Web site operators are doing, APP operating time, pay attention to event-level analysis, such as a button click event, funnel conversion rate, just look at PV, UV can not get action guidance, UV more than a little too little, can not be reflected more with less, and to complete the transformation of our users really flow of a lot worse.
For example :
We want to see added to the shopping cart and submit the conversion rate between the order, if it is 80%, then why 20% of people will be lost?
We know that such information will undoubtedly help us achieve conversion rate optimization, let's get more orders in the same amount of advertising costs.
This is the premise of all event-level analysis, we need to know ADD TO CART event and the number of users, but also need to know the number of events to submit orders and users.
Free analysis tools on the market, only to analyze page views, want to know the analysis of events but also so easy to use, full-featured, comprehensive dimension, it was only Analysys Ark Argo family.
How do we know the number of clicks and the click of a button users? The answer is the need for data buried point.
What is the point of data buried?
In addition to those explained on the search results can be seen, buried data points would be understandable, if you want to know the clicks this button, then you need when the button is clicked, the implementation of a code, which by a hidden on the site or APP line (SDK) this button is clicked this small, imperceptible transfer you to the event in Analysys Ark Argo, so Analysys Ark Argo on the record of this button is clicked once, through some rapid and complex calculations, it became an icon, a quick show in the interface, to achieve event-level data analysis, and execution of a piece of code that is buried point.
Buried after performing the data, you can analyze the event, select an event to see event-triggered trend is not very simple?
Buried in the data content
Buried product data can be divided into internal market and Buried Buried, points are usually buried inside the analysis of user behavior using the product and processes, improve the user experience. Buried market analysis of the product on the market performance and user usage scenarios, such as product downloads in different markets and geographies, different regions people use time, etc.
Product flow is usually divided into the trunk and branches the process flow, the corresponding data points can be buried into the trunk and branch Buried Buried, Buried data not usually get step, when the first line of products usually buried in the following points: PV PC & Web statistics would end product / UV, registrations, the conversion rate between the main flow page, Nikkatsu number and so on. The statistics also move end product downloads in the Appstore, major Android market.
The second point would be buried according to the analysis of the problem and the target product line. For example, when you find the products Home UV high registration volume is very low, you need to analyze the user's behavior in the home, for example, if 30% of the users out of the product, 60% of users into the registration page, but only 1% of the registered user of the product. This means that the registration process may be a problem, we need to further refine the various registration processes, increase data Buried, analyze conversion rates between the various processes, find and solve the problem with the product.
Specific to their products, how the data buried point, we need to design the product according to the task flow and target their products. This is a coarse-to-fine, iterative optimization process.