If everyone starts subtracting swaths of visitors before they calculate the conversion rates they report it will be impossible to understand or learn anything comparatively. Numbers like those we get from shop.org, disappointing as they may be, are useful so long as we can assume we’re all measuring the same thing.

On the other hand, internally and incrementally, there is an absolute need to dig deeper and measure conversion both more narrowly and against a broader range of targets.

I also agree with John Quarto-vonTivadar that tossing bounces wholesale isn't the right solution - those occur in quantities way beyond indiscriminant clicks or an inability of the page to impact the visitor. Before you discarded them you’d have to consider the sources of these ‘bouncers’ – those coming from paid search, email replies, banner ads, and even organic search clearly had some expectation and goal when they clicked. Could a few percentages of them suffer from muscular tics and poor hand-eye coordination? Sure. But more than that and I’d really want to think about why the site/page was so non-compelling as to result in their near instant departure.

Given that bounce rates are commonly quite high (Avinash suggests 30% as typical and we’ve certainly seen them much higher) and it would make sense to segregate that problem – may I suggest a ‘Lingering Conversion Rate’ which applies only to visitors who visit at least two pages or stay at least 20 seconds?

I really like the ‘conversion pie’ Avinash created, as a way of visually expressing the fact that many visitors come with intents (or potentials) which exclude purchase. It would be great to take it further and have the ‘non convertible’ segment replaced with success and failure slices for the other intents which users manifest via their behavior. Determining and categorizing these intents and their achievement is of course quite difficult today – but I think this is an area where we need to do some work and we need our vendors to help.

For example, suppose we know that a good number of our visitors come to do pre-purchase research. Wouldn’t it be nice if we could flag users based on terms they use in their searches (‘compare’ ‘reviews’ etc.) or some combination of links clicked or pages viewed and then get associate success events with each of these segments and get both detailed and comparative reporting? I’ve mocked up the kind of report I’d love to see. (click to enlarge)

Thanks and congratulations to Avinash (again) for the original insights.