Forecast subscription revenues quickly and accurately

More and more businesses are turning to direct to consumer selling, and, in particular, to subscription-based services. From veg boxes to wine, beauty products to fashion, the market for continuity sales has expanded immeasurably over the past decade or so. Companies love the reliability and durability of subscription sales – not only do people on such schemes tend to spend more than their ad-hoc counterparts, but also, with enough customers, continuity sales are generally highly predictable, providing a business has the right tools and the ability to handle large quantities of data.

Of course, many businesses have been operating on a subscription-type basis for a long time. Charities, magazine publishers, membership organisations and insurance companies have for years operated on the basis of persuading people to sign up and then hoping that they will continue to pay monthly or yearly fees for long enough to generate a return on the original marketing investment. However, as the market has blossomed, so it has become more complex, with some companies offering many scheme and frequency options, and allowing their customers to switch between them at short notice. This means that the simple attrition curve approach adopted by businesses in the past may no longer be sufficient.

One of the biggest problems with continuity selling is the amount of data it generates, and the need to simplify it to generate accurate forecasts and actionable reporting. Key to this is dividing the customer base into segments that are meaningful for reporting and can also be used for forecasting. This means identifying segments of customers that are likely to behave in a similar fashion for the purposes of forecasting, and can usefully be grouped together for the purposes of reporting. In Compas, these segments typically consist of those who were recruited together and are on the same scheme and frequency. This segmentation works well for the first two or three years after recruitment, after which most customers who are going to leave have typically dropped off the database, leaving a more or less homogeneous pool of customers for whom the source of their initial recruitment is no longer a  relevant factor – for forecasting or reporting.

Compas starts to generate detailed and accurate forecasts of expected continuity revenues from before the date of initial recruitment. When a marketing campaign is planned, the number of people who will join a continuity scheme can be defined by entering the proportion of orders that are expected to give rise to a subscription – split between different scheme options and frequencies if relevant. If the forecast for the number of orders or expected takeup rate change, the number of new subscribers is updated automatically. These changes then feed directly into the expected future revenues from those subscribers, so that a change to a marketing campaign can automatically update the expected number and timing of new subscribers, and associated revenues months into the future.

Compas primarily forecasts using a curve-based model, forecasting each segment separately and then aggregating the results. However, those curves do not have to be simple attrition curves which simply predict the rate at which people stop subscribing. They can be more behavioural, allowing the forecast to depend on actions at the previous subscription cycle. We generally help new clients to define the appropriate segmentation and build the curves, but it is also possible to upload curves through the front end, using data analysed in Compas or externally. It is also possible to insert your own forecasting model and use that instead of Compas to generate the forecasts, but still to use Compas for reporting and comparison with actuals.

As well as creating highly accurate subscription forecasts, Compas also generates detailed reporting, both of forecast data and actuals. As with other plan data, continuity forecasts are automatically snapshotted at the end of the week, allowing users to observe how the predictions have changed over time, and to see how accurate they were at different points in the past.

Our video ‘Forecasting recurring revenues‘ illustrates how easy it is to use Compas to forecast subscription revenues, and the sort of reporting that is available out of the box. However, Compas is a highly flexible platform and can easily be extended to meet different needs.

In reality, there is no substitute for actually trying the system out yourself though. Contact us now to arrange a demo and no-obligation trial. 

 

 

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