Imagine a person who signs up for cable TV and chooses autopay. A couple of weeks later, she calls to add HBO. The IVR greets her with a reminder that her next payment is due August 1. “Does that mean they’ll automatically debit my account August 1?” she wonders. “Or did my autopay registration not go through?”
What was supposed to be a positive customer service experience for her – signing up for HBO – and a lucrative experience for her cable company – a customer upgrading – instantly turns negative. Instead of simply processing her upgrade request and maybe upselling her on Showtime, too, the company now has the expense of the live agent looking into her billing information. A call that should have been a couple of minutes, tops, drags on for several, and there’s a ripple effect because that agent isn’t quickly freed up to support other customers. On top of everything, this customer will now have her guard up every time she has to interact with her cable company.
This scenario is common. It’s also preventable, but too many service providers, merchants, government agencies and other organizations assume that fixing the problem is too complex and too expensive.
The root cause is one of three Cs that often undermine the cross-channel customer experience: a lack of completeness. Customer information typically is scattered across multiple, disparate databases, so the IVR can’t look to see whether she just recently signed up for autopay – especially if that transaction happened in another channel. If it could, the greeting should have thanked her for that choice and said that the first debit would be August 1.
Connecting all of those databases, or consulting a master log of recent customer contact, solves the completeness problem, but organizations often perceive that project as so intensive and expensive that they keep putting it off. That’s understandable, especially in today’s economy. Even so, the customer experience suffers, and support costs rise because the organization has to spend time – at $1 and up per call – answering questions that didn’t need to be asked.
An inexpensive interim fix would be to take the existing customer profile – the one that has her account number, balance, subscriptions and so on – and simply add a new field so the IVR can see if she’s recently registered for autopay and, if so, what the debit date is. It’s a quick, minor change, but it makes the IVR appear more intelligent to customers, and it saves the organization money by minimizing misunderstandings. Of course, modifications to the existing profile should be limited to a set of known confusion drivers – no interim solution will ever be enough to replace the much needed integration.
Another C is the lack of context: The IVR doesn’t know enough about each customer to provide relevant answers – or the right answer right off the bat. There’s also often a lack of consistency, where a customer uses multiple channels to interact with the organization but gets different answers: one from the IVR, another from the mobile app and still another from the website. As the selection of channels grows, so does the bottom-line cost of the lack of consistency.
All three Cs can be solved by “big data” overhauls, such as developing a cross-channel contact history database, which are a matter of when rather than if. In the interim, however, there are plenty of affordable, quick-fix solutions to minimize those problems.
See Rebecca Nowlin-Green at SpeechTEK on August 14th at 11:45 a.m. – 12:30 p.m during session A202.