This week we covered Advertising. We looked at some of the older types of digital advertising, such as banners, and how to determine when to place them. Banner advertising relies on users randomly browsing websites, and then the advertiser determining what ad to display to the user. There’s only a small amount of information available used to decide what ad to display, such as previous search terms, or previous pages visited. This means there’s a relatively low information value for an ad to a visitor, leading to a low click rate, and a low ROI.
This leads to learning about the difference between knowing a full set of inputs to calculate the best outputs, versus only knowing a subset of inputs, and trying to calculate the best-available output. This can retrospectively be compared to the absolute best output, and the ratio between best-available output and absolute-best output can be used as a metric to understand the value of a particular algorithm.
My reflection is that advertising is really the business of attracting attention of people. There is 300 hours of new YouTube videos uploaded per minute. So can a person gain the attention of others to view their video? There’s some choices:
- Improve the discoverability of the video (get people to the video);
- Improve the informational value of the video (get people to stay on the video).
People can tell others that a video is good, and that is social media. The system can tell others that a video is good, and that is the platform. Advertisers can tell others that a video is good, and that is advertising. Therefore if we think of advertising as the business of attracting attention, it’s also in competition with platforms and social media. This probably explains why Google created a social media platform (Google Plus), owns a platform (YouTube), and why Facebook has invested heavily in video sharing.
Anyways, back to the topic of advertising. As advertising matured, the more recent innovation is advertising auctions, where advertisers bid on keywords, which they then pay for as clicks are received. Google’s platform is known as Adwords.
When it comes to displaying ads on a query, the problem boils down to:
- How many ad slots are available on a query page
- What are the bids that advertisers have for a query
- How effective is the ad for that advertiser (since Google only gets paid on a click, not just an impression)
- What budget is available (since advertisers don’t have unlimited budgets).
- Looking at the bid per advertiser;
- Looking at the quality of the ad (based on previous click rate);
- Looking at the attractiveness of the ad (described as format impact);
All of the above values calculates an ad’s Ad Rank. An interesting component is that they use a Vickery Auction, where the winning bid is equal to the bid of the second highest bidder. This determines who should win (the highest bidder), and what the market price should be (the second highest bid).
Of note is that there is the possibility of gaming the system, known as Click Fraud. Because advertisers pay for clicks as a proxy for attention, automated systems can generate clicks on ads, which appear legitimate, but because it’s not actually a person, the advertising doesn’t have any benefit.
That’s why other metrics of engagement, such as Facebook Likes may be better measures of attention than just clicks.
I think that clicks as a proxy for attention as a business model is vulnerable to a different business model that more accurately measures attention. If we define attention as someone listening to a message, understanding it, and actioning it, then perhaps we could:
- Ask people if they believed the link was valuable to them (whether that be an ad or a social media interaction);
- Measure understanding (perhaps using product engagement online);
- Measure actions (perhaps by measuring if further activity around that ad, i.e. searching on Amazon for alternatives).