5 Best Practices for Getting Rich with Data
2Know what you don’t have. Part of the challenge of creating rich data products is identifying what content exists in the marketplace that would complement the content you already have. Product managers generally know what other publishers are doing in the marketplace and what content other publishers have that would add increased value to their own product lines. Developing a partnership to supplement your content, and creating a link between your content and your partner’s content can make your product more valuable than it would be built on your own content. This can turn into increased revenue from advertisers or subscribers.
3Know how to manage what you have and need. Given that most rich data products are comprised of many types of content, publishers need to streamline the management of disparate data types. Having a consolidated repository (generally XML content with binary image files) is often the most practical way to manage content. Setting up such a system can be a large undertaking, but ultimately, understanding what technology exists within the publisher’s environment and/or procuring the appropriate tools is important. Otherwise, the amount of time it takes to manage the data may make the product impractical to launch and maintain.
4Know when to say “when.” When should you pursue rich data products? When shouldn’t you pursue them? Timing of a rich data product launch is probably not the most important issue. It is best to prototype a rich data product to minimize expenses while verifying the receptivity of your audience. Why spend months developing a rich data product only to find out that no one is using the product? Some publishers are able to quickly produce a product to see how their audience uses the product and make adjustments according to the usage. Prototyping minimizes your expenses and helps mold the product into a better audience experience, and ultimately more revenue from advertisers. The point is that publishers should not cautiously wait for the perfect time to launch a rich data product, but rather experiment with new ideas and concepts to test their viability.