This is a quick introduction to the concept of automatic search engine optimization where a website dynamically adjusts itself for SEO.
The most common example is A/B split testing of Ads where 2 versions of an Ad are tested for which one produces the best result. But it soon becomes more complicated than just a decision on which Ad performs best, other factors may be involved too such as time of day, season, placement on the page, and visitor demographic.
But even measurement of the result can become complex. In it’s simplest form, the result, or rather the goal of a banner Ad may be to achieve maximum click through ratio (CTR). This is good since it is an aim to create maximum targeted traffic to an offer. But ideally, the goal would be to get a sales conversion.
So our measurement of performance of a particular Ad conversion can stem from it’s initial impression on a web page to a completed sale. Feedback of a successful sales conversion is often done by what’s known as a tracking pixel. This is something that an affiliate supplies to their merchant partner to unobtrusively place on the sales order confirmation page. The pixel code is hosted on the affiliate’s own website so that it runs a script to log the conversion.
By varying the parameters of the original pre-sales page and attaching tracking ID’s to elements on the page such as the banners and links, we are able to find out what combination of web page elements creates the highest sales conversion.
Moving in the other direction, we can look to place tracking IDs on our sources of traffic. With organic search it is difficult, but with Pay Per Click Ads, it is easy since there may be a “display URL” and an actual URL that can contain tracking IDs in the link.
So it’s possible to track each step from the search engine to the completed sale and optimize our Ad text (in the case of PPC) and our landing page.
Now we have considered the tracking of conversions, let’s think about how to implement automatic search engine optimization. This implies dynamic adjustment of our elements such as the banners, the Ad text, the timing of delivery etc.
But the problem is that the number of combinations soon become huge. So it needs sufficient visitor traffic to optimize everything.
A better approach for us ordinary Internet Marketers may be to recognize the chain of events from search to purchase (the funnel), and optimize parts of it in groups, such as the sales price, the appearance of the buy button, the Ad content etc. Then we may get a quicker idea of what most affects our profit and optimize those factors first rather than having an over all optimization scheme that simply takes too long to work.
A quick start may be to identify sites that are probably already using these techniques and take ideas from them for starting points.
So I think my conclusion is that in theory Automatic Search Engine Optimization is possible, but in practice it will need manual decision making to optimize things in a reasonable time frame.
I would love to hear your opinion in the comments …