Understanding and exceeding customer expectations means growth and sustainable differentiation for businesses that organize around customer-centricity and pursue new products, services, solutions, and markets to meet evolving customer needs. As the engine for addressing client challenges, inquiries, and needs, the contact center is essential to unlocking this promise.
For this reason, the contact center is no longer characterized by the transactions it processes and the issues it resolves. It can no longer be viewed as a low-cost channel for managing customer interactions. Instead, it is integral to an organization’s customer-centric transformation, fueling continuous evolution and strategic enablement by generating rich insights, safeguarding client satisfaction, and driving profitable growth.
This positioning has made it paramount that contact centers serve as a primary launching point for designing, testing, and deploying new solutions that promote future-focused thinking, organizational resilience, and greater agility in response to customer-led transformation imperatives.
Contact center solutions centered on operational excellence, advanced analytics, employee engagement, and automation-based technologies are generating impressive outcomes for organizations. However, companies who are amplifying their focus on customer experience (CX) solutions are making greater progress in client satisfaction and profitable growth. Our series has covered the action steps needed for mobilizing a CX-led contact center and creative practices to drive adoption and advocacy. We now focus on emerging trends in artificial intelligence and how they can be applied within the contact center.
Imagine the contact center of the future: customers speaking to “virtual” customer service representatives, virtual agents knowing things about the customer including their reasons for engaging, their current emotional state, the issues they might be experiencing, or what their long-term aspirations might be. This is just one of the images that come to mind when contact center leaders envision artificial intelligence (AI), also known as cognitive solutions. Here we will outline the benefits of deploying cognitive solutions in the contact center, distill fiction from reality on how cognitive solutions are being deployed, and highlight the critical drivers for success when implementing cognitive solutions within the contact center.
While rapidly expanding in other arenas, the implementation of cognitive solutions in contact centers is still emerging. For example, a recent survey showed that only 15 percent of consumers have used chatbots in their interactions with businesses in the past year. However, those that have deployed cognitive solutions have seen material benefits, including:
Deepened relationships with customers based on previously unknown insights
Increased first call resolution
Improved efficiency (i.e., reduced talk times, cycle times)
Enhanced data quality and accuracy
Increased capacity for human representatives to shift from transactional to value-add conversations
Streamlined quality assurance and compliance processes
There are many applications within the contact center, the most common being virtual agents, or chatbots. Virtual agents can answer common questions and take action on behalf of a human user (customer or employee). They help with the business goal of reducing repetitive, low-value effort and increasing speed to information or action. Contact centers are increasingly deploying virtual agents and chatbots to both engage with customers to provide automated technical assistance, and provide real-time support to customer service representatives to drive more effective outcomes.
Other applications of cognitive solutions within contact centers include:
AI has many powerful applications in the contact center, however, success has been limited. As we highlighted in our Cognitive Ethics blog series, while the technical capability is available, “organizations are not well versed in how to properly design or implement for adoption.” The biggest challenges that organizations face include lack of clear governance, limited maturity of data, challenges to organizational buy-in, and limited organizational capacity or skillset to deploy cognitive solutions.
Below are several success drivers for organizations implementing cognitive solutions:
Get your data AI-ready. Data is the lynchpin for effective cognitive solutions and many organizations fail when it comes to collecting and preparing data for cognitive solutions to consume and learn.
Build capabilities by incrementally combining automation and cognitive technologies. Discrete technologies within the cognitive spectrum—e.g., chatbots, RPA, natural language processing and generation—should be purposefully combined and deployed in coordination for the best outcomes.
Master the human + machine paradigm. As highlighted in a previous blog on AI, cognitive solutions need a “human-in-the-loop” component to optimize “the partnership of human + machine work to enable […] employees to deliver meaningful experiences at speed and scale.”
Make your operating model and governance approach “solution-agnostic.” The model should be flexible and highlight how to engage with vendors, architectures used, and should include the involvement of many partners across the organization, including business, IT, data science, finance, marketing, and operations.
In our work, we helped a Fortune 50 technology company that was facing challenges with its sales support function. 15,000 sales and licensing agents were spending too much time on information-finding tasks. Pertinent information changed regularly, and tracking down the latest data was impacting productivity. This slowed the sales cycle and distracted from higher value activities. North Highland worked with the client to develop and implement an ecosystem of custom AI-enabled bots that handled manual, repeatable information-finding tasks. This freed up sales specialists to focus time and judgement on complex deals and customer relationships. The company focused intentionally on behavior change and user engagement to ensure the technology not only worked, but was adopted and evangelized internally. The 16-week implementation created efficiencies equating to 83,200-person hours per year. With these breakthroughs, the company is now considering how to deploy bots across other enterprise applications.
Start with the business problem to be solved, then customize a cognitive technology solution to tackle that challenge: this is the best way to capitalize on the promises of AI. With contact centers being a critical component of customer experience delivery, the stakes are too high to simply follow the technology trends of the moment. Those who intentionally decide on and mindfully deploy solutions to problems that matter, will be sure to set the bar for the cognitive contact center of tomorrow.