Call centers are present in almost all business organizations, and they can be seen as the business' data nerve center. Call centers generate huge amounts of data on a daily basis, and this data can provide valuable insights. So, companies are trying to implement analytics applications on top of this data (which is nothing but big data). Owing to this, the result is more insights in customer behavior, which further allows the company to take proper steps to ensure more business. This call center data along with proper analytics can generate a higher ROI.
What Comprises Call Center Data?
In this era of information, the different types of digital media have made consumers more privileged. Every company is competing furiously to get the attention of customers. However, quality goods alone aren’t enough to satisfy the customer. Companies will also need to provide the best customer service in order to succeed, and on a consistent basis at that.
For this, they need to be able to solve the queries of customers. As such, they have established call centers, which try to solve their problems remotely. Because of this, they can collect a huge amount of data, both structured and unstructured. This data can be used by the respective companies to gain very useful insights, which can help in improving customer service, further adding more people to the customer base and producing a feeling of trust among the already existing customers.
Why Call Center Data Is Valuable
The interactions that occur between call centers and customers have a lot of useful information, information which, if utilized properly by the company, can help them gain an upper hand on the market and its competitors. The insights which are gained by processing this data properly can be used in a variety of fields. (To learn about data that is not analyzed, and it's potential value, see How Dark Data Can Impact the Big Data World.)
This data processing can be used in speech analytics, which can help the agents in the call center to respond professionally to queries. It can also be used to analyze the performance of the agent and to pinpoint particular places where improvement is necessary. In this way, it will be able to improve the overall customer service of a company. Also, if the company has an interactive voice response system, then this data can be used to improve its quality, further smoothing out the customer experience.
How Big Data and Analytics Can Help
Big data and analytics can be used to process the huge amount of data from call centers and make good use of it. Some of the places where big data and analytics can help are discussed below.
Through the analysis of data generated by the interaction of the agent and the customer, the company can create predictive models which can help the company in predicting the behavior of the customer and also the trends that will be popular in the near future. This allows the companies to provide even better customer service. (For more on predictive analytics, see How Contextual Integration Can Empower Predictive Analytics.)
Interactive Voice Response
The IVR, or interactive voice response system, can also benefit a lot from big data and analytics. The data coming from the customer
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Getting Even More Benefits
There is still much to be done in order to implement techniques that can benefit a company in the long run. Some of the steps to be followed in different areas are:
If analytics is used properly in a call center's IVR system, then it can become even more efficient. In the IVR system, the following analytical processes must be done for better results:
- Opt-out analysis: Through this, the company will be able to know how many people have opted out of IVR service. This data will help it improve its IVR service. It can even help the company to recognize faulty prompts.
- Reason of calling analysis: This step will help the company to determine the main problems that most of the customers are facing. They will also be able to see if the problem was properly resolved or not.
- Misroute analysis: This step will allow the company to see how many people ended up in the wrong route and had to be transferred.
Some of the steps that can help in enhancing the speech analysis are:
- Real-time issue flagging: Through this machine learning algorithm, the company can track those calls which are at risk.
- Sentiment analysis: This allows the company to easily determine the emotions of the caller in real time.
- Redaction of private details: Private details of the customer can be redacted from the call recording automatically.
What Are the Drawbacks?
One of the biggest drawbacks of using big data analytics in call centers is its price. The price of adoption of big data includes that of the machines required and the space required, which are really very expensive. Also, data scientists have to be hired separately, who have to be paid very heftily. Data scientists are becoming scarce, as every company is trying to implement big data in their business management systems.
Another thing that is necessary to successfully implement big data in call centers, is that the company will have to completely revamp its IT infrastructure. Lastly, the present technologies aren’t powerful enough to help companies realize the full potential of big data.
How Is This Helpful?
Most call centers are actually implementing big data and analytics in some way or another. Many large call centers and newer cloud-based call centers are among them.
They are actually merging both real-time and historical data through analytics. They are now able to predict the causes of customer dissatisfaction, isolating prank calls to save time and identifying the causes of repeat calls. All this data is helping them refine the quality of their customer service.
Big data and analytics are playing a significant role in today’s IT industry and call centers, and will continue to do so. Big data and analytics can be used in many sectors of the call center to improve the initial quality of customer service of the company. It can also help the company to get useful insights on the customers of that company, helping the call center agents to say the right things at the right time. It can also help the company to analyze the performance of the agents in real time. So, it is really has a lot to offer to the call center industry.