52 Bicycles

Advertising is the activity of reaching prospects with a message that incents them to buy. There are, to my mind, three ways to target them:

1. Demographic targeting: Choosing based on the basis of known attributes, usually more broad: older vs younger, men vs women, profession, etc. This kind of targeting usually picks a medium (i.e. a specific magazine or website) and pays a diluted CPM to reach those folks. I think this is the most relevant for a banner ad on, say, digg or reddit, where the content is a melange, but there are certain consistencies in the population using the service. We all know about this type - it’s what we see every day in magazines and in banner ads.
2. Contextual targeting: When you know what else is on the page, provide a message that complements that information, such that a reader would want to know more, so clicks on the data. This is the model of Google Adwords and Yahoo Search Marketing. This can work pretty well when the content on a page is pretty consistent. For example, it is killer on a search engine, and for many individual pages (or blogs) where there is one topic on the page. Click-through should be higher, because the advertisement is relevant to someone obviously interested in the subject.  For example, CNN.com has google ads on individual article pages, but relies on CPM banners on the main page. The contextual advertisers can more reliably use a “Per-Inquiry” pricing model, which translates to CPC, instead of CPM or flat fee. Of course, the challenge is getting the context right, which is often imperfect. Because it’s about understanding a wide variety of content, it is also technology-intensive to get the relevance right, assuming you are doing it mechanically (otherwise, it is still brain-intensive).
3. Behavioral targeting: When you know more about the individual, you can target messages that speak to his/her needs or interests, based on what you know. This is really what the social engines are all about - collecting more data on people so they can give more relevant messages, and drive more relevant transactions. As Amazon has taught us, this is not technologically intensive, but it is data intensive. And since each service has a different structure for their user data, they will have some responsibility to convert that data into the relevant ads. I think this is where Amazon Associates becomes most interesting, because it (among others) allows the driving of direct transactions. As such, behavioral targeting can focus on “Per Order” pricing, which allows a much bigger piece of the pie. And it is the type that users want the most - messages relevant to them individually, without messages that are not relevant. Again I think of digg or reddit or BlinkList or delicious - services that collect a helluva lot of data on their individual users, and so are in a great position to recommend transactions that are relevant to them.

Maybe there are more, and definitely there are intersections (behavioral crossed with knowing the page context) that can drive things up further. But I think that there is a trendline here of increasing data, and as the data increases, the opportunity shifts from impressions to traffic to transactions. And as that shifts, the opportunity to generate more value for the user - and generate more value from that user - increases. So a service with a lot of data on its 10,000 users may be in a much better position to monetize than a service with very little data, but 100,000 users.  The former can drive transactions, while the latter can only drive impressions.

More food for thought I suppose.

This entry was posted on Sunday, February 26th, 2006 at 7:40 pm and is filed under Technology Business. You can follow any responses to this entry through the RSS 2.0 feed. Both comments and pings are currently closed. Reddit This