Guest Blog by Anand Janefalkar, Founder & CEO, UJET
Prior to the pandemic, it was already widely understood that artificial intelligence (AI) would play a major role in shaping the future of customer service. Yet while many knew that AI was an inevitable part of their contact centre, for many businesses, it felt like a “we’ll get to it eventually” item. Then, COVID-19 happened and with the pandemic, businesses and customer service organisations found themselves needing to digitally transform overnight.
Many have realised that the best and smartest path forward is through next-generation cloud technologies and fast-tracking their adoption of cutting edge applications and solutions such as AI and machine learning (ML). In fact, a recent report from Gartner predicted that by 2022, 70% of customer interactions will evolve emerging technologies such as machine learning (ML) applications, chatbots, and mobile messaging, up from 15% in 2018.
Prior to the pandemic, AI in the contact centre was predominantly looked at through the lens of the chatbot. While chatbots are still a core piece of the modern contact centre, the pandemic has shown us where and how AI can be leveraged throughout the customer journey and communication lifecycle in order to not only create better CX for customers but for contact centre agents and supervisors as well.
Curating personalised experiences for customers has steadily become an essential part of creating and retaining lifelong customers, and according to the State of the Connected Consumer report by Salesforce, 84% of customers say that being treated like a person and not just a number or any other person in line is very important to winning their business. When it comes to creating hyper-personalised experiences, real-time contextual information is needed, which is where AI and machine learning comes in.
Real-time intelligent data dips that can be automatically populated and made accessible to support agents provide the immediate context customer service teams need to not only understand the issue but understand the customer as well.
Using AI to set up dynamic queue customisations and smart routing capabilities means customers can quickly and easily be connected to the right agent or routed to the appropriate knowledge base the first time, and avoid the frustrating cycle of being put on hold, transferred, restating their information, and so on. Avoiding these types of situations and intelligently routing customers to the right place where specialised experts can help them can go a long way in keeping customers satisfied and loyal.
Let’s be honest, customer service professionals did not get into this business so they can spend their day generating reports, inputting information, or even handing minor issues that could be resolved through an FAQ or knowledge base. Instead, agents should be focused on solving complex issues that require both human empathy and a personalised touch.
Automating repetitive tasks through the use of intelligent assistance means agents are no longer burdened with the need to interrupt their customer-facing workflows and can instead continue directing their energy, focus, and empathy towards ensuring customers are not only having their issues resolved, but are walking away satisfied with their experience.
We also know that no matter how well we prepare, there are going to be times when support inquiries come rushing in and agents find themselves handling multiple issues and customers. It’s during times like this when some of the more administrative tasks may be more challenging to complete. By infusing AI and automation into repetitive tasks such as closing out tickets, generating reports, updating customer information, and more, contact centre leaders can better ensure that no matter how busy their agents get, things are getting done.
In a global, digital, and currently a predominantly remote economy, customer service is critical around the clock. Yet providing 24/7 service can quickly become expensive and operationally inefficient. Deploying AI-driven Virtual Agents, across both chat and voice channels can help alleviate staffing pain points while ensuring that customers are able to have their issues resolved no matter the day, time, or location.
AI not only can assist with providing around the clock support, it can help contact centre leaders gather more strategic insights into how to achieve operational success. For example, AI can help surface key trends such as peak hours, frequently asked questions, where support issues are located, and more. These insights can play critical roles in helping organisations strategically staff their contact centre, train their agents, and identify opportunities to provide better service for their customers.
In fact, we ran a State of Customer Experience survey earlier this year and found that 74% of respondents said that they are either researching or in the process of implementing AI, and contact centre professionals are predominately looking to leverage AI to reduce repetitive tasks (48%), improve CX (46%), and lower costs (40%).
Contact centres are under more strain than ever before, but while customer service inquiries are spiking, organisations also find themselves with a golden opportunity to usher in a new and modern way to provide customers with the best experience possible.
As companies embark on their AI journey it is important to know that these technologies on their own will not uplevel a contact centre overnight. But with the right partners, configurations, testing, and more, businesses can begin leveraging AI and cutting edge technologies in order to not only help customers through these challenging times but lay the foundation for establishing a one-of-a-kind post-pandemic customer experience.
Guest Blog by Anand Janefalkar, Founder & CEO, UJET
Reimagining Customer Support for a Connected World – Through its drive for innovation and passion for accelerating digital transformation, UJET is a leading provider of cloud contact center software. UJET helps support organizations of all sizes and industries break down silos, reshape business models, and realize their true potential.