Guest Blogger

Debbie Nolan, Business Development Director of CRM Solutions, UK & Ireland, Arvato

When digitally-savvy consumers contact a brand for customer service, they expect a consistent, seamless customer journey across a broad range of contact channels, and to have their queries resolved in a fast, personalised way. Research suggests that many businesses are struggling to keep pace with these expectations. A recent survey from KPMG found that 88 per cent of CEOs are concerned about the loyalty of their customers, and according to Avaya and BT, only one in five consumers have their issue resolved first time when contacting a brand.

Part of this problem lies with the information available to customer service representatives, who often only have access to basic data about the customer they are speaking to – such as their name, address and most recent purchase. Providing customer service teams with insight into the customer’s habits, expectations, preferences and previous contact would help to create more genuine, personalised interactions that get to the heart of an enquiry quickly. With the number of customer touch points increasing as businesses offer multiple contact channels, this data is often buried in disjointed systems and databases across the organisation.

A virtual supervisor

Cognitive technology is set to offer businesses an opportunity to address this, alongside delivering new efficiencies and boosting productivity. It’s already revolutionising the transport industry through the development of driverless cars, and its potential applications for the customer service sector are myriad.

The technology itself has the capability to collate and draw on big data and build it into the everyday interactions employees have with customers, giving contact centre agents a comprehensive view of a customers’ habits, purchasing decisions, preferred channels and previous contact. Cognitive systems, such as IBM Watson, that can understand and interpret natural speech and quickly collate data from each customer contact point, can share this information and recommend actions to agents in real time while they are speaking to customers over phone, email, webchat or social media.

Armed with this real time information, agents will be able to anticipate everything from intention to buy to preferred contact channels and provide the customer with a better service. For example, if a consumer gets in touch with their mobile phone provider to complain about a data charge, the virtual supervisor will automatically recognise any error and recommend a solution to the agent with tailored advice on how to handle the individual customer and which channel to use. To do this, the system will instantly evaluate a range of data, including the agreed terms of the customer’s contract, details of any previous complaints and if they have already tried to resolve the issue independently through another contact channel. Receiving fast, relevant support will make the customer service advisor’s job easier, and more importantly, enable them to anticipate a customer’s needs.

But it won’t stop with collating and providing information. By training the software with stock responses and feeding it with extensive data from manuals, glossaries, customer histories and information from previous customer dialogue, cognitive systems will be able to provide answers to specific questions autonomously through webchat and social media. Together with processing the data, it will also be able to use it to form new rules that dictate how it reacts to a certain line of questioning, ultimately enabling it to determine the most likely answer to a growing number of customer enquiries within a fraction of a second. By continually reducing the burden on agents, they’ll be able to dedicate more time to complex customer enquiries that require human decision making, such as solving complaints and restructuring contracts.

Autonomy today

While this may seem futuristic, we’re already seeing the technology make a difference. Early implementations of these systems have enabled businesses to start using complaint data from dissatisfied customers to automatically improve certain areas of a business, such as errors on a company’s website. By systematically recording which issues and problem areas prompt customers to contact the organisation and flagging the most frequent, employees can prioritise improvements and reduce the contact volume in service centres.

Cognitive technology is also being introduced to filter customer enquiries through to different departments. For example, by recognizing grievance in the language of customer correspondents, the software can relay these concerns through to the appropriate advisor, ensuring issues are resolved quicker.

These applications are just the beginning. As the technology develops, we can expect organisations to implement it across more and more of their customer service operations as they bid to deliver excellent experiences. However, while the concerns around cognitive technology focus on the potential impact on workforces, it’s clear from the 2015 Omnichannel Monitor research – a survey of 1,000 consumers conducted by Arvato CRM Solutions and CSC – that customers will predominantly want to continue interacting with a real person. As such, we can expect to see human and machine working together, with cognitive technology acting as the supportive tool.

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