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    Home»Customer Experience»Is automation really killing customer service jobs?
    Customer Experience

    Is automation really killing customer service jobs?

    Michael StelzerBy Michael StelzerFebruary 23, 2020Updated:March 23, 2020No Comments5 Mins Read0 Views
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    Modern and disruptive technologies that are set to speed up automation and reduce headcount aren’t a new revelation. We frequently hear concerns that artificial intelligence (AI) and robotic process automations (RPA) will come at the cost of jobs, whilst leaving customers without access to real people to help solve their problems. But despite this fear, the reality is far different.

    What the customer wants

    Technology and automation drive improvements in customer experience. Fact. Greater efficiencies, better planning and improved optimisations benefit the enterprise too, but none of this has to come at the expense of real people on the end of the phone as so many assume.

    In fact, the role of the customer service officer remains critical, especially since 78% of Australians prefer to contact customer service centres via their phone over other forms of communication when making an urgent or particularly complex enquiry. 

    In such circumstances, customers expect agents to identify specific problems and recommend a suitable solution that puts their concerns to rest imminently. They desire communication with an officer that is flexible, empathetic and caring – and this is something that cannot be replicated via technology. 

    However, organisations must ensure they sustain a balance between relying on customer service teams and deploying self-service technology. For example,  in those instances where customers just need to get a quick answer to a simple question, they are happy to self-serve via chatbots, social media or mobile apps. Using these tools, they receive answers to their questions in real-time without the need to speak to a customer service agent. 

    Long term, this frees the agents up so they can focus on supporting customers with more complex enquiries, and customers can feel satisfied that their questions can be answered easily and efficiently.

    What the enterprise wants

    Yet dealing with complex customer queries can present challenges for enterprises and more specifically, customer service teams. There are many important considerations for these teams when handling a customer issue. 

    They have to converse empathetically – yet firmly – with the customer whilst trying to coax out the root cause to the problem. After this, they have to find the solution and talk the customer through it, whilst remaining compliant and adhering to scripts to ensure they operate within  industry specific regulations. 

    And of course, on top of all of this, customer service teams need to be efficient to drive productivity. But not at the expense of successful customer outcomes.

    So it’s a finely balanced equation – how do you efficiently deliver premium customer experiences with ever increasing complex problems while meeting enterprise and regulatory standards? That’s where technology comes in.

    Technology helps customer service teams, it doesn’t replace them

    Technology driven solutions are critical in supporting customer service teams and ensuring customer enquiries are dealt with efficiently and effectively. Consider the applications of these technologies supporting customer service teams:

    • AI-powered systems analysing customer interactions in real-time to advise operators on language they should use to better serve a customer
    • Sophisticated conversational analytics that understand the context of conversations and are programmed to identify key words and phrases for review
    • Automated quality monitoring (AQM) that provides real-time feedback to customer service personnel (and that can go  back over many years of recorded conversations for audits or issues with compliance, without human intervention -Set and Forget)
    • Robotic process automation (RPA) that removes routine tasks from the operators , freeing customer service teams for higher value activity
    • Cloud-based applications and data analytics that centralise information and enterprise IP

    The key word is support – all these new technologies help support customer service teams to make intelligent and personalised recommendations that rectify every customer query. Both technology and humans are then working towards the single goal of improved customer experiences.

    This pays back doubly for the enterprise. Firstly, the customer is satisfied that their issue is resolved because they were served the correct solution efficiently, thereby having a positive impact on loyalty and retention. 

    Secondly, customer service teams become more capable in identifying the problem and recommending a solution, whilst adhering to any additional regulatory requirements. This not only creates a streamlined process but also ensures that teams feel more supported in their roles. 

    Aligning customer and enterprise outcomes

    Importantly, these technology solutions are seamlessly integrated – all the customer sees and experiences is improved and more efficient outcomes, alongside a more personalised service. 

    For the enterprise, automation streamlines cumbersome inquiries to enhance the customer experience. Customer interactions then become more consistent and compliant, and enterprise IP is better leveraged.

    Ironically, given a lot of what we hear and read, when it comes to automation, the biggest winners are customer service teams and operators. Technology simplifies their jobs, they enjoy improved interactions with customers and colleagues, and the reduction of mundane or repetitive tasks frees them up to be more engaged. It doesn’t take their jobs, it improves them.

    Long term, this will have a profound impact on enterprise success and importantly, it will ensure that every customer leaves every brand interaction feeling like their issues were resolved. 

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    Michael Stelzer

    Vice President, Australia and New Zealand, at Verint Systems

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