Time -- every business is (or should be) concerned with it. Working hard is important, but working smart, especially with your usage of time, is what can set you, your call center team, and your company apart.
One of the greatest time drains on call centers is the way in which quality is measured. Spreadsheets are holding back call center QA progress. While they do serve some purpose, most notably the recording of static data, they are largely inefficient and unable to scale as your call center grows.
Scores and data must be collected, analyzed, reported, and then decided on before the cycle begins again. Regular reporting is an essential part of call center management used to:
- Record call response data
- Track sales conversions
- Measure employee performance
- Collect and analyze Net Promoter Scores (NPS) and customer service feedback
To collate, measure, and make quality business-driven decisions with a spreadsheet is incredibly limiting. Not only does this take more valuable time, but with manual inputs of data and formulas errors are far more likely to occur.
Why Switch from Spreadsheets to Automation for Call Center QA
Every manager or business owner should immediately know the numbers. Day-to-day data matters, but, as any call center or quality assurance manager knows, it is often most useful when key performance indicators (KPIs) are tracked with their performance examined over time. Trends must be appropriately identified in order for business to improve. Without a proper call center QA process which includes quality assurance scorecards and tools for measurements and reporting, improvements in processes and performance cannot be made.
Guessing on key decisions and prioritization is not in the best interest of any call center’s management model. The data exists – data on agent performance, sales statistics and trends, client retention rates -- use all of it to your advantage. While spreadsheets only get you so far, automated dashboards may be manipulated, sliced and diced in a variety of ways with a click or two. No complicated formulas and no nonsense. Here are the top four reasons why you should be using automation, not spreadsheets, for call center QA.
Leaders need to know how well their call center performed this December compared to the previous December. Whether you are most interested in year-over-year, quarterly, monthly reporting, or all of the above, only a database and secure, time series data stored in a system designed for that purpose, enables data to be retrieved in real time. With a significantly lower margin of error, automation saves time by removing the need for manual spreadsheet inputs that may not even be accurate.
Call center and quality assurance managers can refer to automated data in real-time and be prepared to make quick, informed decisions as necessary. Meeting with senior management? No more spending days prepping decks with questionable statistics. Get what you need at the click of a button.
Automated analysis also streamlines the call center employee review process. With less guesswork and more data, both agents and managers are better informed about performance. Both parties will quickly see if performance is trending in a good direction or one that leaves room for growth. Identifying a call center agent’s strengths will more immediately and transparently present issues and accolades up front thus resulting in higher agent engagement and ownership in their performance.
Get real-time analysis
With automation, gone are the days of waiting for the spreadsheet to be updated. With dashboard access, anyone who has permission can see whatever real-time data they wish to view. This data may also be exported or shared in any way that is most efficient for the management of your call center.
If you’re interested in growing, or even maintaining the status quo of your call center’s overall performance, automation is not a nice-to-have, but an absolute must-have.
So many call center decisions are rightfully based on data. It only makes sense to optimize gathering, analyzing and reporting on data for maximum returns.