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.

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A Secret Weapon: See the Full Potential of AI for Your Next-Gen CX

If I were to ask how often you engage with a form of artificial intelligence (AI), what would you say? Now, what if I told you that not only do you engage with AI more than you think, but you’ll rely on it more than traditional phone service five years from now? Would you agree, or think I’m plain crazy?

Before you form an opinion, consider the reality in which we live. It’s commonplace to engage with AI-enabled virtual assistants like Apple’s Siri or Microsoft’s Cortana. In fact, if you own an iPhone, you’re likely part of the 98% majority who has at least tried Siri. By 2020, more than a quarter billion consumers will be operating connected vehicles that can autonomously drive, park and change lanes. This year, it’s expected that 50 AI-enabled devices (like Amazon Echo) will be shipped per minute.

Overall, top analyst firms like Gartner and Forrester expect AI, driven by intelligent analytics, to reshape the CX more than any other technology over the next five years. With the rapid pace of innovation, this trajectory could very well mean the near-extinction of traditional phones. Consider that assisted/automated service is already practically head-to-head with traditional phones in terms of usage. Phone contacts dropped 17% from 2015 to 2017—now representing about 55% of all interactions—while assisted/automated service has grown to now represent 45%.

The Proliferation of AI: From Fantasy to Hard Reality

Suddenly, a high level of AI dependence doesn’t seem so crazy anymore. And it shouldn’t. After all, the technology is now driving most of our daily experiences. For example, we’re now seeing AI-based cognitive healthcare that can identify patient care gaps and automate personalized interventions. Companies are launching chat bots built on conversational AI to intuitively communicate with consumers across multiple platforms. Educators are working to unify traditionally siloed data to build school-specific predictive models. The world is embracing AI, and this means organizations across every sector must have the right technology foundation to drive desired customer and citizen outcomes.

But this is easier said than done. The rise of technologies like the IoT and AI have made architecture implemented even 15 years ago no longer able to deliver the kind of dynamic service experience customers now demand. Companies are finding that systems meant to last decades can’t sufficiently handle the pressures of a next-gen, digital business ecosystem. AI has opened the door to vast new CX capabilities, yet most companies struggle to realize the technology’s full potential because of a dependency on legacy hardware and hierarchical architecture.

This is exactly why the concept of a next-generation platform has skyrocketed in recent years. The technology is open, agile and future-proof enough for companies to radically shift to meet the customer needs of today and the future, whatever they may be. In today’s world of limitless possibilities, organizations need a platform that boasts a seemingly endless scope of capabilities.

What Businesses Need in a Next-Gen Platform to Make AI Work for Them

Not just any next-gen platform will do for those looking to capitalize on AI, however. As I mentioned in a previous blog, the concept of a next-generation platform isn’t as simple as it sounds, and there are many variations among industry analysts. Having said this, here are three capabilities that we at Avaya believe a next-generation platform must have in order for companies to realize the full benefits of AI in the smart digital world:

  1. Silo elimination: Not minimization—elimination. Unfortunately, many companies will fail to drive the customer or citizen outcomes that matter most because they’re siloing AI. In doing so, they’re effectively limiting the CX capabilities that the technology can drive. While these companies recognize and prioritize AI, they have yet to look beyond their developments as part of something greater. At Avaya, we believe a next-generation platform must easily integrate AI into any existing business ecosystem to seamlessly drive the digital, end-to-end customer journey. As I’ve said time and again, the greatest barrier to CX success is the continuation of silos. This is especially true considering the ability today to connect customer journeys through analytics.
  2. Intelligent automation: As businesses digitize, they will undoubtedly need a certain level of automation to deploy and manage countless connected services end-to-end. This level of automation must be able to accelerate and customize what consumers and/or citizens will experience. For example, consider an AI-supported school where students can receive automated SMS messages personalized to their daily schedules (i.e., their mode of transportation or extracurricular activities). Or, consider that quarter billion figure mentioned earlier in terms of connected cars. Top manufacturers like Tesla, BMW and Audi are investing in self-driving cars where automated M2M communication outweighs human-to-human communication. Even if a mechanical issue arises, the vehicle will automate a phone call or SMS to ask the driver for more information to strengthen its knowledge base for future incidents.
  3. Multi-database analytics: If I could stress the importance of any one capability, it would be this. Just as companies must integrate AI into their existing ecosystems, they must also break traditional database silos. The power of an AI-enabled CX is ultimately found in the free flow of multi-database analytics. Let’s say you’re traveling to Argentina, for example. It shouldn’t be difficult for a tourism company to register when you clear customs as a guest entering the country, allowing the company to begin delivering a contextualized, end-to-end experience based on knowledge acquired from multiple different databases. For instance, they may want to send you an automated SMS listing the top five tango shows in your local region because they flagged a tweet you had posted two weeks earlier mentioning your interest in tango. They can then offer you a virtual assistant who can help you further, should you have any questions.

This level of engagement is not only possible, but is expected to become the norm in just a few short years. The question is: how can we make this easier for businesses to achieve? This all starts with transitioning to a software-based model that is completely detached from hardware dependency. Software automated architecture, which leverages the full power of the cloud, enables companies to begin easily and reliably scaling with more elasticity to drive these kinds of AI-enabled outcomes.

Up next I’ll be discussing the importance of your next-generation platform being built on an open ecosystem. Stay tuned.

Customer Journey Analytics vs. Traditional Analytics—Know the Difference

It’s expected that 60% of all large organizations will develop customer journey mapping capabilities by 2018. Why? Because the average consumer isn’t so average anymore. Consider that a typical customer now owns three personal mobile devices, each with anywhere from 10 to 20 downloaded apps. This individual owns an average of five social media accounts, nearly three of which are actively used. Additionally, the average office worker receives up to 121 personal emails per day. Just imagine what these figures look like for consumers on the high end of this engagement spectrum.

To get a snapshot of my own activity, I followed these simple instructions to figure out how many emails I receive. It’s 10 a.m. and I show 59 emails received (up from 47 just two minutes ago). And tweets average around 6,000 per second—I have 1,175 in my queue based on who I am currently following. The question is: How do you bring your email, tweet, post, or blog to my attention amid all the clutter?

When we look at what this means to customer experience it is worth noting that we’ve reached a point where over 40% of customers now use up to seven different channels to interact with brands, from live chat to email to social media to SMS. Businesses increasingly understand this fact, and they’re taking the necessary steps to ensure they can deliver consistent, contextualized experiences across various channels and devices.

Each of the devices and channels offers its own set of diverse scenarios for linking to other devices and channels, making no two customer experiences the same. The not-so-good news is that businesses are still grappling to understand customers’ actions across these various touchpoints. They need to leverage data but, in fact, 43% of companies currently obtain little tangible benefit from their data, while 23% admit they derive no benefit whatsoever. Organizations are struggling to create a data strategy that delivers the insights needed to drive anticipatory engagement and repeat spending.

The bottom line is that a business can support virtually every interaction channel. However, without a comprehensive view of the data generated and shared across those channels organization-wide, it will fail. Supporting an array of channels is simply not enough. Businesses must gain an inherent understanding of how customers are using these channels so that they can adapt, evolve and change as needed. This is where the ability to understand your data—specifically, customer journey analytics—becomes vital.

The solution here may be simple to describe, but implementing it isn’t. Adopting customer journey analytics means businesses must now support a powerful, real-time visualization of the customer journey across all lines of business, not just the contact center. They need a roadmap to continually reinvent key processes and fine-tune organizational behavior. They must harness real-time and historical data across all channels and devices to intuitively understand customer needs and optimize business outcomes. Most challenging of all, they must do this in a way that shows tangible ROI and improves TCO.

To make customer journey analytics work, businesses must take a critical step from ideology to implementation—a move that can often feel like a leap of faith.

But there’s good news: technology has evolved to a point where companies can now easily, effectively and cost-efficiently achieve these core data objectives. The key is investing in an extensible, omnichannel customer engagement solution.

Your customer engagement solution should boast simple capabilities. It should be pretty easy to create and manage dynamic, multi-touch customer journeys. And you need a built-in, flexible analytics and reporting platform to deliver a single, comprehensive view of customer data across all sources, both internal and external. This lets you compete using customer journey analytics, and also easily add third-party data sources to amplify their strategy.

A customer engagement platform redefines the way businesses engage with digital consumers. Here’s how customer journey analytics stand apart from traditional reporting and analytics:

  • Obliterates Siloes: A siloed environment is the greatest barrier to data success, and it’s affecting more businesses than we realize. According to Deloitte’s 2017 “Contact Center Benchmarking Report,” nearly 60% of customer channels are currently being managed in silos. Analytics integration is vital for competing on customer experience (CX), an initiative that traditional analytics tools simply can’t support.
     

    Built on open, extensible architecture, a customer engagement platform has unparalleled flexibility for gathering transactional information from numerous different channels (IM, co-browsing, SMS, phone, email, IoT) and devices (phone, mobile/tablets, branch, desktop, kiosks). This enables companies to flexibly collect, process and analyze all real-time and historical data. They gain a rich visualization of their customer journey enterprise-wide. This means consistent, contextualized experiences no matter where and when interactions begin, end, continue—and no matter how many company agents are communicating with the customer.

  • Seamlessly combines internal and external data sources: The open nature of a customer engagement platform enables companies to combine internal data with that of virtually any other business intelligence (BI) tool. For example, insights collected internally can be combined with data from visualization tools from leading providers like MicroStrategy, Oracle, SAP and Tableau. This lets managers maximize the return on their existing investments, while driving their potential beyond what was initially imagined.
     

    Furthermore, this unique ability lets managers generate cradle-to-grave customer interaction reports, enabling them to identify innovative new ways to meet consumers’ evolving needs. Chances are you’re not going to get this with traditional reporting and analytics platforms.

  • Transforms the agent experience: A holistic customer engagement platform redefines agent and supervisor experiences by allowing companies to easily create, customize and integrate key applications for specific work groups. Supported by an advanced software development kit, companies can build their own contact center apps, or embed specific functions into their existing apps, to customize desktops for any unique customer/agent configuration. The solution represents a revolutionary way to serve digital consumers. And, it offers managers a new avenue for analyzing performance metrics for all ways customers are served.

With customers using more digital channels than ever, it’s clear that now is the time to adopt customer journey analytics via a customer engagement platform.

Interested in learning more or chatting about transforming your analytics environment? Contact us. We’re here to help and would love to hear from you.

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!