Big Data

Big Data in your call center: Managing the numbers

The data collected by your call center software is huge and varied. But which metrics matter and how can you make changes based on those metrics?

The data collected by your call center software encompasses a wide variety of metrics: time spent on hold, call abandon rates, transfer rates, conversion rates, and cost per call. In fact, there is so much data available within your system that it can be difficult to manage your numbers effectively. Which metrics matter? How much do they matter? How can you make changes within your center in order to produce improvements in specific metrics?

Utilizing big data in your call center can help you establish baseline metrics, identify areas within your center that require improvement, and help improve your efficiency overall.

Prioritizing metrics

Of the many metrics you may be tracking within your call center, two of the most important performance indicators you will come across are your first call resolution rate (FCR) and average handle time (AHT). These rates are often in conflict with each other, and your decision to prioritize one over the other should be based upon the particular functions and goals of your center.

Your call center's FCR is a measurement of how well your agents provide your customers with a solution the first time they contact you. The more your customers have to call back in order to find a solution to their problem, the lower the quality of your customer service. A low FCR incurs higher operating costs as agents repeatedly interact with the same customers.

FCR can be a difficult to objectively track. You may have to rely on customers to self-report their satisfactions via phone, web, IVR survey, end-of-call survey, or voice menu. You can also use your CRM system to see whether individual callers have called multiple times or only once.

The average handle time metric tells you how long your agents are on the phone with customers. The lower your AHT, the less time your representatives spend on the phone with each customer, and the les each customer costs. Working to lower your AHT can also decrease your call center's operating expenses, reduce the number of agents you need on staff, and reduce customer wait times in the queue.

Applying changes

By tracking and analyzing your performance metrics, you can gain the insight into your call center that you need in order to effectively change your processes for the better. Whether your goal is to increase customer satisfaction or reduce costs, any attempts to make improvements should be informed by the data you glean from your call center's analytics.

  • For the average customer contact center, a 1% improvement in FCR would result in a $276,000 reduction in annual operational costs (Bluewolf). You can improve your FCR by providing your agents with more training and coaching to increase their knowledge and ability to solve customer problems.
  • U.S. call centers receive 45.4 billion inbound calls per year, and each call costs, on average, $5.90 (Zendesk). You can reduce the cost per call by working to reduce your AHT. Optimizing your inbound call center's script to include answers to frequently asked questions and other scenarios can help bring down your AHT.

Your call center analytics can also help you schedule your agents more effectively by predicting call volumes by day and hour. You can then schedule your employees so that you have enough agents on the clock to handle the volume of incoming calls without any idle time.

Keep track of when you start making changes within your call center and assess how effective they are at improving performance as compared to your baseline. This can help you determine whether your changes are worth the effort, or need to be modified for greater efficacy.

Megan Webb-Morgan is a business blogger for Resource Nation, a lead generation company that targets the business-to-business marketplace.

2 comments
ravincap
ravincap

Well written article. Often times, the both transactional & non-transactional data resides outside of the network (esp. in a third party call center). Also, to leverage Big Data & Analytics effectively in contact centres, following investment is a pre-requisite: 1. Data Centre 2. Data Warehouse 3. MDM, BI & BA strategy 4. Hardware & Software: In memory databases & analytics servers, HADOOP, R, SAS etc 5. Executive sponsorship

Zahra B.
Zahra B.

Actually, adding stuff to the script (I'm assuming this is the script agents should follow when they receive a call)shouldn't be the way to go. Train the agents on asking yes/no questions (or questions with few possible answers) instead of open questions, and how to re-direct and re-focus a client to the matter at hand. However, if the script includes the automated part where you "Press 1 for English", etc. there is some efficiency to be gained in adding pre-programmed answers. For example, my local internet provider/cable company will have a "There is a problem in your area and we estimate it will take an hour to repair" message before putting you on the queue for an agent. That must save them countless calls.

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