When thinking about IVR technology, the elephant in the room (or at least one of them) is the tendency to set everything up then never touch it again. That is, unless something goes wrong.
Many times companies automate phone calls in order to prevent callers from talking to operators or agents. This strategy runs into problems when callers too frequently abandon the automated application for a live person.
It's possible to get the best of both worlds, using automation to reduce the need for live calls while giving callers the information they need. This is where data and analytics come into play. If you don't have a way to monitor an automated voice application, then creating a better user experience comes down to guesswork.
Enterprises that take thousands of calls per day generate a ton of data about those calls. No one wants to make business decisions without good information, and this call data provides that very thing.
Once you have all that information at your fingertips the question becomes: How do I use it? Optimization is the process of looking at the empirical data generated by your automated voice app, understanding how current callers use it, and using that information to create better experiences for them. This is also where best practices dovetail with data and analytics.
Where to Look
One of the first things you want to look at is your average call length. The goal of automation is to provide callers with information quickly. So the longer they stay on the line the further you are from your ultimate goal.
Many things can affect call length. Excessive prompts are one possible culprit. There's rarely a need to have callers confirm every input they make into the system. Data on how many menus callers go through provide some insight here. Having "bargeable" prompts helps reduce call length, too. This is where callers can interrupt, or "barge in," on prompts with their selections before the prompts finish.
If prompts aren't the issue, then look at your call flow. What are the most common options that callers choose? If your data shows you that 90% of your callers are selecting option 5 from the main menu, then you should change the menu order. Replace option 1 with option 5, make option 2 the second-most-frequent choice, and so on. Consistently monitoring your app's data allows you to keep an eye on usage patterns and optimize based on actual data.
Another item to investigate is at which point callers are transferring out of the automated app and connecting to live agents. These transfers can drastically increase average call length. Analytics show you where these transfers occur. Having this data enables you to modify that menu to provide callers with more, or better, information. Think about what callers want to know at that point in the call and how you can give them that information in the automated app.
Getting It Right
After identifying a problem and updating your voice application, analytics help to determine if that change was successful. Comparative data visualization allows users to see trend changes quickly and to correlate those to application updates.
The point here is that analytics aren't a panacea. The information generated by analytics tools simplifies the process of monitoring voice applications. It also helps developers and project managers make informed decisions when optimizing their applications. The goal of VoiceTrends, the analytics toolkit Plum Voice has built into our cloud voice communications platforms, is to promote monitoring and optimization, and to make those tasks easier.
Voice remains a major communications channel for enterprises, and neglecting it constitutes a major risk vis-à-vis customer experience. Having the right data and analytics helps mitigate that risk.
Try one of Plum's cloud communication platforms to get access to VoiceTrends, and start getting the most out of your voice channel.
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