[LMG S6] Issue 68: The Age of Bloat
Previously: Each click on a link, or even an ad, sends data to the server. This information can include an ID for the link you clicked, or the category of ad you clicked. But without Javascript, the webpage can’t know very much about you.
The dot-com bust
Once Javascript was made available … surprisingly little happened on the ad front. Javascript could animate your pages and make buttons that changed image or even changed colour when you clicked them. But it was doing little else for now.
3 years after Javascript was announced, the online advertising industry had achieved revenue of $4.6 billion. It’s hard to imagine that this was largely achieved through banner ads alone … many new companies were being founded, there was lots of capital in the market, and it looked like the Internet was the new growing industry, with stock prices continually soaring beyond what people could imagine.
On March 10, 2000, the NASDAQ Composite stock market reached its peak, and then it all went downhill from there. It was the dot-com bust which welcomed the 21st century.
The old model of advertising: cost-per-mile (CPM)
Past online publishers (who displayed ads on their sites) primarily used a CPM model of pricing (“cost per mile”, which was interpreted as “cost per thousand ads served”). You paid for a certain number of ads to be served on a certain number of pageloads, and that was it. You could pay more to have your ad served in a more prominent slot, or to have more ads served, and that was it.
You would often have little idea who saw it or who clicked it, and you just sat and waited for the clicks to come through. Sometimes they did, and often they didn’t. It was cheaper than highway banner ads and huge posters on buildings, but it was still expensive.
Recovery and restrategising
As freeflow cash quickly shrunk during the dot-com bust, many companies began to rethink their advertising campaigns. They could no longer just spend freely on banner ads that online users were getting accustomed to. The pop-up ad, invented in 1997, was being blocked by non-Microsoft-owned major browsers (Netscape, Firefox, and Opera) around the time the economy started to recover from the bust. New services were needed, new value needed to be created.
The dot-com low lasted until early 2002, when stock prices finally started to pick up again. Google led the rise with its revamped Adwords.
Google Adwords, revamped after its premature introduction 2 years earlier, offered a CPC model: cost-per-click. You only had to pay if somebody clicked through the ad to your site, not if they ignored the ad.
This was not a new innovation: Yahoo already offered a similar model back in 1998. That was a flop, because Yahoo didn’t know enough about its users to optimise the click-through rate.
Google innovated over the old model in one unique way though.
The new model: cost-per-click (CPC)
Early CPC models literally just counted clicks on a link and invoiced you accordingly. As the number of advertisers buying ads rocketed, the publishers switched to an auction model: highest bidder wins. This model disadvantaged smaller companies, who had much smaller advertising budgets, and could not out-compete the big ad-buyers on price.
Google (back then still a tiny company) saw this and, inspired by its search engine algorithm, introduced one change to it: if an ad with a lower bid got more clicks than ads with higher bids, it could climb the ranking ladder.
Now the race is on to grab every user click, with new services and web media. Facebook launched in 2004, YouTube in 2005, Twitter in 2006.
The search for unified user data
There was just one problem: these companies still didn’t know very much about the market. Every company had a piece of the puzzle: Online publishers knew a bit about its users: what time they visited most often and their approximate locations. But they didn’t know what kind of ads their users wanted, and they have to balance the annoyance their users experienced with the revenue that could be brought in by online advertising.
Ad buyers, on the other hand, mostly knew who their target market was, but had little idea how to reach them. They had to make a guess, or talk to online publishers to see if there was a fit somewhere.
Analytics companies such as comScore and Nielsen quickly saw this need, and started researching demographic behaviours online. But this didn’t work for niche markets, or when data was lacking.
Ad servers (such as Doubleclick, whom you already met in Issue 66) helped to aggregate advertising slots from online publishers. But they were not in a place to gather data on the users; users were not visiting their site. Nor were they in a place to gather the disparate information from online publishers and ad buyers to build coherent profiles of users.
That piece of the puzzle would come later. Konrad Feldman and Paul Sutter, who noticed the surge of interest in search advertising after Google’s IPO in 2004, and were working on an interesting puzzle: “How would we get direct data on users of sites that we don’t own?”
They figured it out two years later, and founded a company called QuantCast.
Issue summary: Advertising was sold on a CPM model (cost per thousand impressions) in the early Internet, until the dot-com bust forced companies to reconsider their ad-buying strategy. The CPC model (cost per click) became more popular, but was still not very user-targeted. It would take QuantCast, founded in 2006, to figure out a way to gather data on users and build a coherent profile of each demographic.
What I’ll be covering next
Next issue: [LMG S6] Issue 69: The Cookie Monster
We will take a short detour next week so that I can explain what cookies are, how they came about, and what they do. It’s the linchpin for understanding how modern online advertising works today.
Sometime in the future: What is:
- booting up? [Issue 15]
- a cookie? [Issue 8]
- XSS? [Issue 8]
- a CDN? [Issue 8]
- a good reason developers write code and give it away for free online? [Issue 21]
- firmware? [Issue 34]
- OpenType? And what are fonts anyway? [Issue 42]
- What is involved in installing a piece of software? [Issue 48]
- How do apps know where a file starts and ends? [Issue 49]
- What is a password hash? [Issue 63]