A new product by a cool young company called Datanyze is capitalizing on some well-established infocommerce best practices. Here’s how they did it.
The core business of Datanyze is identifying what SaaS software companies are using (sometimes called a company’s “technology stack”). To do this, Datanyze interrogates millions of company websites on a daily basis, looking for telltale clues as to the specific software they are employing online, and apparently a lot of categories of software can be divined this way. Datanyze aggregates and normalizes these data, then overlays company firmographic data (Alexa website rank, contact information, revenue estimates) to create a complete company profile.
Datanyze links directly to the Salesforce accounts of its customers, so it can add and update prospects on a real-time basis. At a basic level, the use case for this product is straightforward: a marketing automation platform like Eloqua could use it to find companies using a competitor or no marketing automation at all. But wait, there’s more!
Datanyze’s new product essentially flips this service. Now, Datanyze clients can have Datanyze analyze their existing best customers, and Datanyze will build a profile of these customers that can be used to predictively rank all their prospects, current and future. Here are the best practices to note:
- The transition of Datanyze from a data provider to an analytics provider, something that’s happening industry-wide
- The shift from passive (we supply the data, you figure out what to do with it), to active (here are top-rated prospects we’ve identified for you), and the associated increase in value being delivered by the data provider
- The tight integration with Salesforce means that Datanyze customers just need to say “yes” and Datanyze can get to work – no IT involvement, no data manipulation, no delays
- Datanyze is pouring leads into critical, core systems of its customers, a strong example of workflow integration
- The use of inferential data. Boil down a lot of the analytical nuance, and Datanyze has discovered that companies that buy expensive SaaS software are better prospects for other kinds of expensive SaaS software. Datanyze doesn’t know these companies have big budgets; but it does know that these companies use software that implies they have big budgets
Datanyze offers a concrete example of how data companies are evolving from generating mountains of moderate value data to much more precise, filtered and valuable answers. Are you still selling data dumps or analytics and answers?