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From chatbot to conversational AI: why customer service needs to change

A wide range of factors have combined to heighten competition in retail banking in recent years, most linked to the digital revolution.

From chatbot to conversational AI

To start with, traditional “high street” banks are facing stiff challenges from digital-only start-ups such as N26, Revolut and Curve. On top of this, most customers have moved to online banking – and their expectations of great customer service have risen as a result.

The latest data from PCM’s Digital and Card Payments Yearbooks 2021-2022 shows[1] that more than two-thirds of customers across Europe now use digital banking – writes Sebastian van der Meer, Country Manager DACH at e-bot7.

In Germany alone, the proportion of customers banking online has been rising at around 2% per year for the last twelve years, a rate that increased last year such that almost 60% of Germans now bank online.

Digital banking holds the promise of 24/7 service provision, with customers being able to access their accounts and purchase new investments and other banking products around the clock.

“Banks with the highest degree of reported customer satisfaction found that deposits grew 84% faster than at the banks with the lowest satisfaction ratings.” – McKinsey & Co

From a banking perspective, digital banking means the potential for more revenue and increased cross-selling – provided they can get online customer service right. A recent study from McKinsey & Co[2] revealed that banks with high customer satisfaction see deposits grow 84% faster than those with unhappy customers.

The customer service dilemma

To cope with this influx of always-on customer demand, which has seen up to a third of customer enquiries placed outside regular working hours, banks and insurance companies have turned to automated customer interaction tools.

These “chatbots” have acted as a front-line customer engagement tool and have been around for at least a decade. However, such tools have not always been successful, with customers expressing frustration during long wait times and poor interpretation of their requirements.

“There’s huge demand for technology that can accurately interpret customer needs and provide relevant and timely information on those needs.”

Even worse, from a customer point of view, chatbots often misdirect enquiries referred for human interaction to the wrong team, leaving human operators unable to answer customer enquiries.

Given the complexity of most financial institutions’ product suites, there’s huge demand for technology that can accurately interpret customer needs, provide relevant and timely information that meets those needs, and refer calls to the right operators where necessary.

Conversational AI: next-generation customer interaction

Step forward Conversational AI, or Artificial Intelligence. Launched in 2016, Conversational AI works by doing away with the rules-based approach adopted by chatbots, interpreting customer needs based on their neuro-linguistic patterning.

In plain language, this means working out what customers want from how they are using words, rather than simply identifying keywords like “car insurance” and providing information on that product. What’s more, Conversational AI learns from each customer interaction to improve the accuracy of its responses.

e-bot7’s Conversational AI platform for customer service has successfully achieved automation rates of between 85-98% for our clients, a level of automation that reduces the need for expensive and time-consuming human interaction.

Such high rates of automation have been realised by more accurately interpreting customers’ needs and rapidly referring customers to relevant product information and application processes.

Where human interaction is required, the better interpretative capabilities of our Conversational AI tool mean interactions are more effective, something that improves both customer satisfaction – and employee satisfaction with their jobs.

The e-bot7 system provides analytics in more than 75 different areas, from the number of customer drop-offs in-chat through to the type and number of queries answered for each product area, and length and quality of customer interaction.

Based on this data, it’s possible for financial institutions to look to improve their products and identify new opportunities. A few clients are already using e-bot7’s Conversational AI platform to generate new business leads based on customer needs as expressed during chats.

As competition heats up and the battle to retain customers in a digital environment intensifies, Conversational AI has a key role to play.

Visit e-bot7 to find out more about next-generation customer interactions online

[1] See The Digital and Card Payment Yearbooks 2021-2022

[2] See “Reimagining customers engagement for the AI bank of the Digital Future”, McKinsey & Co


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