Influencing customers only works when you have an idea of what they like or don’t like. Only then can you start predicting behaviours and improving tenant relationships.
Evidence-based recommendations mean you’ll have the insight to educate social housing officers about how to communicate with tenants, learning from their previous engagement. It’s the end goal of predictive analytics.
So what can you do to improve the customer experience and forecast their preference for discussing arrears? By using tenant engagement software and successfully predicting behaviours, you’ll have a quality data set that continually points to the best course of action. In short, Voicescape Collections puts the power in your hands.
Once you’ve segmented tenant data, built a risk profile and gained a greater understanding of tenants, you can forecast what they’re likely to do next. It all ties back to your current collections procedures and how effective they are.
Tenants may, for instance, prefer an in-person visit to resolve arrears – rather than a letter or phone call. Some days may be better for them than others. They could struggle to meet current deadlines due to issues with their earnings. Perhaps they are sick, elderly or dealing with mental health issues meaning you could help with a repayment plan or additional support.
Knowing such information means you can adapt, try new collections procedures and speak to them at more convenient times.
It’s then a matter of testing what works and what doesn’t. Anything that positively influences behaviour can be used again for similar issues and demographics. Your forecasts stay up to date, shaped by everything you learn from predictive analytics.
Voicescape Collections combines leading-edge modelling techniques with established technology to provide insights that really matter.
Our system records every attempt we make to contact the tenant, as well as the outcome. By tracking the response and linking it to a deeper understanding of the customer, this data can begin to model:
Whether the tenant appreciates phone calls or ignores them.
Whether they have a phone at all – a particular issue for elderly people.
The best days and times at which to call, if they do respond positively.
The extent to which a letter, personal visit or other form of contact may be preferable, based on their behaviour so far.
This information allows you to pre-empt customer behaviours and make evidence-based recommendations for how to influence them. And, if your response has a positive impact, we track it meaning you can trust it in the future. Random controlled trials are useful in this regard, as they give the most reliable data sets for testing your actions and influencing customers (new or old) before they ever miss a payment.
Recently, Voicescape Collections left a transformative mark on Northern social housing provider. Using tenant engagement software, we have placed predictive technology at the heart of a root-and-branch redesign of the income collection service.
A suite of self-learning statistical models will direct what they choose to do for each tenant. The tenants themselves have been assigned a risk factor and housing officers will only intervene if this breaches a certain level. If it doesn’t, they can leave collections to an automated system – only intervening when required.
Not only does this free up a huge amount of time and energy for the organisation, but the provider is improving their landlord-tenant relationships.
Predicting behaviours is the benchmark for every improvement in rent collection. Know exactly who to prioritise, what they prefer and the extent to which you can roll-out the same measures for similar people in the future. You won’t sink money and manpower into misjudged solutions. It’s part of our wider Collections analysis…
Want to know how to make rent collection easier by predicting customer behaviour and therefore, strengthening your relationships? Get in touch to find out more.