Debt collection is far from a new concept. As such, it’s safe to assume that debt collection best practices are well-established and highly effective. Right?
Modern consumers think, browse, purchase, and communicate differently to their predecessors. This means that traditional debt collection practices generally miss the mark nowadays. In an age where customer experience is king and personalisation a mere expectation, lenders need to reevaluate how they approach collections.
We’re going to lay out 6 best practices when it comes to modern debt collection. These fall under two primary pillars:
We’ll explain the theory behind these practices and explore how they will transform your collections strategy, making it both more efficient and more effective.
There’s a common adage that states: “Data is the new oil”. For companies of all shapes and sizes, customer data is perhaps the most valuable asset that they have: providing an infallible blueprint outlining each individual customer’s preferences.
But your data is only as good as the analysis that follows—and that’s where AI comes in. It’s difficult for humans to quickly analyse large datasets. Artificial intelligence, on the other hand, can seamlessly crunch the numbers and recognise core patterns in a matter of seconds.
Finally, automation can help companies carry out this AI-based data analytics at scale. Data analytics, AI, and automation may well be the ultimate trifecta when it comes to collections. They seamlessly turn overwhelming amounts of data into easy-to-use, highly valuable assets—helping you gain greater knowledge of your debtors on an individual level. As a result, this significantly aids your collections efforts.
Let’s explore three main ways in which you can use data analytics, AI, and automation to transform your collections process.
There’s no universal strategy when it comes to creating the perfect collections process. It varies depending on the industry and the individual consumer themselves. So how do you work out which strategies work and which don’t?
By testing them out. For example, you might hypothesise that your debtors prefer regular, casual text messages than irregular (but highly serious) letters through their door with a big red ‘URGENT’ sign plastered on the front. This makes sense in theory. However, to identify if it actually brings greater results, you’ll need to test it out.
Machine-learning algorithms can automate large parts of this testing process. They’ll quickly identify potential trends to consider implementing and immediately tell you if a strategy simply isn’t working. Machine-learning algorithms will then pinpoint each individual customer’s precise preferences, thereby making your communications more effective going forward.
Your testing process has thrown up some invaluable insights. What next? Now, you need to turn that data into assets. Ideally, you would have an up-to-date dashboard with all relevant data and insights at your fingertips. This might show things like a customer’s preferences, their balance history, and their days past due.
Once you have all this data at your disposal, you can then craft an appropriate collections strategy for each individual debtor. You’ll be able to identify which strategies have the highest chance of success and tailor your automated outreach accordingly.
You’ve tested various hypotheses and your dashboard demonstrates all corresponding collections data. Now, you can begin to segment your customer base depending on the results.
Group A might respond very well to loss-aversion style messaging (e.g. “Pay now to avoid further dunning fees”). Group B, on the other hand, might prefer outreach that relies upon the principle of social proof (e.g. “9/10 customers repay their debts after the second reminder”.)
Your debtors are individuals, and so they must be treated like such. However, you can use their individual customer profile data to segment them into categories. These categories will then inform the way in which you communicate with these debtors going forward.
Data analytics, AI, and automation are only one piece of the puzzle. In order to appropriately leverage their power, you need to focus on content creation and implement multi-channel outreach. Data analytics, AI, and automation are like a car. They provide the complex structure and the technical machinery to help you reach your destination. However, a car is useless without fuel—in this case, that’s the multi-channel content outreach.
Companies used to adopt a one-size-fits-all approach to mass communications. In the digital age, however, that no longer works. There are two main steps to successfully communicating with consumers at scale. First, you need to leverage data-led insights to appropriately segment your audience. Second, this segmentation needs to be followed by appropriately crafted messages sent out through a variety of digital communication channels.
Take the above point regarding customer segmentation: Group A responds better to loss-aversion style messaging and Group B to social proof. However, this is useless unless you use these insights to tailor your outreach accordingly.
If you’re struggling to do this, or want more ideas on how this principle can be put into practice, then check out our four email templates for debt collection.
Gain access to relevant data. Segment customers and pinpoint which strategies work best for which individual. Use this data to inform your outreach messaging. It’s really not so hard.
Email outreach is great—but it’s far from the be-all and end-all of debt collection. Modern consumers are available across a variety of channels, so they should all play a part in your integrated multi-channel contact strategy.
Employ a methodical approach when creating your strategy from scratch. Remember: the ultimate goal is to reach the right customer, at the right time, with the right offer, and on the right channel. If you do this then you can’t go wrong.
Collections should be a dialogue, not an imposition of terms. This means that particular emphasis needs to be placed on the content, tone, and style of digital communications.
This is only natural when speaking face-to-face with someone. Mirroring—imitating the other person’s speech, manner, and gestures—is one of the most effective sales tactics. By communicating with people how they like to be spoken to, you have a far higher chance of creating an effective dialogue.
Some customers might want to avoid confrontations and embarrassment and so will require a softer, more nuanced tone. Tailored messaging, personalised according to an individual’s preferences, is a critical modern debt collection best practice.
These 6 best practices will transform your collections strategy going forward. However, there’s more to them than meets the eye. If you want to truly master modern debt collection then join us for our upcoming series of educational webinars, where we’ll cover each of these 6 topics in more detail.
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