In a world where switching brands is easier than ever before, customer service is increasingly central to maintaining brand loyalty, and how organisations streamline customer interactions will be critical to a successful strategy. In fact, a survey by PwC found that 32% of customers would stop doing business with a brand they love after just one poor experience.
This underlines the speed at which customer expectations are evolving. Many are now demanding a near perfect online experience and with more competition than ever before, organisations need to do all they can to ensure they keep customers on side. This is already being achieved with more businesses adopting the correct omnichannel capabilities but it’s imperative they go one step further and provide a service that makes them stand out from the competition. This is where artificial intelligence (AI) comes into play.
AI’s rise to prominence across manufacturing
AI refers to any type of computer software that engages in humanlike activities, such as learning, planning, and problem-solving. The most common way AI is used for business purposes today is through machine learning, whereby systems can appear to ‘learn’ over time, and complete tasks with increasing efficiency. This makes them ideal for analysing vast amounts of information, before converting them into contextual data that is more digestible for humans. This has seen AI rise to prominence in the IoT environment, but also within leading CCaaS solutions, where data and the ability to interpret it, are key.
Utilising automated chatbot communication tools
The popularity of AI-driven chatbots has grown significantly in the last couple of years, with younger consumers particularly fond of interacting with companies in this manner. Now, the use of AI in automated chatbot communication has become commonplace in many organisations’ customer service functions. In many cases, it provides the seamless experience that today’s discerning customers require, so AI’s transformative potential in this respect is clear. Its recommended that service-based businesses should be using automated chatbots.
AI will continue to be used for automated chatbots, but more granular applications such as call analytics will also see major growth.
The importance of investing in AI-based analytics in manufacturing
Speech analytics refers to the ability to understand and process keywords, phrases, and terms, but furthermore, advanced acoustic algorithms can now even measure and evaluate voice pace, volume, pitch, tonality, and other factors to determine emotions behind the words, accurately capturing the sentiment of each interaction.
The ability to, for example, transcribe speech into text is the bridge between call recordings and being able to analyse your data, with AI now the driving force behind those analytics.
Capturing both sides of a conversation using voice recognition software used to be difficult, but the technology is now capable of separating caller from agent, thereby enabling more granular analysis and allowing the true potential of AI to come to the fore. By layering screen and video capture into the mix, the organisation can harness this data to build a full profile of interactions between different customers and audiences.
The average contact centre might process thousands of calls, including hundreds of hours of information. In the past, what this meant was that to extract data for quality assurance, supervisors would manually select only a small percentage of calls, before undertaking the hugely time-consuming task of listening through those calls to score them for agent evaluation.
AI-powered systems completely bypass the need for this kind of work. Businesses can now have every call or video interaction recorded, automatically transcribed, and used for analysis, almost instantly, and with totally customisable data points.
Being able to search transcribed call data for customer tonality, keywords, and phrases linked to both positive or negative sentiments, and spot trends over time could quickly deliver ROI for businesses. Quickly identifying problems that negatively impact customer experience allows businesses to solve those problems and prevent them from affecting the rest of their customers.
The trend towards using analytics in this area is by no means new, but the past two years have urged organisations to invest more into AI-based analytics than ever before.
AI’s ability to improve the performance of agents
Studies show that 82% of customers stop doing business with a company as a result of a single bad experience, so as well as customer analysis, the ability to ensure consistency of agent performance is also vital. It’s also not just the quality of interactions that can be improved. Studies show that as well as improved CS score, the speed of ticket resolution can even be improved by contact centres who use AI-powered tools effectively.
Agent evaluation such as being able to quickly analyse agent tone, script adherence, and how they perform when facing negative customer sentiment can help to create best practices, show trainees how to implement them, and how calls can break down when policies aren’t followed. Equally, positive examples to use in training can help agents improve.
This kind of analysis benefits both managers and agents alike. Managers become more aware of how individual agents perform, while agents are given clear direction on how they can improve their performance. The result is increased sales and an overall improvement in customer experience that promotes brand loyalty and raises the overall profile of a business.
Now is the time to invest in AI
Customer experience is more important now than ever before, so modern businesses must be mindful of this when evaluating how their customers can communicate with them. Those who properly marry AI to deliver high-quality customer experiences will be the ones to enjoy the highest levels of consumer loyalty.
The outlook for businesses in 2022 looks much more positive than the last two years. As a result, now is the ideal time for leaders to figure out the best ways to unleash the full promise of AI, and build a more complete, rounded experience for customers.
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