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News & Insights

News & Insights

Features v. Intent

by Matt Manning

For the information industry, the question of customers’ return on investment in data subscriptions and licenses is an existential one: without a clear ROI, renewal rates go down and information services wither away (see The Importance of Being Used). A corollary to being able to

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prove the worth of a data set is that you can only charge top dollar if clients can import it into their existing CRM, BI or other systems. This also works if you’ve gone down the road of bundling software and content into apps or online services with robust functionality. Both approaches allow customers to make immediate use of the data. Companies with clear case studies highlighting the cost-effectiveness of their solution to clients’ problems are best positioned to succeed.

This success means an offering’s features have become progressively more important than the content itself. Users’ expectations on data integration, analysis, and visualization continue to creep upward as people interact with increasingly powerful tools with intuitive interfaces, from in-vehicle GPS to Nest thermostats. But have rising functionality expectations caused the execs managing data businesses to lose track of the importance of identifying and bundling unique or hard-to-find datasets? I think this may be true today, but perhaps the answer is right under managers’ noses in the form of unique user data gathered by their digital products.

Take start-up StreetContxt, a niche aggregator similar to They bundle specialized content, in this case research reports from investment advisory firms, for their financial industry audience. What they do next is what makes them different: they sell information on users interested in particular industries to the folks flogging investment opportunities in those industries.

The act of blurring the line between content and user/usage data for an information service typically involves giving the content to the end-user outright so they’ll agree to surrender their metadata. This emerging paradigm has been evolving for years and it gets more interesting the more aggressively it is implemented. For example, the more data customers “consume” on a B2B buyer’s guide site under this type of model, the more revenues increase. This is because now there is more high-value data (that costs nothing extra to obtain) to be monetized.

It’s a tantalizing proposition and I expect to see more and more variations on this model.

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