Powering through your CX program manually probably won’t do the trick. It’s time to turn to artificial intelligence and machine learning.
When it comes to business growth, customer experience is everything. You can’t expect your brand to grow without ensuring it delivers a pristine CX.
Despite the known importance of an optimal customer experience, many companies are still stuck at poor and very poor levels on the customer experience index. The reason, allegedly, happens to be a reactive rather than a proactive approach of shaping the customer experience.
Companies have long been reactive about their CX. Gathering feedback first and then taking appropriate action.
These conventional methods are time and resource intensive. They introduce a decisive lag between customer complaints and resolution, leading to the entire customer experience taking a hit.
“Experiences that are constructed and then left to run are no longer good enough for consumers,” George Colony, CEO of Forrester, wrote in a 2018 piece.
Conversational-AI-powered real-time customer experience offers an alternative to this outdated approach.
Customer Experience, Personalization and Customer Personas
Customer experience spans all customer touchpoints and plays a vital role in driving revenue and building brand perception.
Customers are willing to pay 17x more when a brand offers an exceptional customer experience. This could be why companies offering a good CX increase revenue twice as fast as those with a bad customer experience. In modern times, a sound customer experience is shaped in real-time.
According to Colony, “Real-time CX does two things: 1) delights customers now, and 2) shows sophistication and responsiveness — which enhances the company’s brand.”
Since 74% of Gen Z consumers prefer personalized products or services, personalization is a critical part of a well-built customer experience equation.
Personalization is rooted in customer data manifested through customer personas. Accurate, data-based customer personas empower brands to be intuitive of their customers’ needs. They deliver on them proactively, ensuring they don’t miss any opportunity to gain customers and brand advocates.
As we rapidly enter digitization, we come across large volumes of data across various channels. Collecting and analyzing this data accurately is not something humans can do efficiently.
AI-driven data analysis helps companies collect, sort and analyze massive volumes of data with accuracy. This is why AI happens to be a key player in building streamlined customer personas that fuel effective personalization.
But the utility of AI depends on the quality of the data itself.
Related Article: Are You Using the Right Customer Experience Analytics?
Data — a Goldmine for Analytics and AI
“Delivering exceptional customer experience comes down to the right tools and good data,” Scott Clark wrote on CMSwire. Effective implementation of AI and the outcome of analytics depends on the quality of data.
According to Gartner, real-time CXs that drive revenue and increase customer satisfaction rely on your ability to gather high-quality data in real-time, analyze it and implement appropriate responses based on it.
Once a business has its hands on non-siloed, well-sorted data, it can leverage the insights captured within to shape its customer experience using technologies like machine learning and conversational AI.
Real-Time Messaging With Conversational AI and ML
Customer service is a huge part of the customer experience. Sixty-one percent of customers are reported to have switched brands due to poor customer service. Moreover, 95% cite customer service as an important factor in choosing and staying loyal to a brand.
Customers no longer have the patience to wait for a support agent to contact them. They want immediate answers. In fact, 90% of consumers believe an immediate response to a customer service query is essential.
Modern technologies like AI and ML enable brands to implement real-time messaging. This allows brands to offer superior customer service (and experience) without allocating huge budgets for it.
Conversational AI provides an excellent alternative to human support agents in the form of chatbots.
Chatbots take and respond to queries 24/7, just the way your customers want. These robots also collect and store customer data in real time. The availability of such data enables you to deliver better, more personalized experiences.
So, conversational-AI powered chatbots play a critical role for companies trying to uplift their customer experience with a proactive rather than reactive approach.
Related Article: What’s the Impact of Conversational AI for Contact Centers?
Conversational AI in Action
Seventeen percent of customers abandon their shopping carts due to a bad customer experience. So, focusing on enhancing customer experience across all customer touchpoints is no longer a choice. It has become a necessity.
Customers want brands to know what they are struggling with without having to tell them. Therefore, collecting customer feedback and implementing findings in real time is an absolute must.
An international hospitality company was able to double the customer engagement and grow their reach to almost 11 million by tracking brand mentions and relevant conversations on all digital channels. This company then uses the information it collects to shape individual customer experiences in real-time.
Chatbots can also serve as a channel for real-time messaging and data collection. Responding to customer queries promptly, these bots can help foster a positive customer experience and contribute to business growth.
Amtrak implemented sound chatbot technology to uplift their CX. As a result, the company answered 5 million queries annually, generated 800% ROI, and saved $1000.0000 in customer service expenses in one year.
Chatbots are, however, only one of the many use cases of AI-driven, ML-based CX.
Moxiworks, a platform that connects clients to real estate brokers, uses an ML-based platform to analyze incoming queries and support tickets. Based on its findings, the platform automatically routes these queries to appropriate departments and agents, effectively bringing down the inherent friction in customer support.
Conclusion: Real-Time CX the Only Answer
Fostering a profitable customer experience in real-time is what modern brands need to stay competitive. However, shaping customer experience proactively rather than reactively requires good quality data, efficient analytics and implementation of technologies like conversational AI and ML.
When adopted, tools running on these technologies, like conversational chatbots, contribute immensely in shaping a positive customer experience, bringing down costs, and increasing customer satisfaction.