By Jonathan Wax, VP EMEA Nexidia
Approximately 2.5 quintillion bytes of data are now created every day and it’s estimated that 1.7 MB of data will be created every second for every person on earth by 2020. All this data needs to be processed and leveraged. Through analysis or analytics?
Analysis vs analytics. What are they and how do they differ? Many people get the two terms confused and assume that they are the same thing, but they actually have some key differences.Analysis refers to a detailed examination of the elements or structure of something, while analytics is the discovery, interpretation and communication of meaningful patterns in data. The insights generated from analytics help businesses understand why issues occur and how to anticipate them in the future. Both rely on structured and unstructured data and (up until now) can be either predictive or descriptive.
In today’s age of the customer, more and more firms are using analytics in their contact centres to improve the customer experience and stay one foot ahead of their competitors. If we look back over the last ten years, the use of analytics has been the key customer experience differentiator for businesses and their contact centres. It’s not solely about technology. It’s about how businesses are using analytics to make the most out of their customer data and provide a quality customer experience.
The role of analytics
For organisations large and small, data analytics is having a revolutionary impact. With so much information available, maximising the potential of this data can transform operations as well as deliver tangible business results.
For example, analytics can help contact centres automatically analyse all of their omnichannel customer interactions. The data collected can then be used to optimise average handle times, reduce call volumes, decrease hold times, increase first call resolution rates and even predict problems before they occur – all of which improves the customer experience. These insight-driven improvements can also extend to the agents, providing real-time next-best-action recommendations and automatic alerts when handling problematic interactions. All of these benefits ensure high levels of compliance, reduce risk and deliver ongoing quality control to businesses.
Furthermore, analytics can give managers full visibility into trends, performance indicators and workforce plans to help identify potential and existing issues and skills gaps. This can then feed into evaluations and training. The data can pinpoint performance strengths or weakness and assist managers in giving their employees a roadmap that ensures meaningful growth, and therefore better employee engagement.
Finally, analytics software can also boost productivity by 10-25%. Typical back-office operations max out productivity at around 50-60%, but analytics change this by providing a holistic view of operations, highlighting process inefficiencies and suggesting time-saving alternatives.
Descriptive and predictive analytics have already proved their value in predicting customer interactions and questions, but there is still more to come.As the market develops further, prescriptive analytics will come to the fore,which will further provide employees with intelligence on what they should do next or tips when engaging with customers to improve interactions.
Prescriptive analytics builds on descriptive and predictive analytics. It explores how different approaches affect a result and what the best practices are in specific situations, giving businesses the ability to automate decision-making. Generally speaking, prescriptive analytics offersa way for businesses to efficiently use limited resources – providing business benefits that might not otherwise be realised. For example, agents can be indicated the best next step when dealing with a difficult customer based on that customer’s past interactions, and his or her chances of leaving you for a competitor. If the chances of that customer switching for your competition are high, prescriptive analytics might respond by suggesting that the agent offers a discount, or maybe a refund.
Prescriptive analytics can also help managers better manage and engage their workforce. AI-driven analytics can be used to point supervisors towards areas where performance can be improved and facilitate personalised, measurable and engaging programs that empower employees to achieve their personal objectives.
One step ahead on the experience race
Analytics offers many benefits, but central to its value is the ability to use data to understand the challenges or opportunities of the past. Analytics can help businesses uncover potential trends, evaluate the performance of certain tools and platforms, or investigate the potential effects of specific events.
As the competition for customer attention continues to intensify over the coming months and years, being able to provide an excellent customer experience will become even more important. By equipping their contact centres with powerful data analytics platforms, businesses will be able to maximise their data,boost customer satisfaction and loyalty and, ultimately, increase their bottom line.