Content Quality

A while back, when 365 Media was figuring out how to determine which information sources were more reliable than others - we developed the concept of the 'content momentum' of a site. Our NLP-based system were scouring content to find described business events to convert into data changes in existent (customer) databases. We were constantly looking for ways for our system to make better decisions based on things like priority (which news piece is more reliable), efficiency (which site is churning out re-runs and wasting good server time) and ranking (in this industry, which are the best sources of primary news).

Content Momentum was a concept that enabled us to do this - it worked loosely around the mass (size of overall content on site) multiplied by velocity (rate at which new content appears on the site) concept (hence 'momentum') with added caveats around the value of that content as it was processed through our system and then fed back to the training set.

All very interesting. Why am I mentioning this? Well, today Google announced a change to its search algorithm in order to "provide better rankings for high-quality sites—sites with original content". Google now cares whether the site has content quality? Well, duh, that's great.

Quality versus Quantity

I was reading Russell Perkins' blog today (definitely worth getting if you're in the information business). Today's subject was Google's lack of progress in creating a more efficient and effective search - underlined by iProspect's research into search behavior that claims that 50% of search activity fails.

Lots of blog commentators obsess about Google, so I'm not going to start. The interesting question to me was - does Google really want every search to be successful? Google makes money by placing ads next to searches - if a user session is three searches before frustration sets in (or the result is found), then the average potential yield per user is three searches. Each search yields revenue for the search engine. If the search engine is improved to reduce that to two or even one search, on average, then the revenue decreases. This is an interesting dynamic - the business goal of the search engine is to optimize the number of searches within the 'frustration parameters' of the user - in other words quantitatively, not to optimize the search qualitatively - because this is the maximum revenue opportunity.

Compare this with services that charge for delivering information - their goal is to minimize the frustration of the user and deliver the solution as fast and efficiently as possible. In other words, their goal is quality.

From the user perspective this is a trade-off between frustration/time and dollars. But let's not pretend the search engines are in the business of optimizing search by reducing the need for it, they are in the business of optimizing it by prolonging it - quantity is the goal here.