Gary Zellerbach's Weblog: Focus on eMarketing and Electronic Software Distribution

I've actually been on my new job for a number of months now, so it's time I start writing about it! After 10+ years working in the ESD (electronic software distribution) space here at Sun, it was time for a change, and so I took on a new challenge in the eMarketing realm. I am overall Program Manager on the sun.com web team for an initiative we call "Contacts to Revenue" (C2R). The essence of C2R is that we have zillions of web visitors, and especially downloaders, and we need to do a better job of identifying contacts and hopefully "nurturing" contacts into customers. There are several primary initiatives now underway.

First, we're creating new content we feel is of value to our customers and asking them to login to receive it. (If you don't already have a Sun Online Account, then there is a brief registration form that must be completed.) We feel this is a fair value exchange -- you tell us who you are, and we provide valuable information in return (examples include white papers, blue prints, webinars, and downloads). Here's an example:  Deploying Hybrid Storage Pools with Sun Flash Technology and the Solaris ZFS File System.

Second, I want to discuss Project SMILE -- The Sun Machine Learning Engine. We're building a new analytics engine to help provide more relevant content to web visitors. I'm the Project Manager for SMILE and pleased to say we went live with "phase 1" in mid-January. For the initial release, our goals were modest, focused primarily on improving the relevancy of small advertisements displayed on our main web site. We used a good ad banner server program previously, but it lacked sophisticated segmentation and targeting capabilities, so we built our own. If you are a return visitor to sun.com, we may serve you small ads that are more targeted to areas in which you've indicated an interest. All the ads are unobtrusive, appear in the right hand column, and are of this format:

For SMILE Phase 2, we're working on the ability to more proactively serve "Recommended Links" and other content of value based on web visitor's interests in our products and services.

We realize that asking for a login to obtain content and using machine learning and analytics to serve customers may be of concern to some. However, the bottom line is that we're in business to make a profit for our shareholders. Times are tough (duh), and it's imperative we do a better job of converting our web visitors to customers in order to grow our customer base and increase revenue. It's not a one way street -- we will continue to provide exceptionally valuable and unique content in return as well as striving to make relevant content more apparent and easier to locate on the web. 

In conjunction with these changes, we have recently updated our Privacy Policy to more accurately reflect how we'll be using customer data in support of these programs (among other updates). Please read it if you wish to be fully informed on this subject. (We also make it possible to opt-out of web personalization if you wish.) In any case, as this blog post and the new privacy policy illustrate, we're openly communicating about these new programs and changes. Our intent is to better serve our customers and our shareholders.