Your comments are on target with respect to the “old-school” mentality of measurement as applied to successful marketing in social networks. It’s a Catch 22. Companies want to market in social networks. If they use traditional advertising methods, they can easily measure the success (or lack thereof). However, if they go about it correctly - using the medium as it’s intended to generate viral spread and word of mouth, it becomes much more difficult to measure success, therefore leading to the potential that a company could ditch it’s social marketing efforts due not to a lack of success, but rather, to a lack of available metrics (or metrics that they understand).

New medium requires new tools, maybe even an entirely new way of defining success. Companies who properly use social networking as a vehicle should want to know what people are saying, who they’re saying it too and where they’re saying it. Those tools do exist, but old-school thinking hasn’t learned to shift from “click-through rates” to “velocity of talk”, etc.

Scott Oppliger
oppliger.typepad.com

However, it looks like you are right into this space - i’m going to read the rest of your blog and discover more….

and Jim, that has to be the most thoughtful and thorough comment i have ever seen on a blog - kudos

As for the matter of demographics, you really need to define what you mean by “traditional demographics”. Grouping people at all by age/gender? The actual bounds of traditional age/gender groups? Trying to target contiguous ranges in the age/gender set? Other possible demographic data? It sounds like you have an interesting point of view, it’s just not entirely clear what that is.

I’ve thought for a long time that what on-line (particularly social network, but ultimately anything where you’re logged in) could do with is “I like this” and “I don’t like this” links by each advert, providing trend data effectively allowing people to pick what adverts they see themselves; add to that a system akin to Amazon’s “recommendations for you”, and you could have very quick and effective advert auto-targetting. You could also, in social networks (assuming SOME level of feedback, even if that’s only whether an advert has been clicked on), use the friend data to bias a person’s friends’ adverts according to the person’s own preferences, which presumably are generally similar.

But I don’t think any kind of intelligent targetting system of that kind is likely to be agreeable to the advertising industry, and that’s all because of numbers. Advertisers like to think “I’ve just bought 10,000 eyes” or whatever it might be. They don’t care if there are duplicates in the set, they don’t much care how many people actually see it (it’s a probability-driven industry), they may not even care if much of the set is outright disqualified from whatever the product is (eg. people outside the US getting US adverts), but they do really like firm numbers to base everything on - and that means the set of people who MIGHT see the advert. In effect, that requires some form of demographic data: you have to be able to say, in advance, that a certain number of people should see it, and provide reasonable assurances that most of those people are well targetted. I don’t think that the idea of quality over quantity, at that level, is conceivable to advertisers right now, even in the face of more advanced targetting such as Google’s AdWords (which still provides firm predicted numbers).