Move Over Transactional Sales and Deep Discounts:
Enterprises Learn the Value of AI, Real-Time Omnichannel Analytics and Big Data Solutions to Drive Loyalty and Profitability
By Rajesh Nambiar
Competition for customers is as fierce as ever. Just ask the wireless service providers like T-Mobile and Verizon Wireless. Or the smart phone manufacturers like Apple and Samsung. Or rideshare companies like Uber and Lyft. Or big box retailers like Target and Kohl’s.
Every industry has its unique challenges. Among cable and telecommunications companies, the number of competitors and types of companies offering services is expanding just about every day; in the banking industry, firms battle for customers with the latest digital services; and in retail, brick and mortar retailers, ecommerce-only retailers and even ecommerce retail aggregators (think jet.com and amazon.com) are fiercely competing for consumers.
For many, the winning strategy used to entail advertising (lots of it) and deep discounts (lots of them). These companies are slowly realizing this strategy is a race to zero, complete with low margins and razor thin profitability. And it’s a tiring race that seems to have only be won by attrition. Take a look at the number of major retailers shutting down their operations while Amazon has demonstrated a stunning growth journey in this decade.
Enterprises understand they need to refine their strategy, and are turning to data science and new technologies to transform their businesses into real-time predictive enterprises. Customer service call centers, those all-important nerve centers where thousands of customer interactions happen daily, are typically where these technologies have been implemented. Companies are using artificial intelligence and machine learning to develop business reflexes to allow customer service representatives to respond to customers and prospects in near real-time, powered by analytics from both historic data as well as current data as it flows in. We believe any enterprise that does not have the ability to sense customer intent, nor the tools to influence and engage in near real-time, will lose customers and prospects as short windows of opportunities close.
This is not entirely new technology. Most consumer-facing enterprises have long collected data on customers and even prospects. Predictive analytics and business intelligence have been around for two decades, but these systems have become more affordable now and the element of real-time prediction and contextual intelligence has made it every more valuable for enterprises. AI, machine learning and real-time voice-to-text technologies are the relatively new technologies on the scene – at least in a format that is now accessible for commercial use.
At Xavient, we offer AMPLIFY, our real-time, AI-powered, speech-to-text transcription and omnichannel customer interaction engine –to enable businesses, especially service providers achieve positive business outcomes:
· For customer service reps, the technology increases productivity, job satisfaction, first time resolution.
· For those tasked with client satisfaction and retention, it allows for proactive outreach to dissatisfied customers, reducing churn;
· For marketers and sales pros, the technology allows for identifying personalized upsell opportunities
· For the help desk department, it allows for better diagnoses of problems and issues, and more efficiency
· For smart digital assistants and robots at homes, it provides for real-time updates, chores and assisted living.
The best big data solutions begin with an ability to capture and aggregate data, including countless threads of customer interactions – be it chat, tweet, email, voice mails, voice transcripts, payment habits or logs and social feeds – into a single, all-encompassing data stream on which companies can mine information to better serve customers.
One of the foundations of such an awesome system is real-time, voice-to-text transcription and analytics and dynamically driven business processes fine-tuned to drive next best action. Relying on notes is not enough. These systems record call customer calls, transcribe them and analyze keyword content in order to determine customer disposition, concerns and sentiment. Consider that typically 60 million hours of conversations are recorded every day in call centers worldwide. Buried beneath these myriad calls lie their customer needs, wants, concerns and issues. But this wealth of information largely remains untapped due to technology constraints and the high cost of infrastructure and software licensing.
Obviously, collecting the data isn’t enough. It’s what companies do with it that will determine winners and losers in the marketplace. AI and machine learning algorithms are the key. In systems such as Xavient’s AMPLIFY, the more CSR-customer interactions, the smarter the system becomes, improving suggested troubleshooting techniques and even offering alternative or additional products and services where appropriate. We have worked with clients to develop a system in which the machine deep learning analytics algorithms feed recommendation engines capable of delivering real-time coaching to achieve the optimal customer interaction.
Some of Xavient’s major clients have successfully deployed AMPLIFY to automate the process of collecting and mining large volumes of digital data from multiple channels/customer touch points and gaining contextual intelligence to improve operating efficiencies, reduce customer churn and drive up their Net Promoter Scores – a direct indicator of customer experience. One such client is bringing down both CAPEX/OPEX in their call
centers, which typically receives more than a million calls per month, while improving customer experience by being predictive and solving customer issues over the phone, thus reducing the need to send technicians into the field.
Call centers usually record about 10-15 percent of all their customer calls and perform quality assurance on 1 percent of those calls due to high cost of voice processing infrastructure. Historically, such systems were prohibitively expensive due to complex infrastructure required for real-time systems, computing, analysis and storage. Xavient has solved that problem by architecting AMPLIFY
entirely based on open-source components, along with using Amazon Web Services (AWS). Enterprises today can embed AMPLIFY
into their call centers and digital assistants to elevate their customer experience journeys by capturing the full voice of all their customers and acting contextually with “next best” action. These services are available via an on-demand subscription or usage-based utility payment model which costs a fraction of traditional in-house voice infrastructures.
At Xavient, we believe that the road to differentiation is by extreme customer experience and the road to profitability is through automation and reducing cost to serve. Everything else has been commoditized. AI and machine learning platforms can deliver a new level of actionable insights into customer interaction and experience, enabling businesses to not just react to a problem or opportunity, but to seize opportunities and avert threats as the situation is developing in real-time. This solution not only provides the ability to attain precise insight into what is actually happening with a business at any moment, but goes one step further by generating and delivering contextual intelligence to employees at the front lines, actionable recommendations while they are interacting with the customer to steer the transaction to a successful outcome, which results in a happier customer, reducing cost to serve and higher customer life-time value and share of wallet.
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About the Author: Rajesh Nambiar is senior vice president of North American Sales for Xavient Information Systems (www.xavient.com), a leading IT digital solutions integrator headquartered in Simi Valley, Calif. Rajesh can be contacted at firstname.lastname@example.org and on twitter @rajeshnambiar