Can you please explain what makes this different from all other in-text advertising? The article did not make it clear if there's any difference at all.
We're trying to focus it on specific data sets that users have more control over. We're not using the "keyword" approach like a Kontera or Vibrant allows you to link a lot, but creates a lot of crap. In Seat Geek's case we started with a simple database of the remaining NFL games; there's a limit on what can get linked so it doesn't get out of hand. We have another data set of product names that link product names to retailers and create affiliate links for people who do reviews or have users that talk about a certain product category. The goal is to focus on uniform data sets that can keep the links specific and relevant.
Hmmm...so help me understand something. As a publisher, if I'm using in-text advertising, I'm going to want to: a) increase my revenue, while b) keeping the links relevant. In the case of a), I'm assuming that more links on more keywords is better (at least up to a point), whereas for b) I'm guessing that advertisers on Kontera probably want to link relevant keywords. Apple doesn't want links for a sports team, even if it gets them traffic, because it's not relevant and won't convert. So I'm assuming that Kontera's relevancy issue would be self-correcting to some extent, in which case I'd actually prefer a broader array of options, rather than focusing on one data set. I guess I don't understand how this is better for anyone, unless Kontera really gives you zero control over what can / can't be linked, how many links there will be on the page, etc.
Regardless, this all sidesteps the primary issue IMO, which is that in-text advertising sucks.
