Guest blog post by Daniel O’Callaghan from Telax
Consider the volume of data a contact center processes daily. Depending on their customer service model, that information may not only consist of phone calls, but also email, chat, social posts, video, etc. With so much data at hand, it is natural to wonder if and how the majority of these businesses are using BI and analytic data to enable contact center managers and agents to learn from that information and to improve on the customer experience.
More data than many can handle
A few years ago, The International Customer Management Institute, a major provider of resources for customer management leaders, did a survey of 500+ directors and managers involved in this space working in different industries around the globe. After asking participants to describe how they were integrating business intelligence and analytics techniques into their contact centers, with the ultimate goal of improving customer experience, the survey revealed the some interesting observations:
- 67% of contact centers use aggregated data to evaluate agent performance
- However, less than 50% of respondents said their contact centers were using business intelligence to measure improvements in customer satisfaction
- Additionally, 60%+ don’t proactively deliver customer information to their agents
- 41% of agents still manually enter customer contact information into multiple systems
- And 69% of agents have to use multiple applications in order to locate the data they need
Acknowledging and assessing challenges
From a holistic perspective, it’s evident analytics tools aren’t available to a majority of those who interact with their customers most; the front lines agents. This brings up a very important question. If customer service representatives can’t analyze the way they communicate with customers, how are they supposed to be able to figure out what they’re doing right or wrong during their interactions?
On a more granular level, manual data entry processes are not simply slowing business intelligence initiatives; they’re also increasing the amount of time it takes agents to handle each inquiry. When an agent has to spend time entering a customer’s contact info into their database, it ultimately takes more time to satisfy that customer’s inquiry. And the longer it takes, the less satisfied that customer typically is.
While some progress has likely been made since this survey was last conducted, the results are still likely consistent and indicative of changes contact center leaders should all consider taking:
- Implement business intelligence/analytics solutions capable of automatically aggregating, analyzing and inputting finished data into reports, customer profiles and databases.
- Look into using a solution that allow both managers and agents to quickly access data detailing daily, weekly and monthly performance across different communications.
Business intelligence metrics and use cases
In order to operate effectively, business intelligence applications require rules that “tell” them what information to collect and which patterns in the data they need to look for. Seems easy enough, as these rules will most often correlate with a contact center’s key performance indicators. Though for anyone who needs direction on that, ICMI conducted another study that isolated a group of KPIs that have been shown to have helped contact center managers improve performance.
Among the most popular KPI is the FCR, or first-contact resolution. On a surface level, this metric informs contact center workers how many customer inquiries they satisfy during the first interaction they have with their customers. For example, if a customer has to call a manufacturer multiple times to find out how to purchase a part for a model that’s no longer in production, the FCR rate declines.
Here’s an example of where BI tools and techniques could make a difference. If the contact center applied business intelligence analysis to this KPI, managers could not just understand how long it takes agents to satisfy first-time callers, it could also identify obstacles their agents encounter attempting to do so. For example, a database that makes it difficult to locate required parts. Or another that requires the agent to manually reenter customer contact info. Once those hindrances were identified, managers could then restructure contact center workflow and resources to bypass them.
The truth is, there’s far more to applying BI analytics to how contact centers operate, and how to use that data to improve the outcomes and the customer experience than we can cover here.
Suffice to say, the more integrated those analytics are into contact center operations, and the more sophisticated and easy to use the contact center platform is, and the more geared towards improving customer experience, the better. All good food for thought when applying a bit of business intelligence to your own next steps in that direction. You and your customers will find the resulting experience to be positive in more ways than one.
Embracing the Cloud to Support a Multi-Channel Contact Center Strategy
Customers today have multiple options for contacting customer service at companies they do business with. To create a contact center strategy that supports all of these channels – email, phone, chat, etc. – companies with an eye on the customer experience are turning to multi-channel contact center solutions hosted in the cloud.
Telax works closely with EarthLink’s Voice and Unified Communications group to gather client requirements and develop custom contact center solutions that are fully aligned with customer business needs. Together, we work to leverage Telax’s cloud-based call center technology, in combination with EarthLink’s high performance network services, to create an industry leading cloud contact center solution with a single point of contact that is customizable, easy-to-use and provides businesses all the tools they need to offer a world class multi-channel customer experience.