Companies are being inundated with data about their customers, which is being churned out by myriad internal systems as well as external outreach (social media, for example). The Internet of Things, with millions of connected devices and sensors, is exponentially increasing this data flood.
One major – though often overlooked – data source is the interactive voice response (IVR) system used by most contact centers to handle phone-based voice self-service interactions. Thousands or millions of calls per month to the contact center generate huge volumes of customer analytics information – a rich but potentially overwhelming resource.
The trick is making sense of this data, and powering it for your organization. If that’s the case, is too much data really too much?
Stepping stones to insight
Let’s say you are trying to cross a river, and you are carefully trying to make your way across a path of stepping stones so you don’t fall in and drift away. Keeping on the path gets you more efficiently to your goal of crossing to the other side.
Now take that same scenario and apply it to customer analytics. The data maps out a story that tells you what you need, but one small miss – like overlooking a key insight it can reveal to you – sends you off a clear path, missing the step that could solve a customer or operational issue.
By itself, data has limited utility. For instance, an IVR typically records reams of data points about variables such as how often an individual places a call, which language most callers prefer, what actions they take and how many calls per month are transferred to a live agent.
But without analytics tools, and a true understanding of the data’s value, it’s difficult or impossible to navigate through a wilderness of individual facts to gain the prize: insights that can guide business decisions, both tactical and strategic.
Consider these two scenarios:
- A customer calls in via the IVR and needs additional assistance from a live agent. All the data about that customer’s current and past interactions -- what menu selections she made, her behaviors and preferences – remain locked away in the IVR’s database. When the agent picks up the call, he starts with a blank slate. The result? Frustration for the customer at repeating basic information, extra work for the agent and higher costs for the contact center.
- In the second case, when the customer is transferred to the agent, the IVR delivers her history, in summary form, via computer/telephony integration (CTI) so the agent is prepared with the background needed to tackle her current issue, rather than ask her for information that’s already captured by the IVR. The result? A faster, more personalized interaction that pleases everyone.
There’s another aspect to this example. When voice self-service is adaptive, it constantly applies data that has been compiled and analyzed by built-in tools to personalize the customer experience. The system automatically learns from past encounters and uses that information to deliver customization such as language preferences for the most basic personalization functions, and for more advanced IVRs to adapt menus and even adjust interaction speed, among other parameters.
One important benefit of IVR analytics is spotting issues and trends. Over time and many, many calls, the masses of data collected during every interaction point in the IVR can be analyzed to produce both a story of each individual and a collective picture of usage patterns, problems and trends across many individuals. Think of it as connecting millions or billions of dots to form a detailed map that can point to:
- Reasons why customers call the contact center
- What actions most customers take within self-service
- How long they interact with the IVR
- What seasons, days or times are most popular for calls
- How frequently customers use self-service and disconnect vs. requesting transfer to a live agent
- Delays or bottlenecks in systems or processes
When you combine IVR data with information from a workforce optimization (WFO) solution, the opportunities for trend and issue identification rise exponentially. Analyzing data from the front end of the customer interaction (the IVR) and the agent-side of the interaction (the WFO) can yield cause-and-effect insights that are priceless for understanding and supporting the customer journey.
For instance, it can show a direct link between a downward pattern in self-service and a rise in agent costs due to heavier workloads, plus higher turnover due to burnout. This finding should trigger an investigation into why customers are abandoning their interactions in the IVR and relying on live agents. Analytics may reveal a system glitch, an unforeseen spike in traffic or another factor to be resolved.
Driving better business decisions
How can contact center executives take full advantage of rich IVR analytics?
- Increase customer experience
- Improve operational efficiency
- Control costs
- Optimize agent resources
- Strengthen fraud protection
- Orovide justification for capital expenditures
Here again, IVR analytics turns data points into business intelligence, providing a fact-based roadmap to follow in making informed decisions about staff resourcing, technology upgrades and other improvements. The most powerful IVRs also offer reporting capability that enables managers to easily visualize and present findings from data analysis.
Getting a handle on IVR data
IVR analytics can cut through the maze of data and help organizations “see the forest for the trees.” Analytics are the key to transforming disparate facts into insights that can keep contact centers operating at peak performance and delivering a great customer experience.
According to CustomerThink, a global online community of business leaders, Top 5 Contact Center Trends for 2017 research reveals that even with all the technological options today, the majority (79 percent) of customers contact a support center via phone. Voice remains vital, and it’s critical to make the best use of data generated by this channel.
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