Is your Ring No Answer (RNA) value too high?
If your call center uses a predictive dialer to place outbound calls, you should be aware of Ring No Answer (RNA) time. RNA is one of the few key factors within your control that can determine the performance of your outbound campaigns. It is defined as the duration an initiated call rings at the destination before being killed as a No Answer. You may not be aware that, if your RNA value is too high, chances are your dialer, and therefore your agents, are underperforming.
If asked “How should RNA time be set for maximum productivity?” many people would answer “the longer the better”. This is actually the answer to a different question – “How should RNA time be set to reach the maximum number of people for x call attempts?” This is not the same as productivity.
In our experience, unless you can extract business value from answer machine calls, the optimum RNA setting for your business will fall between 15 and 18 seconds. This holds, no matter whether you are calling cell phones of the under 25s or people living in retirement communities. And as answering patterns are similar worldwide, it holds no matter where you are calling.
Real-life answering patterns
The graph shows incidence of connect time for all connected calls, both live and machine. The data is taken from a large UK-based corporate customer who outsources some of their customer acquisition programs.
The customer had Ring No Answer set to 22 seconds. The sample covers around 30,700 calls answered by a live person.
The red line shows live people. The green line shows machines. As you might expect, median time to answer for human respondents is 9-10 secs, with responses tailing off to very little at 20+ secs.
This particular customer has their agents screening machines rather than doing AMD. You can see that at 16 seconds and beyond the overwhelming majority of calls answered were in fact answer machines picking up.
The red line on the graph clearly shows the phenomenon of diminishing returns. This is obvious in other walks of life but strangely misunderstood in the call center world. Imagine an insurance salesman, knocking on doors. He knows that 9 out of 10 people (if they are home) answer the door within 10 seconds. If he wants to maximize his productivity for the day, he knows there is no point standing at the door for 30 secs. After 10 secs he will try the next house, even though he knows he is turning his back on the occasional elderly person or busy mum who is a little slower than average.
A similar principle (although with more complicated factors) holds true for outbound calling. The question is: how long should you stand at the door?
Looking at the graph, if you carry on ringing past 16 secs, around 90% of consumers will have answered already and your trunks will be tied up waiting with a dwindling probability of reaching a person. Of course, any RNA setting carries the expense of not reaching a certain number of people you might have connected to if the RNA had been longer. But here’s the crunch: if you assign an opportunity cost to those who didn’t answer in time at various RNA settings, you can work out the optimum RNA setting for your line of business.
The bottom line is that every time we have done this exercise rationally and honestly with our customers, we come back to the conclusion that unless you can extract business value from answer machine calls, the optimum RNA setting for your business will almost always fall between 15 and 18 seconds.
The cost of getting it wrong
Trunks are finite resources that must be managed in such a way as to bring maximum return. There is a point at which the probability of reaching a live person is outweighed by the cost of keeping the trunk tied up waiting. The longer you keep trunks open past that crossover point, the more your productivity is reduced. As part of our service contract, we return to our new customers after a week or two of production to check whether settings are right to produce optimum performance. RNA in our experience – and we have seen 45+ secs – more often than not needs to be reined in.
The result of tying trunks up is that agents will be waiting longer between calls and therefore talking less per hour. Our studies have shown that reducing RNA from say 30 secs to 18 secs can produce an increase in talk time of up to 5 mins per agent per hour.
In other words, by optimizing your RNA you could reduce the agent pool by 8.3% and still complete the same workload. For a 100 seat operation, that’s 8 agents, on an annual salary of say £15k, representing a saving of around £125k/ year.