Baynote sells a recommendation engine whose motto appears to be “popularity implies accuracy.” While that leads to some interesting technological ideas (below), Baynote carries that principle to an unfortunate extreme in its marketing, which is jam-packed with inaccurate buzzspeak. While most of that is focused on a few trendy meme-oriented books, the low point of my briefing today was the probably the insistence against pushback that “95%” of Google’s results depend on “PageRank.” (I think what Baynote really meant is “all off-page factors combined,” but anyhow I sure didn’t get the sense that accuracy was an important metric for them in setting their briefing strategy. And by the way, one reason I repeat the company’s name rather than referring to Baynote by a pronoun is that on-page factors DO matter in search engine rankings.)
That said, here’s the essence of Baynote’s story, as best I could figure it out.
- Baynote’s secret sauce is a set of 20+ behavioral metrics to identify whether, if somebody clicks on a page, they are SATISFIED with the content.
- Based on that, Baynote provides a “content recommendation” engine. (For now, the distinction between “content” and “web page” is not important, but the concepts are in my opinion diverging over time.) This is manifested in two forms (a typical installation uses both). One is just a list of recommendations. The other is in a search engine – “social search” with an “implicit folksonomy” — and its results pages. Both sit on web pages as boxes/widgets.
- Baynote’s first markets were online support and eMarketing. The company is now rolling out eCommerce as well. I didn’t get clarity about what was different in the nature of the recommendations, if anything, that underlies any small separation between these apps. (Baynote was clear about saying that the differences were indeed small.)
- The whole thing is SaaS, built on a LAMP stack. MySQL 4.something seems to suffice, which makes sense given that Baynote’s system is not handling any significant transactions directly. That said, I didn’t push to understand what it means for a search engine to be built on MySQL. This wasn’t the kind of conversation in which one could elicit substantive detail.
- Baynote claims that a sample size of as few as 7-10 visitors liking a particular piece of content suffices to provide a good basis for predicting who else will like it. I’m not in a position to assess the credibility or, more to the point, limitations of this claim.
- Baynote has the philosophy that they try to watch a user’s behavior on a site and map that to a “context.” I like that approach.
- The company cites tested stats of 20% net lift (revenue increase), with 50% of sales being touched by its recommendations. Those numbers don’t sound terribly impressive, perhaps unless they’re truly additive to those provided by, say, Endeca, which is an announced partner.