One startup trying to do just that is DataPop, which just closed a $7 million Series B round for its service that tries to present the most-relevant search ads to each individual consumer. DataPop relies on semantic search and natural-language processing to infer connections between what consumers enter into the search window and what they really want, and then on machine learning to help with everything from determining common spelling mistakes to search construction to the sequence of events that leads to a purchase. When we can understand the structure of these [ad] campaigns, DataPop Co-Founder and COO John Zimmerman told me, that provides us with the data to actually do the math and understand whats happening where. That type of insight can be invaluable to a small, niche company selling designer handbags, for example, but the company doesnt have to do anything but feed its inventory data to DataPop.
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