How to Use Analytics from Call Center Software to Improve Collections

Despite its unpopularity, the debt collection industry continues to grow. Nearly one in 10 Americans have a minimum of one debt in collection whether it is for medical bills, mortgages, credit card debt, student debt, or automobile loans. Businesses are placing more debt with collection agencies than ever before, and aggregate household that is still rising – portending a need for debt collection agencies long into the future. Even without a recession, debt recovery services are a big business. However, collection companies need to do a lot to improve their collections rates and move into the era of big data that is generated by their own call center software.

Understanding Big Data

 Big data is the stream of large datasets that can reveal a lot about human behavior, including patterns, associations, behavior, interactions, and even marketing trends. This type of data feed is so massive that it needs to be analyzed through computer algorithms to make much sense. In a highly competitive marketplace, such as the collections industry, analyzing customer data through the use of call center software offers a competitive edge. Let’s look at some of the ways that call center software can analyze raw data and improve collections rates.

1. IVR Data: When a customer calls back, odds are they will be greeted by an IVR. Interactive voice response is an industry standard and helps to route the customer to the appropriate agent in the appropriate tier. However, many of those who come into contact with IVR immediately assume that their experience will not be a good one. By using IVR analysis, collection firms can improve the customer experience and mindset. For instance, by analyzing IVR data to find out which prompt causes the most clients to opt out of IVR by hitting 0 to reach a live human.
   
   
2. Speech Analytics: Speech analytics cannot only help you identify a customer’s tone and emotion, but can also identify customer frustration, anger, and patterns of silences that can indicate when an emotional explosion is about to take place. Even better, speech analysis can be used to identify which agents may need more training and encouragement to hone their skills and become more effective.
   
   
3. Multichannel Analytics: Everyone has a profile nowadays. Collections targets are on Facebook, using Twitter, and all over Instagram. They use email, text, and video chat to reach out and communicate. Your agency should do the same and meet the people that you are seeking where they are.
   
   
4. Predictive Analytics. Predictive analytics are not a crystal ball, they simply identify the most effective approach to a client based on their activities and history. Predictive analytics can also identify when inbound traffic is likely to spike, which customers should be routed to what agents, in which agents are going to be the most effective in a given situation.
   
   
5. Performance Analytics. Call center managers and supervisors need a much more hands-on approach to data. They need to be able to access data as it happens and compare it with historical data in context. They can use this to figure out staffing levels, which agents are better at handling difficult customers, which agents are being more passive, and which are being proactive. Every business wants its performance to be top-notch, not only for their customers, but for their own internal benchmarks.
   
   
6. Agent Workstation Analytics. Giving agents robust tools to analyze their clients is a win-win situation. Client benefits from a faster and easier interaction, and the agent is exposed to less stress. Collections are a sensitive matter, and by using agent workstation analytics, the agent can call up the client’s history, current file, and notes from other agents who have interacted with the client previously. With input from supervisors and managers in real time, agents know that they are not alone on the firing line.

Call Center Software Needs to Step Up

Working with a call center software provider is not enough. The company needs to be innovative, and ahead of the latest trends in data analysis. While your current software is sitting there collecting data, you might not be able to do anything with it. That takes specialized algorithms to sort through the data and make sense of it all. Large datasets are not easy to analyze, which is why best call center software includes robust analytics that are intuitive, and easy to use.

Staying on Target – Not on Top of Your Software

In addition to needing robust analytics, collection agency software needs to stay up-to-date on the latest rules, regulations and laws. Most importantly, debt collection companies need to adhere very closely to the regulations set forth in the Telephone Consumer Protection Act. With a top-notch software and recording capabilities, even more data can be analyzed and evaluated for future use.

Get Your Data Out of the 20th Century

Call centers as a whole operated for many years without making much use of the data that came through with every call inbound or outbound. At the bare minimum, they knew how many deals were closed by the end of the month, and who close the deals. There was very little else to go on. Many call centers were not computerized until the early 2000’s, and those that were did not have robust analytics that could be used to further refine their operations. By computerizing and partnering with an experienced call center software vendor, even small businesses can realize the benefits of big data.

Open Source Can’t Cut It

Open source call center software is often free, or very low cost. However, in terms of call center software the saying that “you get what you pay for” definitely applies. Open source software does not automatically update, and while you can apply your own bells and whistles to the source code, there is nothing that says it is stable, secure, or will operate as advertised. That takes a professional call software company that knows and understands the call center in collections industries. Working with ChaseData means that a collections company has an industry-experienced leader at their fingertips, ready to break down that data into better collections rates.