Online and offline customer behaviors are not world apart, in fact they relate to each other very much. For example, if you ever walked into a real life retail store and moved out without buying something then you have already sent a message to the retailer and same is true when you visit the online e-commerce store and close the app or website without buying anything. The only difference is that in case of real life you can wander in the mall and can simply kill the time. People who visit online stores are usually looking to buy something or are comparing the online and offline prices. By analyzing their actions and other online customer behavioral data one can see very clearly that why the customers are not buying the goods and then can take the appropriate steps.
Bounce rate is one key metric to which retailers must pay significant attention. Search engine ranking of a particular retailer often decide its click through rate (CTR). For example, the web page in the no.1 position will definitely have more CTR’s then the page in no. 8 position. Instead of looking CTRs one should look for the bounce rate which is nothing but the visitors which leave the site without checking out any other pages. Bounce rate is a better indicator of the site’s viability as higher bounce rate usually means that wither the product price is too high or the comments for the products are negative.
It also means that there is not enough information available about the product or the product does not solve the intended purpose of the customer.
Focus on the web page’s bounce rate and you will automatically improve your usability, conversion rate and search engine rankings.
Trying to understand what’s not working on the site can be very complex undertaking. But, if you really want to nail down the truth then turn to A/B testing where all elements of the page are kept same except one variable. The data that these A/B tests generate can be synthesized by the analytics but retailers will still need someone to examine the data, draw conclusions and tell them what it is that needs to be changed.
By testing the site retailers can decrease the bounce rate and keep the visitors from leaving the site.
The other way to get sense of what is actually attracting the consumers attention is by using the visual analytics like heat maps. The technology is capable of tracking the customer’s movement on page by following the mouse movements, scrolling and clicks. This visual representation of data can be very useful in designing the site in order to attract the consumer’s attention. But, to use this effectively one must use the information in right context. For example, a pink colored dress might catches the attention of the customer but if she does not purchase it then this is the indication that she might not like the style or something else in it.
This process is not fully automated and retailers need someone who can interpret the data for them. But, still analyzing the results from the A/B testing and heat maps can help in ruling out some unnecessary variables. For example, if the prices are too high then test lower prices which yield high CRTs and this will clarify that indeed high prices were barriers to sale. In any case no matter the testing, retailers must pay close attention to the data to see what pattern emerges.