Mining Metering Data To Boost Revenue

By CA Technologies Guest Blog 1

You’ve certainly heard the term big data a lot recently. But did you realize it should be part of your sales efforts? Cloud computing has driven demand for self-service, on-demand usage of computing and with that, the notion of metered billing has become quite common. When offering on-demand services, it’s tempting to assume that users who self-serve don’t need sales contact, lowering the cost of serving those customers. However, that can be short sighted and result in lost revenue opportunities.

Metering data used to generate billing can be a source of opportunity for MSPs. When mined correctly, within that data is information on which customers may soon discontinue service, which are ready to upgrade, which may buy extended support offerings and other valuable sales context. Over the course of the last few years we’ve used this data ourselves and have helped our partners to do so as well.

Data collection often includes amounts of resources being used, user logins and may even include commands issued as we do with our own AppLogic system. The mining process begins with identifying what’s out of the norm.

Determining which customers are more likely to cancel

Users with infrequent logins are at risk of leaving your service. There may be several reasons, which if understood, can be acted upon. For instance, the customer may be new or the customer’s primary user may have left and their replacement may need assistance getting started.

Contacting these customers early can make the difference in keeping them and even growing their business. As an example, when we uncovered the fact that a customer had assigned a new user responsibility for the service, we directed them to online training and even offered a short term support contract to get them up and running.

Users with low CPU or storage usage may not be aware of certain capabilities of your service. Email or login messages highlighting applications being run by other customers or new templates in your own catalog may be sufficient to get them to try new things. Support contracts for migrating certain applications may also be attractive offerings.

Determining customers likely to respond to upgrade offers

At the opposite end of the spectrum are customers with high usage and frequent logins. Obviously, these customers are clearly are finding value in your service and don’t need sales or support help – right? Wrong! These customers probably make up a large percentage of your revenue and you may know little about them if you’re not in contact with them. In addition, they may be very receptive to special bundles for new services, support, training and other high value upgrades.

In one instance we worked with a large user to secure service for them internationally with another vendor. We maintained the primary contact with the customer, while they maintained a single point of billing and support. Without the data mining we would not have made that sales contact and we would never have known of the opportunity.

Upgrading your metering data

My examples are just the surface of what’s possible. As you get proficient, you’ll move beyond mining existing data to actually identifying data you want to start collecting specifically to identify sales opportunities.

Bert Armijo