The Growth Of Self-Service Technologies
Every time we take cash from an ATM machine, fill up our car at automated petrol pumps or print out a boarding pass at the airport, we are using some form of self-service.
The three keys to a satisfactory self-service transaction, from the customer's viewpoint, are:
Lessons From The ATM Machine
If we examine the information flow at an ATM machine, we can see one of the reasons why they are so successful. First, ATMs are limited in what they offer. You can't increase your overdraft facility or enter a new direct debit at an ATM machine. The restricted number of services available increases both reliability and speed. There are only a few inputs required from the customer (a card and a PIN number), a limited number of choices (check your balance, withdraw cash), a very small number of steps to get to the outcome, and a limited number of outcomes.
The inputs from the customer are a highly structured combination of machine-readable data (on the card) and a very small number of PIN digits to key in on the keypad. There is very little scope for misunderstanding in the transaction, and, even if you enter the wrong PIN number, you usually get at least two more attempts to get it right.
Basic Self-Service Contact Centre Applications
Contact centre technology can cope with these kinds of self-service transactions well because of the highly structured data in the information flow. To pay your credit card balance by phone, for example, you might select this option from an IVR, key in your credit card number, your date of birth and pass key, your debit card number, expiry date, security code and the amount you wish to pay. All of the data involved is numeric.
Comparing this kind of self-service to an ATM machine, it scores well on availability, high on reliability (because the communication is highly structured), and perhaps rather less well on speed, since you have to go through several steps and key in 40 to 50 digits once you get through to the contact centre.
Voice Recognition And Self-Service
Let's look at a very simple example of one such interaction: finding train times. In this application, the contact centre application needs to know:
These kinds of self-service applications already exist. Typically, they offer times only for direct trains on the day of your call (thus limiting the level of service offered, and simplifying the transaction, like an ATM machine).
The first question that such an application asks callers is the station from which they are travelling. Typically, the application has two attempts to recognise the station name. If it fails to recognise the name of the station, it invites callers to key in the first few digits of the station name on their telephone keypad.
Clearly, this might not be particularly convenient if you are rushing to the station on foot or by car. Where there is considerable background noise, the reliability of train tracker's recognition falls. Under these circumstances, it can be tempting to hang up to and dial an alternative number, which uses live operators.
This illustrates the main problem with voice recognition technology: although it has made considerable progress over the past 10 years, it is still not 100% reliable. Indeed, in circumstances, its reliability is nowhere near 100%. As a result, applications that, on the face of it, should be a boon to customers, fail the reliability test, and can cause frustration.
Huge strides have been made in recognition accuracy, dialogue design, grammar compilation and noise reduction, to the point where a well designed application will now get near 100% accuracy for 'in-grammar' responses. Most inaccuracy therefore derives from the caller responding to a question with an 'out of grammar' response.
So, for example, let's say an application asks you for your postcode. If you say 'RM14 6FB,' a well-designed application wouldn't normally have a problem. But if you say 'R…..M for mother…… fourteen…..six…..Foxtrot…..er, B as in bath,' even though that response would make perfect sense to a human, it will send a speech recognition application into a flat spin.
People, on the other hand, are extremely skilled at dealing with these 'out of grammar' responses. The challenge for the industry, therefore, is to create close integration between speech recognition and call centres that will lead to a much better customer experience. However, the overall customer perception must not be one of speech recognition failing then agent helping out. Given the right integration the callers' perception can be one that the speech recognition is always successful – and therefore they do not feel as though the called party has tried and failed to automate their call.
Vonage (NYSE: VG) is a provider of communications services connecting individuals through broadband devices worldwide. Our technology serves approximately 2.4 million subscribers. We provide communication solutions that offer flexibility, portability and ease-of-use. Our Vonage World plan offers unlimited calling to more than 60 countries with popular features like call waiting, call forwarding and voicemail - for one low monthly rate. Vonage Holdings Corp. is headquartered in Holmdel, New Jersey. Vonage is a registered trademark of Vonage Marketing Inc., a subsidiary of Vonage Holdings Corp.
Published: Wednesday, April 19, 2006
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