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5 Best Practices for Implementing Contact Center Analytics

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Contact center agents working
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Data is the fuel that organizations need to be successful, and that is particularly true for enterprise contact centers. According to recent McKinsey & Co research, companies that have applied advanced analytics within their contact center were able to reduce average handling times by up to 40%, increase self-service containment rates by 5 to 20%; cut employee costs by up to $5 million, and boost the conversion rate on service-to-sales calls by nearly 50%.
 
Yet, that same research states that enterprise contact centers are particularly slow to adopt analytics for two reasons: One, traditional silos have created the inability to have integrated data across channels, and two, contact centers haven’t been able to link analytical insights to action successfully.
 
Having access to meaningful, real-time data across channels can enable contact centers to cut down the barriers of silos, improve performance, and empower sales and marketing managers throughout an organization to better align customer campaigns and maximize sales. However, knowing how to implement an analytics program can be challenging.
 
Transitioning to Real-Time Analytics
Traditional contact centers -- where voice is either the main or only customer service channel -- have long used technology to measure numerous aspects of the customer journey, to improve both customer experience and operational success. Examples include the collection, logging and analysis of data related to key performance indicators (KPIs) such as average call times, average wait times, first call resolution, and call abandonment rates. In the past, these very basic call measurements were primarily generated in a piecemeal fashion, with each disparate system reporting to its limited capability and insight. Contact center managers would have to poll multiple systems cobbld together results to gain some sort of “comprehensive” reporting.
 
But, logging isolated data points can only get an organization so far. Data means nothing without analysis. And as we start to look at the omnichannel organization, things get even more complicated and require an entirely different analytics solution.
 
Knowing how to implement a successful, modern analytics program can be downright confusing. Turning data from multiple channels into actionable insights can become difficult without the proper tools and knowledge to synthesize and present the data in an easily digestible format.
 
5 Best Practices for Building an Effective Analytics Program
Implementing an effective analytics program doesn’t just happen, it takes heavy lifting and buy-in from across the organization. Following these simple best practices can help to smooth out the implementation process and make the task more successful:
 
1. Provide information, not data
There is a major difference between data and information: Data needs to be analyzed, whereas information doesn’t require analysis but rather, it provides a sound basis for decision making.
 
2. Design dashboards to clearly communicate key points quickly
Take into account the context and device on which contact center agents and managers will regularly access their dashboards. Unnecessary clutter can both confuse and hinder their decision making.
 
3. Analysis must be timely and shareable
Contact center managers need to know what is happening in real-time in order to make good decisions. The most effective analytics platforms provide user-defined time parameters that allow contact center managers to recognize, track, and predict trends toward increased efficiency and profitability over a variety of time periods. Effective platforms should also give users the ability to import and process data across other organizational business analytics platforms, for increased visibility and usability.
 
4. Users need control
Different team members have differing goals. A solution should be able to provide the specific analysis each team requires to complete their tasks, so that each department within an organization can isolate the information and trends most pertinent to their role.
 
5. Consider goals holistically, from the entire organization’s perspective
Business initiatives can be strategic, operational, analytical, or tactical. Solutions and processes must be tuned to support each of these business initiatives and activities in order to meet their own various definitions of success.
 
Don’t Forget Security and Compliance
Implementing an analytics program into your omnichannel contact center will pay off with improved levels of customer service and experience, reduced operating costs, revenue generation opportunities, as well as more effective planning and lower customer attrition rates.
 
Whatever analytics solution you select, make sure it is compliant with industry regulations such as the Payment Card Industry Data Security Standard,the European Union’s General Data Protection Regulation, HITRUST standards, and the California Consumer Privacy Act . Strict compliance with these industry regulations and standards will ensure better protection of customers’ personally identifiable information and significantly reduce your organization’s risk of a brand-damaging data breach, while also providing a frictionless agent and customer experience.

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