously generated in different ways, and is consumed by different people across different processes and applications. Having the right information at the right time empowers agents to focus on customers’ needs without having to ask for the same information multiple times (which, as we all know, is one of today’s greatest customer frustrations).

  4. Ensure continuous improvement.

    When it comes to big data, businesses can’t manage what they can’t measure. Therefore, it’s important that companies measure their data both in real-time and historically to help improve systems, processes, and applications over time. This is what will enable them to consistently deliver on key business objectives, operate within budget, and maximize every customer experience. Here are four key technologies for ensuring continuous improvement:

    • A data collector that can collect, standardize and normalize raw data across any data source so it can be used for enterprise-wide reporting and analytics.
    • A processing engine that can correlate, translate, calculate and publish normalized data into meaningful business measures.
    • A visual presentation platform that provides unified, real-time and historical reporting and analytics dashboards that can be used to visualize, analyze and explore key business measures.
    • Predictive analytics to discover new trends, apply changes based on insights, and continuously improve applications, workflows, self service and routing decisions.

So, how can you succeed with these four objectives to fine tune your customer experiences? That’s an entirely new discussion—however, we can tell you this: invest in a customer engagement platform that:

  • Provides a single view of customer interactions across all systems
  • Allows you to add data sources quickly
  • Can correlate data across both real-time and historical systems
  • Boasts an open and extensible reporting and analytics framework

Experience is everything. Learn How Avaya Oceana Works.