Search Traffic and web analytics: easy to understand and difficult to do

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A popular speaker, due to time constraints, asked her assistant to count the basic information of the audience. She prepares lectures based on these data so that most listeners can understand them.

She looked at the basic information the assistant provided to her, asking about the average age of the audience, the status of their income and their educational level.

The average age of the audience is 36 years old. The income was 30,000 dollars a year, far less than she had expected, and far less than most of the people who had heard her lectures before. Literacy was also lower than expected, and the audience was educated only at high school level.

So she had to readjust her speech to better fit her audience. But on the day of the speech, she had to face an awkward situation: a group of retired CEOs and their grandchildren to attend the lectures.

The retired corporate executives, with their impressive academic credentials, and the savings and investment outside the bank, are still living, and most of their grandchildren are in Grade 2 and 3.

The moral of the story is clear. Contact to the search traffic data statistics, we should also be cautious, in-depth analysis of the content behind the data, and strive to have a full and comprehensive understanding. Instead of spending time validating or refuting your intuition, you might as well take the time to revise the data that you believe in.

Beware of averages

As the little story above mentions, don't believe too much in averages. There are a variety of data statistics for search traffic; some charts (such as search engine backlinks and access times during the day) will be normal, with a bell, and other charts (such as hot search terms) will have a big head and a long tail behind them. I've also seen some of the U-shaped or camel-like Shuangfeng in the company I worked with.

Some of the above charts, if you use averages to represent the whole situation, will undoubtedly produce errors. So, generally speaking, when you want to estimate the overall situation of the data, you might as well chart it out first.

Can you tell the true reverse link clearly?

Because each site's data analysis software is not the same, some software may be sharp to identify the major mainstream search engine services provided, and some do not. Most statistical software is able to figure out which traffic comes from PPC (Paid-for-click Business) and which are from natural rankings. However, in traffic from natural search, you sometimes see traffic totals for the following services (GOOLGE,YAHOO,MSN):

1. Regular search Business

2.Blog Search

3. Mail

4. News Search

5. Panel (Groups)

Therefore, you need to carefully study the statistical reports of the analysis software, based on these data, to plan appropriate advertising methods.

PV, also PV

The operator of the company will unconsciously measure the success of the online advertising that is being put on a standard. The Click Conversion rate has finally become this important indicator. Of course, there are other indicators that will also attract attention. Page View has long been one of the most trusted reference metrics on the site. But because of the ubiquity of Ajax, Flash, and RSS technology, the site has performed better on search engines than before, and users have spent a lot more time on the site, but Page view does not reflect these changes. Page view relies on the Web1.0 traditional click-Response pattern. In the "pageviews are Obsolete" article, Evan Williams made this point clear:

So what are the better metrics? That's a good question. Like many other good questions, the answer is "depending on the circumstances". If you want to know what is the most important thing about the site, first you have to try to determine what is the first standard of success for the site? For each site, it may be the number of subscribers, the number of paid users, the revenue or the upload rate of files, and other things that you think are important. It could even be pageviews.

Web sites that rely on high search rankings need to use the page views to present the site's user experience to future potential users. If the impact on the site is no longer just the amount of time spent, but the number of clicks based on the script between Ajax applications, or whatever, then evaluating the site with a variety of metrics will become more important to the profitability of the site.

Look at the departure rate objectively

Believe it or not, the rate of departure of your site (bounce rate: The proportion of users who visit the page and leave the page for a certain period of time) is 100%. Whether it is imported by the search engine ranking users, PPC brought by the user or from the "favorite" visitors, the end is to leave. So when you get an analysis of the exit page that refers to the last page that a user browses to at the end of a visit, there's no need to be frustrated when you see a lot of links going to the URL address elsewhere.

Some important questions to analyze:

1. What part of the user left a certain page, what is the reason?

2. Did they find what they wanted?

3. Did they complete a buying behavior?

4. Are they disappointed to leave?

If different backlinks are imported to generate different bounce rate, you can compare what the users of the search engine rankings will pay attention to, and what content visitors to the paid-click Business and e-mail business are interested in. Many of us are used to referencing conversion rates, PPC, and other types of data, but few people notice the departure rate associated with backlinks.

If a lot of people leave after visiting a Web page, you'll need to take the time to find out why and try to change it. But if they leave this page because they want to search for other words, they are likely to find content on this page. The remaining question is whether you are satisfied with the quick departure of your visitors, and of course this needs to be judged by the profit model of your site.

Big director Billy Wilder once portrayed user feedback: "An audience may be wrong." Individual views may be foolish, but when thousands of fools think so-they are right. "

I don't mean to make you a fool of your users. There is no doubt that Billy Wilder's remark also applies to the website's data analysis. If someone laughs, is it certain that everyone is amused, or is it just the sound of a two-strong-sounding guy standing at both ends of the hall?

Sometimes things sound the same, but they are not.