5 Steps to Success With Rich Data Products
Not all companies will conclude that marketing rich data products makes sense for them, but it’s worthwhile to at least explore these opportunities. Innodata Isogen—a provider of knowledge process outsourcing and information technology services—suggests the following five steps to develop successful rich data products.
Step 1: Perform a Customer Survey
Ask your customers how you are currently meeting their needs, and how you can help them realize their vision for their business. Also, ask your staff how they think your customers are now using your information, and what they believe your customers would like to derive from it. Develop your best analysis of what people are doing with your data now, and how they would use it if it was accessible in greater detail.
Step 2: Audit Your Content
Take a careful, thorough look at your own content resources. See where your data is already rich and where it could be further enhanced. Imagine how useful this data could be if it were easily accessible. Also, consider how well you are positioned to develop and market a rich data product. Do you see yourself as a publisher of magazines? Or do you see yourself as an aggregator who can package content into whatever format the customer wants? That latter mind-set is an important building block toward developing successful rich data offerings.
Step 3: Find an Experienced Partner
Look for a rich data-savvy partner who can help you go from concept to reality. Ideally, your partner should be able to provide all the resources you need to develop rich data products—editors, researchers, IT professionals, technical expertise and experience.
Step 4: Lather, Rinse, Repeat
Once your rich data product system is built, start feeding the data back into itself. Your data is only as rich as your customers believe it to be. Offering rich data products is an ongoing process—one that constantly requires you to analyze what your customers are doing, and not doing, with your data; what they would prefer to do with your data; and how you can further meet their expectations.