How Buyer Factors Increase Web Site Sales - Using the Landing Page Optimization Tool
To improve conversion rate and increase web site sales you must account for buyer behaviour as this conversion rate predictor shows
Using the pay per click optimization tool it is easy to show that for the same volume of visitor traffic, small changes to improve conversion rate can provide a big increase in web site sales.
A landing page design with a better conversion rate of visitor to sales, not only means an increase in web site sales, but it also means you can afford to pay to get more traffic to the page.
However knowing what changes to make to a landing page design to improve conversion rate is not a matter of guesswork or what you think will improve the landing page.
The only proven way to improve conversion rate and establish which improvements to a landing page design actually increase web site sales - is by testing.
Such tests are known as AB split tests or multivariate tests.
Standard AB Split Testing to Increase Web Site Sales
AB split testing is quite simple and involves sending visitor traffic to one of two web pages. One page normally acts as the reference design and the other page will have one change made to it, compared to the reference.
The splitting of traffic is done with a split testing script that also tracks what page each visitor is presented with. Should the same visitor return to the page this ensures they always see the same page they were first presented with.
The results of an action on each landing page design are compared and the page with the greatest increase in conversion rate can be determined.
The action could be a sale, completion of a form or whatever the purpose is of the landing page design.
Multivariate Split Testing to Increase Web Site Sales
Multivariate testing is more complex and frequently uses Taguchi statistical techniques to determine which landing page design is producing an improved conversion rate.
The advantage of multivariate testing is that many changes can be made to the landing page design and tested all at the same time. This can not be done with standard AB split testing.
Using multivariate split testing also means that since it is possible to test many design changes at the same time, the whole process of landing page optimization can be completed much more quickly and with less visitor traffic.
If you are paying to drive traffic to a ppc landing page then multivariate testing can save you a lot of money and time.
A page that takes weeks or even months to optimize using conventional AB split testing can be done in a few days using multivariate testing.
Improve Conversion Rate
Clearly the advantages of this sort of testing to improve conversion rate must be obvious and yet it is still only used by big companies and a few of the top marketers on the Internet.
Why these powerful techniques are used by so few I’m not sure, but cost may be a factor as well as a lack of knowledge and understanding by web site owners.
Multivariate testing scripts are expensive and usually not available for less than $450.
While split testing will help improve conversion rate and hence increase web site sales, there are other factors that influence visitor behaviour that can also have a dramatic effect on landing page optimization.
Effects of Buyer Behaviour on Web Site Conversion Rate
Visitor behavioural factors include things like visitor motivation, the level of anxiety experienced and whether they have the necessary funds to make a purchase.
Other factors that affect buyer behaviour are the value of the proposition as perceived by the visitor to the landing page. There are also the incentives to buy that are offered and the extent to which the buyer experiences problems or difficulties completing the sales process – a.k.a. sales friction.
The various relationships between these buyer behaviour factors are demonstrated in the Landing Page Conversion Rate Predictor shown below.
The Landing Page Conversion Rate Predictor
The calculations performed in this landing page conversion rate predictor are based upon an algorithm developed by MarketingExperiments.com.
The mathematical model was modified by me to avoid negative probabilities and probabilities greater than one, that occurred in the original model. I have also included an additional factor, namely available funds.
Clearly if the visitor does not have the funds it does not matter how good the landing page is in terms of the value of its proposition, or the incentives being offered, the visitor will be unable to afford to make a purchase.
The landing page conversion rate predictor is calibrated to assume that with all factors being at an average of 5 on a scale from 1 to 10 that this results in a typical landing page conversion rate of 1%.
At the other extreme with all positive factors like motivation, value proposition, incentives and available funds at 10 and negative factors like anxiety and sales friction at zero the predictor is calibrated to show a 100% conversion rate.
In other words every visitor who comes to the perfect landing page will buy the product or perform whatever other action is required.
To improve conversion rate and increase web site sales click here to discover more
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