Predictive Customer Service: A 2020 Toolkit

With the vast amounts of customer data and AI tools available now, contact centers are securely leveraging real-time data patterns to deliver a more intuitive and anticipatory customer experience known as predictive customer service. But how do you build out a predictive service environment that preemptively delights customers? Consider this your toolkit to predictive service for 2020 and beyond.

  • Get a technology toolkit anchored in the three core components of predictive service
  • Explore three keys for predictive success and get tips on what to look for in solutions
  • Discover real-world uses cases driving desired outcomes across many industries

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With the vast amounts of customer data captured today and the artificial intelligence (AI) tools available now, contact centers are securely leveraging real-time data patterns to deliver a more intuitive and anticipatory customer experience known as predictive customer service.

With more than 69% of enterprises planning to increase their contact center AI budget in 2020, it’s only a matter of time before AI gets infused into every inch of the enterprise. As it does, IT and service leaders need ways to capitalize on this data without further complicating their operations. How do you leverage all that’s available today to build a predictive service environment that preemptively delights customers? Consider this your toolkit to predictive service for 2020 and beyond.

The Predictive Customer Experience

What is predictive service? Predictive capabilities engage customers proactively, using data to anticipate needs. By using a 360-degree customer approach that works in line with sales and marketing, predictive service is known to optimize revenue with more loyal customers and greater competitive advantage.

Predictive service is no longer an “emerging” new concept. It has become a staple within the modern-day cloud contact center.

The predictive customer experience is built on three core components:

  1. Leveraging AI to deliver personalized, predictive, and proactive care.
  2. Providing the right context and automation exactly when it’s needed.
  3. Intelligently matching customers and agents to drive targeted results.

Here are the technologies needed for mastering these areas of predictive service.

Predictive Service Fundamentals: Conversational Intelligence

What it is: AI and machine learning can be applied around voice conversations to generate key insights into customer interactions. Conversational intelligence draws from a group of technologies including speech recognition, text-to speech, voice biometrics, natural language processing, machine learning, predictive analytics, behavioral analytics, speech analytics, and more. Analytics engines are used to transcribe conversations in real-time for deeper intelligence and superior customer engagements. These systems leverage current and historical facts to make predictions about future customer behaviors and needs (ex: 61% of customers who inquired about this product were also interested in purchasing this accessory) 6 . The result is essentially computers or programs that interact with people through a natural language conversation, backed by elevated levels of intelligence thanks to AI tools.

Why it’s important: Conversational customer care is growing in demand. Gartner predicts that by 2023, customers will prefer to use speech interfaces to initiate 70% of self-service interactions (compared to 40% in 2019) 1. Conversational intelligence drives operational efficiency, reduces after-call work, provides a more dynamic self service experience, and creates better consistency across touchpoints.

Use cases:

  • Simplifying administrative duties: automate appointment scheduling and rescheduling, service subscription reminders, client notifications for when bills are due, membership management, payments and PCI compliance, and more using customers’ preferred communication channels.
  • Having a free-flowing phone conversation that can range from basic to very sophisticated: Using natural language processing, you can create a conversational self-service system that listens and engages in two-way conversation. For example: “Press 1 for sales, 2 for service,” “Would you like to purchase? Please say yes or no,” “Your contract is due in February and we want to continue your service. Would you like to learn about our discount for early renewal?”
  • Understanding and adapting to the various ways your customers ask for things: Virtual agents use machine learning to understand the different ways customers ask for the same thing. For example, if the solution is programmed to understand “I need to fix my car,” over time it can learn the many different ways this might be asked (i.e. “my car needs to get fixed,” “my car is broken down,” “my car needs help”).

 

Matchmaking for Results:Predictive Routing

What it is: Predictive routing uses AI and machine learning to match customers and agents based on next-level variables like personality, similarities, and the skill level of a particular agent (how likely an agent is to sell, subscribe, upsell, retain, etc.). AI engines can quickly mine a contact center’s entire library of intelligence to optimally pair customers with agents and drive the best possible outcomes.

Use cases:

  • VIP service: Provide VIP service to your most important customers by routing them immediately to someone who can help.
  • Customer loyalty: Automatically route customers identified as being at-risk to an appropriate team or service member versus having them go through your IVR system (this could be determined by AI engines analyzing key indicators of dissatisfaction like number of support tickets submitted or service cancellations).
  • Improved business outcomes: Use predictive routing with your contact center and customer data, including: customer service inquiry types, solutions for common customer concerns, records of each customer’s previous service interactions, scripts to upsell/cross-sell products, knowledge of each agent’s skills, and more.

From AI to Dollars: Three Keys to Predictive Success

Enterprises can (and must) adopt predictive service for delivering better experiences in 2020 and beyond. Practically, there are three steps that should be taken to ensure success:

1. A single technology ecosystem for digital transformation readiness

Predictive service is much more than “just” AI. Cloud contact centers require a constellation of technologies all working together: AI and machine learning, virtual agents, predictive routing, omni-channel tools, workforce management, unified communications (UC), SIP trunking, network services, security services, and more. You must think about your entire technology ecosystem working as a unified whole, understanding the various layers that both make up the environment and ultimately lead to customer experience success. In order to reduce IT complexity, companies need a single cloud platform that can support the plethora of cloud technologies needed to make predictive service work successfully.

Gartner recommends: “Use an application ecosystem approach to investing in contact center vendor technology that can power improvements by offering fluid and easy access to features and benefits.” 1

What to do or look for:

  • Evaluate providers that deliver a single, seamless solution that crosses a wider swath of cloud contact center capabilities including UC, SIP trunking, network services and security tools. Fewer providers are typically better, particularly with SIP trunking and also as data passes between channels into analytics tools for real-time agent screen pops and/ or historical trending.
  • Consider migrating both contact center and corporate communications to the cloud together. According to Gartner, companies that empower their agents with UC experience up to a 68% greater annual increase in customer profit margins and 98% improved customer retention rates. Gartner recommends: “to empower greater collaboration in customer service with digital workspaces, favor providers that offer the commercial model and mobile productivity features that will support the dissolution of the front-office/back-office divide.”1
  • Integration is key, as all services should be proactively integrated. Ask your provider for proven solutions and case studies showing how they deliver across all needs on a global and enterprise scale.

2. A reliable and secure network foundation

Building the highly desirable “digital customer experience” hinges on delivering near-perfect network connectivity for users across the globe. In today’s world, customer experience leaders and IT professionals are less worried about the ROI of migrating their contact centers to the cloud (cloud benefits are well documented and easily justifiable). Instead, today’s cloud investors come to the table needing a partner who is an expert in seamless cloud migration and application support with a proven history in executing transitions that minimize contact center disruption. They quickly steer the conversation away from virtual agent features and functionality, probing into creating a smooth transition and, most importantly, additional capabilities that advance their digital transformation.

What to do or look for:

  • Don’t think about cloud applications independently. Rather, proactively consider the IT network and a managed network service purpose-built for global voice, video, and real-time communications.
  • Networks that provide global reliability for all voice/ video communications and have the computing power for real-time AI analytics. Industry leaders will have global SLAs that deliver:
    • <1 millisecond of jitter
    • 100% packet delivery
    • 99+% uptime
    • <1 second failover
    • 24/7 network performance monitoring
  • Don’t let your contact center transformation get stuck waiting on IT. Global networks built on a uniform software-defined architecture are designed for agility that can shift as fast as your enterprise needs. A single SD-WAN across the globe enables one portal for centralized management, real-time application performance analytics, and self-service controls for bandwidth adjustments on-demand. With these modern networks, enterprises can also allocate dedicated resources to contact center operations without impeding other business processes.
  • Leaving security as an afterthought is a common mistake with AI. When establishing cloud applications for a global footprint of contact centers, you need to be well-attuned to the security threats that could be unleashed. In order to mitigate these risks, customer experience and IT leaders alike should proactively prevent system compromises by establishing security monitoring and creating policies for protection. It is possible to dynamically monitor network behavior in response to typical contact center events and report anomalies that could indicate a security threat.
  • Providers that bundle security monitoring and threat response services in a single solution can simplify digital customer transformation. These comprehensive solutions are also based on machine learning and behavioral analytics and use the latest technologies to detect early indicators of infiltration. Additionally, 24/7 security monitoring by a team of experts can accelerate the processes needed to identify attackers, watch for lateral moves, and mitigate threats before they cause extensive damage.

3. Integration Platform-as-a-Service (iPaaS)

Virtually every SaaS application (CRMs, ERPs, UC platforms, marketing tools, etc.) has an API option, but they are rarely used. As a result, only a fraction of contact centers integrate their apps in a meaningful way (ex: enabling predictive service). There is no shortage of APIs, yet IT teams aren’t taking full advantage because doing so is too complex. Integration as a Platform (iPaaS) changes all of this.

iPaaS is a solution that simplifies the integration of multiple apps and automates workflows. iPaaS solutions expedite and simplify integration projects, using a real-time execution engine to keep up with demanding requirements of real-time apps such as UC and CCaaS. Think of iPaaS as the glue between cloud applications or a way to break down the walls between your various services.

For example, when contact centers unite iPaaS with UCaaS, voice recognition tools, and any cloud-based business application, they have the power to easily create voice-triggered automation experiences for agents and customers. Voice-triggered workflows take business process automation to the next level. Imagine an agent’s voice triggering automated processes, where the conversation goes like this:

Agent: “Thanks Mike, I understand you would like to order those holiday slippers and have them sent to your house by Christmas. Is that correct?”

Customer: “Yes”

Agent: “Smart Assistant, create a purchase order for item #123 and ship to customer #987 at primary address 1234 Miller Ave, Dallas, Texas 78206. Over.” (On the back end, a purchase order is automatically created and populated, ready for final confirmation and order submission)

Agent: “How else can I help you today, Mike?”

What to do or look for:

  • iPaaS tools should have prebuilt API channels and advanced data management to handle complex workflows
  • Visual workflow editors make integration as easy as drag-and-drop menu options
  • All-in-one providers offer iPaaS alongside cloud contact center technologies for easy, oneinvoice solutions that encompass a wider array of technologies required for transformative change

If service and IT leaders wish to keep up with the pace of change coming in the next decade, they need a smarter, cloud-based contact center approach; one that ensures connected, intuitive, and personalized experiences both internally and externally.

Transform with Certainty℠

Transforming with certainty comes down to converging the latest AI technologies with your data libraries and cloud contact center applications as a single platform. Accelerating this process requires a partner with expertise that crosses cloud contact center applications, IT networks, global application performance optimization, and security as well.

Masergy is the secure software-defined network and cloud platform for the digital enterprise. Recognized as the pioneer in software-defined networking, Masergy enables unrivaled, secure application performance across the network and the cloud with Managed SD-WAN, UCaaS, CCaaS and Managed Security solutions. Industry leading SLAs coupled with an unparalleled customer experience enable global enterprises to achieve business outcomes with certainty.

Contact us today for a free consultation.

Sources

  1. Gartner “The Future of the Contact Center”
  2. https://www.marketsandmarkets.com/Market-Reports/predictive-analytics-market-1181.html
  3. https://www.gartner.com/en/newsroom/press-releases/2018-02-19-gartner-says-25-percent-of-customer-service-operations-will-use-virtual-customer-assistants-by-2020
  4. https://www.gartner.com/en/newsroom/press-releases/2018-02-19-gartner-says-25-percent-of-customer-service-operations-will-use-virtual-customer-assistants-by-2020
  5. https://www.gartner.com/en/newsroom/press-releases/2018-04-25-gartner-says-global-artificial-ntelligence-business-value-to-reach-1-point-2-trillion-in-2018
  6. https://www.marketsandmarkets.com/Market-Reports/conversational-ai-market-49043506.html
  7. https://patientengagementhit.com/news/patient-access-to-health-data-portal-access-surges-to-92
  8. https://www.artificial-solutions.com/wp-content/uploads/protected/wp_the-future-of-retail-customerservice.pdf
  9. https://nemertes.com/banks-adding-ai-analytics-to-boost-cx/
  10. The Intelligent Contact Center: Get Smarter to Drive Customer Satisfaction, Aberdeen, June 2018

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