How to analyze website revision results explain page data analysis methods

 

 

wrote an article before, and used to share with you.

Before the

analysis results, it is necessary to review the revision for what.

usually, there are two types of website revisions:

1., because the content of the website itself expands, cause present website framework to bear no more content,

2. leads to web transformation based on changes in website user needs.

of course can not rule out purely for the appearance of the site and make revision decisions. (this is rather thankless.)

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What’s the

revision expectation?

of course, this is also an important question that needs to be faced before the website is revised: what value can the website be expected after the completion of the revision?

How does

get results

?

can mainly come from three aspects,

collects active feedback from users by arranging online surveys of new pages.

receives user feedback directly from the service department.

data analysis of the new page to get the results of revision

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the following focuses on page data analysis methods

because the revised website will surely lead to a variety of user reaction sites even rebound? And this reaction is a concrete manifestation of data fluctuation, a clear analysis of these data can help us understand the user’s response, and how as smooth as possible to reduce their volatility, the revision towards better results.

1, take data

the first revision of the line on the page for weeks before and after PV, Session, and page Jump revision (single path down step) or multi step path, personal feel taken before and after two weeks a month of appropriate data.

two, contrast

revision page before and after the PV, Session can macro understanding, revision before and after, page access, viscosity changes.

on a hop data (PV, session) as the data perspective, when data taken advice Url categories and subcategories are taken out, at least a small class to take this perspective when you can analyze small classes, get each block to block access fluctuations, fluctuations in the analysis with Url. This analysis is a key, a multiplier. The on-line analysis before and after PV and Session [(proportion of each small class PV/ PV session) in]<>

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