Audiences as targets

Here is some very apt criticism of the notion of a “target audience”, particularly in relation to online media. The passive connotations of the idea of “audiences” as receivers are criticised, as is the notion of a reader as “target”. An alternative phrase, “communities of interest”, is suggested. Again this is from Amy Gahran.
Still, I’m not sure that the idea of a “community” is better in all respects – the warm and fuzzy connotations of “community” just don’t seem suitable for all aspects of online media. For example, the most profitable notion of online marketing is based on an ever more precise targeting of individuals and their potential utterances.

In the forest of online words, you buy your ammunition – search keywords – and Google lies in wait for your prey, ambushing them with your message as soon as they move into sight.

Long tails and fat cats: Social networks and inequality

I’ve been fascinated by the idea of the “long tail” and online media for about a year now. The long tail is a distribution graph. For example, you might graph the number of blog readers for each blog, and arrange them in descending order of popularity – you’d find that a small number of blogs would have a large number of readers, and an incredibly large number of blogs (or the long tail) have a small number of readers. The long tail is used to explain how the diversity of online audiences and content on the web have fuelled the growth of new media aggregators and filterers such as Google.
How the long tail works – for some
Here’s a wry comment on the the failure of the Excite search engine>. Although the most popular searches on Excite were for predictable terms such as “sex”, “Britney Spears” and “mp3”, 97% of their traffic came from the “long tail” – a hugely diverse range of pretty unique queries. While Excite failed to figure out what to do with their long tail, Google (which copied Overture) put it to work. They are still systematically “optimising” their techniques of making money from this diverse audience — by using targeted keyword advertising. This is a huge shift from traditional marketing, which sees audiences as segments or categories. For example, the games industry produces loads of games tailored for “18-35 year old males” (naked women on the box, big weapons, lots of blood and gore), and a much smaller number intended for “tweenie girls” (hot pink box, Barbie etc).
How tagging works
The long-tail approach to marketing doesn’t categorise an audience, but rather plays a game of “tag”. Newspapers traditionally categorise a story as “news”, “sport”, “entertainment” etc. Tags, or “folksonomies” work by breaking away from fixed categories, and allow an organic and evolving vocabulary for labelling or annotation of content. Bloggers tag their posts, and social sites such as delicious allow users to tag content. In keyword advertising, an advertiser “tags” their product or service with a set of keywords, and bids for these keywords on a search engine such as Google or Yahoo, and then waits for a user to match the tag with a search query.
These new patterns of media use have been seen to herald the death of the blockbuster. It’s argued that, as people are free to choose from more diverse sources of entertainment, they are less likely to all flock en masse to see the same films and listen to the same music.
The long tail has also been heralded as good news for small, specialised content producers, who now use the web and search engines to target smaller groups of people with very specific interests. From the perspective of developing countries, then, this surely sounds more democratic, and a move away from homogenised “one-size-fits-all” mass produced “McMedia”. Sadly, it also suggests all sorts of new recipes for inequality – the long tail is indeed a “power law” in more senses than one.
First, here’s a sober explanation of who in fact profits from the long tail model of media distribution. The long tail allows fat cat profits – in many cases by producing content for the fat cats for free: In this article, Where’s the money in the long tail, Ventureblog argues that the long tail model only turns a significant profit for media aggregators (e.g. Yahoo’s flickr) and filterers(e.g. search engines, who get to make money from directing the traffic. So there’s a strong centralising tendency emerging as people attempt to make sense of the diversity.
Second, as social networks settle, it’s getting harder and harder to get the kind of attention needed to make any kind of a splash — without a major marketing campaign, that is.
The “long tails” seen in graphs of blog audiences do mean that the vast majority of blogs will be read by only a handful of people. Increasingly, well-capitalised media organisations have huge advantages here, since they have the resources to create content, and more importantly, are able to market the content to audiences via other forms of media.
Blogs to riches – the haves and have nots of the blogging boom.
Most residents of the blogoburbs who talk about social networking and social software don’t feel the need to extend their theories to account for the position of whole groups of people who are not connected, or who occupy a marginal position within global social networks – these people are not in the Rolodex.
Here are two ways that developing countries are probably being systematically marginalised in the social networks that rule the web.
* The search engines favour older, more established content through the time bias in ranking systems – this is a particular problem for those in developing countries who arrived at the Internet party unfashionably late. It remains to be seen whether new localised and community-based versions of search will be able to undo this bias.
* It’s who you know – online networking is about making connections with powerful celebrity players, whose viral marketing will get you attention. Alternatively, you need to be promoted in the media consumed by your target audience.
Systems such as Google or wikipedia are too immense to comprehend easily, and their social effects are similarly complex. Nicholas Carr challenges the technorati and their implicit trust in these statistically “optimised” systems. As he points out, just because something (like the Google algorithm) is technically elegant, doesn’t mean we should accept it and all its social consequences.

Where I have a problem is in [the] implicit trust that the optimization of the system, the achievement of the mathematical perfection of the macroscale, is something to be desired. To people, “optimization” is a neutral term. The optimization of a complex mathematical, or economic, system may make things better for us, or it may make things worse. It may improve society, or degrade it. We may not be able to apprehend the ends, but that doesn’t mean the ends are going to be good.

Read Carr’s whole entryhere .