January. 29, 2019 posted by Foehn

Modern contact centres are pumping out data and analytics more than ever. Real-time monitoring and detailed historical reporting offer a powerful opportunity to enhance customer experience and raise agent productivity to new heights.

All too often, though, that opportunity isn’t being realised. The problem arises from system vendors that compete to deliver a seemingly infinite range of data and analytics. Meanwhile, overwhelmed contact centre managers are finding that you can get too much of a good thing and opt to put-off implementation.

Under constant pressure to deliver on KPIs, managers risk analysis paralysis by attempting to graph and chart every ounce of data. At the other extreme, many managers are faced with a challenging contact centre environment where time is the scarce resource and exploring data analytics is always something for tomorrow. It’s a chicken and egg situation where analytics can create efficiencies and save time but getting to that point can require a significant investment of time up front.

To help break that cycle, here’s your need-to-have priority shortlist of the essential data and reporting that you should be using, whatever the size and type of your business. After that, we highlight the nice-to-have capabilities of Interaction Analytics, a powerful addition for businesses that want to go beyond asking ‘what?’ to explaining ‘why?’.

Analytics Essentials

  1. Analyse your IVR stats to find out where callers are dropping off or abandoning the call, then adjust call flows to suit.

  2. Identify and classify your calls to identify common issues. Then allocate agent resource accordingly and accelerate caller response time.

  3. Analyse contact handle times and identify abandoned or missed calls. This can identify agents that may need training.

  4. Monitor your voice application interface. Track hang-ups, visits, time spent on a page, and other indicators of trouble spots.

  5. Use a funnel view to track callers going through the system and identify entry points, exit points, frequently visited areas and hang-up points.

  6. Set up agent performance reports to monitor statistics such as talk time, consult time, hold time, waiting time, busy time, ready/not ready time

  7. Create a dashboard of all core metrics – queue and agent activity, total calls by time of day, average call duration, etc., allowing you to schedule agents optimally and improve SLAs.

  8. Schedule historical reports to see how call metrics change over time for IVR, agents and routing.

  9. Customise reports and dashboards for real-time monitoring and create interactive, multi-tabbed dashboards from multiple data sources.

  10. Automatically share reports via email to all major stake holders to gain insights and requirements against KPIs.

Interaction Analytics

Your business contact centre deals with a multitude of interactions – verbal and written conversations that hold valuable insights into trends, issues, customer behaviour and business performance. The challenge is to uncover those insights from such a vast number of interactions covering such a vast range of issues.

Traditional metrics like those mentioned above are essential but don’t provide information about what actually occurred during the conversations. Likewise, customer surveys are excellent for measuring performance against KPIs but, generally, relatively few customers respond. On its own, the survey does not explain why a customer gave a certain score, nor does it indicate the root cause of a problem. Furthermore, traditional quality management programs usually listen to randomly selected calls but struggle to review more than two percent or so of calls, whilst chat or email are usually handled by separate systems and reviewed even less extensively.

Interaction Analytics go much further. The most effective systems combine speech and text analytics in a single application to enable users to search for keywords across all interactions and all channels of contact. Speech-to-phrase recognition is an enhancement that directly recognises entire phrases within the call audio itself. This avoids converting the audio to text first, prior to searching for key phrases, a process that can lose data and compromise quality. This means conversations can then be categorised accurately according to topics, in order to identify emerging trends from discussions with the customer. For example:

  • Identifying critical skills that agents can use for skills-based routing.

  • Analysing calls to identify the root cause of a problem, like high handle times.

  • Identifying types of contacts that could be handled using self-service methods.

Interaction analytics will also expose the unexpected – things users wouldn’t have searched for – and ensures you can analyse all conversations, not just a small percentage. This is crucial to meet the growing number of communication channels used by consumers today.

At Foehn, we maintain a philosophy of building cloud communications that are uncluttered, simple to use and, therefore, cost-effective to manage. Now, more than ever, contact centre managers should consider this approach in combating the growing complexity of contact centre functionality, not least data analytics.