Bridging the Gap Between Customer Expectations and Reality in Telco, with Conversational AI

Bridging the Gap Between Customer Expectations and Reality in Telco, with Conversational AI

This article is co-authored by Sverre P. Jonassen

Meeting the expectations of consumers in today’s on-demand world is by no means an easy task. They often have sky-high expectations and expect the brands they interact with to be ready to assist their every need 24/7 with instant, helpful and personalized service.

This goes doubly so for the telecommunications industry where reducing customer churn is critical and the small differentiations in products and services make it difficult for inexperienced buyers to spot. This leads to a fierce competition where, if a telco is unable to provide a frictionless experience to its customers, other companies are eagerly waiting in the wings, happy to oblige them.

The mantra of putting customer service first and letting the rest follow has never been truer than it is today. Telco companies that lead the market in providing exceptional customer service have a higher recommendation rate, a higher share in deposits, and a far greater likelihood that customers will increase their portfolio of products and services from their operator.

Artificial Intelligence and Chat technologies are now making it easier than ever to help telcos meet customer expectations and assist them where they spend their time most: online. It is well documented that Millennials prefer to use chat as a method of communication over traditional channels – i.e. phone and email – when interacting with a brand. Capitalizing on this trend is necessary to meet customer expectations, but – as with all avenues of customer service – must be handled competently and with finesse or you run the risk of alienating customers and negatively impacting your brand.

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The Leading Causes of Poor Customer Experience

Accuracy of information and time are two key pain points in the customer journey. Customers already dislike being made to wait, and so when presented with inaccurate information, or answers that they didn’t ask for (i.e. false positives), it can cause serious friction.

A study published by the Journal of Consumer Behavior established that customers who have to wait 10 minutes (whether it’s on hold with their telco or in line at a cafe) before being served will feel more dissatisfied than those who wait 10 minutes for their order to be fulfilled – regardless of whether the total service time is the same.

Prioritizing the following should be at the top of the list for any company serious about improving customer experience:

– Long wait times

– Inconsistent experiences across channels

– Slow resolutions times

– Inefficient customer interactions

It is unrealistic to think that these challenges can be simply resolved by staffing up. Telcos today are already struggling to meet support demands, burdened by call centers overflowing with inquiries that result in lengthy queue times and plummeting CSAT scores.

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Bridging the Gap with Conversational AI

In a report from J.D. Power, it was revealed that, even as far back as 2015, chat was clearly poised to become a dominant channel of communication between consumers and brands. 42% of those surveyed said that they preferred live chat compared to email (23%) and social media (16%). Half a decade later those numbers have only continued to trend upward.

This rise in demand for chat has led to drastically reducing deployment costs. Whereas the cost of phone or email ranges between $5-8 per interaction, chat only typically costs between $3-4 – making it a built-in benefit to a company’s bottom line.

Live chat does, of course, have its limitations. It can be difficult to scale human support staff to handle large volumes of incoming traffic. The average wait time for customers to get through to a human chat is 2 minutes and 40 seconds (the same amount of time for phone support), so relying solely on humans to handle all incoming chat inquiries for a large telco is simply not feasible.

This is where Conversational AI comes in. By leveraging Natural Language Understanding (NLU) and Deep Learning, a Virtual Agent can act as a customer service ‘first responder’, automating thousands of requests instantly and carrying out complex transactions (i.e. mobile data upgrades, invoice payment, PUK reset, etc.) without ever needing to involve human support staff.

The benefits of Conversational AI are many:

– Instant service that not only answers any questions customers may have but can also complete transactions that require authentication and backend integrations.

– Scalability for handling spikes in traffic without needing to onboard additional staff. Conversational AI is always readily available and can even be proactive in resolving situations.

Omnichannel consistency is key to large brands. With conversational AI you can leverage optimized support spanning multiple channels with the same level of consistency time after time.

– Cost reduction. Conversational AI is a great way to support strategies towards self-service which can, in turn, lead to significant savings.

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