When it comes to maintaining high levels of customer service in today’s world, the bar is always being set higher. Whether you work for a consumer-oriented company or a B2B organization, the constant drumbeat to anticipate every need and deliver greater convenience means that we have all become tougher customers who are increasingly difficult to please. As leaders in the B2C world have demonstrated, the application of technology to boost customer satisfaction has gone way beyond boosting efficiency and responsiveness to anticipating needs before the customer has fully articulated that need themselves.
That requires a whole different way of applying technology to identify opportunities and create a competitive advantage. It means evolving from a reactive mode to a continuously proactive process of teasing out trends and parsing knowledge out of data streams.
Doing so requires more than just technology. It requires time and energy from knowledgeable, skilled employees who have value well beyond the often routine tasks they are asked to perform today.
If you looks at emerging trends in customer service, here’s how th bar will continue to get raised over the next decade or so:
Omnichannel support, across email, chat, text, phone and social media, through interactions with sales, marketing, and other customers has created a wealth of opportunity and challenge for many companies. Often, customers jump from one channel to another in an effort to get their voice heard and get the response they want. Managing these interactions effectively and tapping into the wealth of information they contain will continue to determine the degree of success of any digital transformation effort.
According to Gartner, more than half of established organizations (55%) have started making investments in the potential of artificial intelligence, or are planning to do so. AI will have all sorts of roles to play when it comes to customer service, including helping to transform data from customer interactions into better insights about how to best anticipate customer needs. That may means knowing which channel is most effective to communicate with a particular customer, or how to match a customer service agent (or bot) that best matches the style of communication of a particular customer.
In many ways, Intelligent Process Automation can help to deliver a pipeline of meaningful data for AI systems to parse and find the kind of customer service insights companies are looking for to give them an edge. Intelligent Process Automation solutions can be used to extract data from unstructured content like sales orders, so that detailed purchasing data is captured quickly and put into systems that AI tools can tap into. In the past, this data was found in sales orders that had to be manually keyed into database systems. Now, with IPA tools for order processing, not only is the data more timely and accurate—it also means that you can refocus staff on capitalizing on newly-discovered buyer behavior trends to deliver better service.
The number of channels customers use to contact your company will continue to expand, even as the existing channels are more broadly adopted. Today, it’s phone, chat, text and social—who knows what methods or media will emerge next? That means that the challenges companies face today to get their arms around all of these interactions will only grow, unless they are addressed in a way that can continue to scale and adapt.
There are lots of things companies can do and plenty of opportunities to improve operations to boost customer service. Across the board, though, the biggest challenges companies face are related to operational inefficiency and ongoing challenges related to gathering and analyzing data.
One of the most straight-forward ways to address these fundamental problems is to automate the most routine, predictable parts of your process to free up the time and attention of your teams members, and then further nurture and develop their skill sets.
One simple example that can lead to further automation and innovation is customer order processing. Intelligent Process Automation that applies machine learning to the challenge of extracting relevant data from sales orders and other customer- or sales-related documents can radically reduce the time and effort sales operations and customer service team members spend handling documents and entering data. It also provides them with more timely access to that data and related documents, so they can more readily respond to customer inquiries.
More importantly, that data can be mined to provide additional insights about buying behavior and purchasing trends to anticipate inventory levels or pro-actively engage with customers to address their needs.
From there, all of the added benefits of emerging technologies like AI come into pla, because you have actionable data to work with. Often, this is the biggest stumbling block to business intelligence and other innovations that begin with data.
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