Tracking Performance Data With Digital Debt Collection

By on October 21st, 2019 in Data Science, Product and Technology

Call centers are notorious for reaching hundreds, if not thousands, of consumers several times per week (and even several times per day!). The debt collection industry is plagued by the perception that collectors are relentless and uncaring, which makes resolving debts even more challenging. Digital debt collection strategies aim to alleviate the stress of incessant calling for consumers, and also provide unique, powerful solutions for creditors.

Collection metrics

Digital-first debt collection strategies provide creditors the ability to track and aggregate more objective performance metrics that help strengthen their collections strategy. Qualitative metrics from traditional call centers are still subject to the endlessly variable human element of a phone call. 

When outreach is entirely automated, it becomes easy to A/B test simple changes (new subject lines, different greetings, etc.) and determine which are the most effective. But how do we define effectiveness? At the end of the process, an effective collections strategy is one that leads customers to make a payment. 

There are a few key metrics that call centers use to drive customers to this end goal that can be easily supplemented or overtaken by digital collection strategies.

Calls per account and calls per agent

Traditional collection agencies, like any other sales call center system, track the total amount of calls made to each customer and by each agent on the team. When individual agents are responsible for contacting customers, they have to hit an outreach quota. This quota reflects directly back on the calls per account, or how many times an individual customer has been contacted. 

As agents are required to call customers and collect on accounts, the calls per account may increase to a point where customers feel overwhelmed and over-contacted (which can even lead to symptoms of anxiety and depression). At the same time, if countless calls are being made, and an account is not paying, there is a clear gap in effectiveness. 

One of the advantages of a digital debt collection strategy is that agencies can reach customers with relevant messaging at times that work for them. This can include hours in which call centers are no longer legally allowed to reach a customer—before 8am or after 9pm. With these legal limitations in place and the need for agents to meet quotes, traditional collections strategies encourage an artificial inflation of outreach numbers that may not be positive.

Hit rates, percentage of outbound calls resulting in promise to pay (PTP), and call quality 

Call volume is not the end-all-be-all of call center metrics though. Simply tracking output numbers isn’t enough when engagement is the key metric. Hit rate is defined as the total number of calls divided by number of those calls that are answered by customers. While this number can be helpful in narrowing which calls were more successful than others, it cannot reach the same level of detail as a full digital strategy.

In the case of a phone call, there are limited options once the phone has been dialed:

  • The customer does not answer
  • The customer answers but ends the call before promising payment
  • The customer promises to pay

Trying to understand what leads to a successful payment on a call is then dependent on the agent’s perspective. Digital debt collection conducted through machine learning is able to communicate using personalized and consistent content. Hit rate, PTP, and call quality analysis can then be expanded on, and performance can be measured by:

  • Email Deliverability
  • Email open rates
  • Link click rates
  • Website engagement (Including clicking on further links, filling out forms, viewing specific webpages, and more)
  • Online payments

These data points can help pinpoint where in the process a customer was lost, improve the next attempt at outreach with that data in mind, and eventually guide the account to a payment. With more data and longer periods of time, machine learning processes only continue to improve.

Updating your collections strategy 

TrueAccord takes our digital strategy a step further by looking beyond simply using digital channels and focuses on the power of machine learning to continuously improve our collections performance. We’ve come to understand that creating an effective, empathetic collections experience actually comes from creating a more analytical and AI-driven process.

With better visibility into performance, more granular data points, and more accurate reporting available than ever before, digital debt collection strategies strengthen the power of any collections team.

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