Moving Beyond Transactions: The Benefits of Web Services and SOA

Revenue-generating activities such as purchases, subscriptions, licenses and related cross-sells are relatively easy for most companies to track and understand at a customer level. Non-revenue activities have long been more difficult to track, with only isolated instances of useful information, such as cart abandonment and contact form completion.

But now that we have web services and service-oriented architecture (SOA), companies will soon see a flood of non-revenue information tied to individual customers, which could unlock deeper insights and create far more opportunities for positive customer interactions.

Most companies have some mechanisms for handling non-revenue activity in place today. But most are tightly coupled systems, where information flows in defined pathways from one system (e.g. web site forms) to another (e.g. lead management or sales force automation systems). Once information is in the appropriate system, marketing automation can kick in, nurturing the customer or prospect through the next phases of the relationship.

The problem is getting the activity information in the first place. Where an activity is clearly of high value, such as a new lead or a program enrollment, companies have put systems in place to collect and manage the activities. The investment to build these point to point connections is high, so only proven indicators tend to be collected.

What many marketers are still working to grasp is how the technology landscape is changing dramatically. Web services have finally come into their own, making it much easier for companies to use each other’s application programming interfaces (API). Service oriented architecture (SOA) has become mainstream, making it much easier for companies to share information internally.

The important point for marketers is that customer activity data can be accessed and used by any system, regardless of where it resides. (Your IT director may disagree, but give it time.) Since there is far more activity data than revenue data, you will make your IT director happy by concentrating on aggregated data (for example, who did an activity or how many times they did it, versus every detail of that activity) and about event brokering (events trigger distinct processes and actions, but aren’t necessarily stored for future use). Don’t assume you will have complete freedom to use every detail of every action of every customer. Pick out key activities to start and expand over time.

With technical limitations removed, a whole set of new customer activities are now available. Beyond Web behavior, which is already widely used, the most obvious activities are user generated content, such as product reviews, forum postings, and blog comments.

Activity using your Facebook applications (you have at least one, right?) provides another indicator of customer engagement. Usage information, particularly for subscription businesses, is an important indicator of churn, and is not always readily available for marketing applications. Customers’ social graphs (essentially who they are connected to via social networks) are gold mines for finding mavens and connectors.

There are many ways to make this information valuable. Improved message targeting and more relevant messages are a clear benefit. Marketers can include referral value of customers in lifetime value estimates. More sophisticated marketers can sharpen their predictive models dramatically. Churn prediction can become more accurate, especially for non-subscription businesses, which also improves lifetime value estimates. Marketers can more clearly identify key customers and begin to treat this segment very differently from less active customers. Lastly, activity data opens up fertile new areas for testing promotional effectiveness, both for short-term promotions like coupons and long-term efforts like loyalty programs.

Armed with good software and a great data analyst, marketers can begin to understand the causal relationships between activities, financial incentives, and resultant behavior. Tying appropriate incentives to specific, incremental, value-creating behavior is one of the most important long-term objectives for relationship marketers, and incorporating activity data provides a huge step in that direction.

Michael Greenberg is president of Loyalty Lab, a San Francisco-based developer of best customer management and loyalty solutions for the retail, travel, CPG, and consumer services industries.