A blog focused on helping bloggers and online retailers make more money online.

Since the beginning of the advertising age, the basic premise of advertising has been the same: create an ad and put it where people who you think will buy your products will see it. As advertising evolved, the methods to do this became increasingly more sophisticated through demographic profiling and focus-group testing while the range of advertising medium grew to include, print, television, radio and other new means of dissemination. However, despite these advances in advertising medium and technique a fundamental problem still existed: once initial assumptions were made, content was created, and advertising buys were executed, an advertising campaign was a largely static, impersonal, one-way method of communicating to potential customers.

In the mid-90′s, as the Internet became a growing force in communication with the general population, advertising once again took a fresh toehold. Like print and television before them, initial forays into online advertising were clumsy, poorly targeted, and largely static. Early banner ads assaulted website viewers with irrelevant content that neglected their interests or preferences.

Fortunately, the web continued to evolve, and as one of the primary revenue generators, advertising was often on the vanguard. Today we enjoy an online experience that is vastly different that the one that existed even five years ago. Content is far more dynamic, and through profiling techniques, web pages can be automatically tailored to specific readers on the fly.

And of course, advertising is at the forefront again through retargeting. Retargeting, in its simplest form, refers to the practice of serving advertising based on previous user behaviour to create a more relevant user experience (and, ultimately, more effective return on advertising efforts). Through retargeting, advertisers can ‘learn’ user preferences in order to more effectively target advertising inventory to achieve both higher passive engagement (impressions) and higher active engagement (e.g. clicks or conversions).

For example, on an automotive news website, a user is presented with two ads for automobiles: a black sedan and a blue truck. The user clicks on neither. On the following page, the advertiser presents the user with a different range of ads: a white convertible and a red van. The user takes an action on the white convertible (for example, roll-over the ad to expand it). Based on the preference for the white convertible, on the following page the user is presented with two different ads for white convertibles: one domestic and one import. The user clicks on the ad for the foreign make and continues down this avenue. In this case, the end result (user clickthrough) would have likely not have occurred if ads were randomly selected. However, through analyzing user behaviour and retargeting ads as the user navigates, the advertiser is better able to gauge user interests and tailor advertising content to better suit the users preferences.

Through retargeting, the advertiser (and website) are able to provide more interesting, relevant advertising content which leads to the user taking the desired action. Retargeting allows both websites that host (and are paid by) advertising and advertisers to maximize the number of effective impressions and ultimately achieve higher click through and conversion action rates, leading to greater exposure and sales.

As an advertising platform, AffinityClick takes the concept of retargeting one step further. Our approach is to analyse publisher content and match content keywords to advertising for optimal placement of ads. We further refine this placement by using aggregate network behaviour data and [anonymous] user session data to retarget ads for even greater efficacy and user relevancy.

The results of retargeting: greater revenues for websites with advertising (especially if they are paid on a Cost-per-click basis). Advertisers enjoy greater return on investment for pay-per-click campaigns through more engaged clicks while minimizing poorly matched positioning which chews through impression budgets. And for users, it ensures that advertising content is more topical and interesting and less distracting to them for a more useful browsing experience.

There is a rumour on the street that Twitter is once again in acquisition talks. This is no surprise. In many ways it is the belle of the social media ball and all the big Silicon Valley princes want a dance and shot at her hand in marriage. More specifically, two princes are vying for Twitter’s attention: Facebook and Google.

This time around, Twitter’s valuation has ballooned to 11-digits: $10 Billion. Having doubled in value in under a month and pushing it into the range of stratospheric multiples (220 times earnings…time to buy tulips?) that’s a lot of zeros on a golf cheque. Whether or not that is a reasonable price is an entirely separate discussion for another time.

But this article isn’t about the price Twitter can command, nor is it about Facebook, other than to say that I personally hope that Zuckerberg and company are not successful as a suitor. Facebook is a walled garden with a somewhat dubious track record for doing the right thing. Not to mention the prospect of Farmville on Twitter makes me cringe.

The reason I’m rooting for Google is because, to me, the real value in Twitter is in the constant inflow of up-to-the minute data generated by its users. This data is valuable not only from a commercial perspective (read ‘advertising’) but also in a more meaningful social context.

Curation is a big thing right now. Personally I think the term does a huge disservice to those who actually curate things for a living. It’s a tough job and deciding what’s important and saved and what get’s discarded or devalued; it is more difficult while you’re inside the fishbowl. The fact is that in the digital world storing data (e.g. Tweets) isn’t as big a problem as finding and accessing the data you need when you need it. Twitter produces a torrent of data, some 90 million tweets per day (as of November 2010) and growing exponentially. While arguably many of these tweets have the shelf-life of toast, some are very significant (as witnessed by recent events on Egypt) and en masse, form an intricate tapestry of collective context.

Unfortunately, Twitter’s current infrastructure is fragile at best and can barely manage its data as it happens, let alone anything it has archived. The Fail Whale, Twitter’s unofficial mascot held aloft by his bird friends and displayed when the site encounters technical troubles and overloads, collects more frequent flyer points than George Clooney’s character in Up in the Air. Searching for anything older than a few days is an exercise in futility: Twitter’s “Older Messages temporarily unavailable” warning in reply to searches has proven itself as temporary as Cambrian granite.

Google, on the other hand, knows how to collect, store, manage, and search data. Very, very well. Google also has a massive amount of computing resources (estimates peg GOOG’s server inventory in the 500,000 range) and knows how to operate a service with a high degree of robustness—when was the last time Google was down? Google is also desperate to gain a toehold in the social web (Orkut doesn’t count…unless you’re in Brazil) and seems to have had a dry spell on the acquisition front as of late (most famously, Groupon’s spurning of its $6 Billion purchase offer). If Google weds Twitter, they gain an invaluable amount of real-time data that also meshes very nicely with their lucrative AdSense/AdWords model from the union (I should add, AffinityClick *also* offers CPC ads! Twitter, call us!) But it’s not a one-sided deal: Twitter gains access to Google’s deep computing resources, talent pool, and operational expertise, and, of course, a nice payday for all at a valuation which seems very…generous.

But to me, the sum is greater than the parts. I want all that raw, unfiltered information that pours out of millions of Twitter users to be organized, catalogued, and preserved through Google’s massive data index so I can pluck the needles out of Twitter’s haystack. Fewer Fail Whales would be nice too.