Businesses based on selling data on a subscription basis are in a truly turbulent period right now. Competition from open source databases and low-cost API databases is starting to emerge and firms with killer workflow integration software are also hungrily eyeing B2B database publishers’ steady revenue streams. Adding to the pressure is the fact that data aggregators like EBSCO are actively promoting data usage analysis to their library customers
This new reality means that those firms who haven’t been busy building brick fortresses of killer functionality for their customers and can’t quickly tell you the “cost per use” for their products are not going to be prepared for the kind of scrutiny on the ROI of their services that is coming their way. Before your customers head for your competitors’ doors, however, there is the opportunity to take a long, very specific look at how your customers use your data before it is too late. When you start wading through those log files, here it what you should be looking at:
- Search volume: Looking at total search volume is easy and tells you a lot about the importance of your product to the consumer. Typically marketers do these simple analyses to spot folks violating enterprise subscription rules, but product developers should take a look at this data with an eye for seasonality patterns, decreased usage over time, etc. If you serve more than one vertical, then overlaying market segmentation data and usage data to compare usage across different industries can be extremely useful, too.
- Search trail analysis: What did the user search on?; Did they find what they wanted? Did they search for something that they didn’t find? The answers to these questions can drive product enhancements, the development of wholly new products, segmented approaches to marketing, and product repositioning.
- Feature usage analysis: Pockets of high activity around certain features (e.g., downloads, advanced searches, workflow integration tools) are critical indicators of where software development resources should be focused.
In fact, subscriber data analysis is so important that subscription services with, let’s say, over $2.5MM in revenue probably need a dedicated data analyst to keep their products delivering what the marketers promise: a compelling ROI that ensures high renewals.
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