Focus on user tracking and analysis-cross-screen tracking

With the rapid growth of mobile internet, in the multi-screen era of screen tracking has become a hot topic in the analysis of the Web site, but also become a site analyst can not ignore the problem. One of the major changes in the Google Analytics upgrade to Universal Analytics is support for cross screen, cross device visitor tracking. The commercial-level Web analytics tools of Adobe Omniture and Webtrekk are also starting to support the focus analysis between multiple screens. Cross-screen analysis seems to have become a standard configuration for Web analytics tools.

1, why do we need to cross screen tracking?

Before we start talking about the importance and value of cross screen analysis, let's briefly review some background information. This is how our web analytics tools define, differentiate, and compute unique identity visitors? Here's a look at the basics.

Visitor definition

Web analytics tools rely on IP or cookies to define visitors. An IP address or a cookie represents an audience. Early log analysis tools relied on IP addresses, but because of the presence of multiple people using an IP address, such as an internet café, or a school room, etc. So most web analytics tools now define visitors as cookies. A cookie is a text file stored in the visitor's browser that is used to record the identity information of the visitor. Of course, there are analysis tools that can be customized to continue defining and tracking visitors by IP address when the visitor's browser disables cookies.

Visitor Distinction

The cookie that defines the visitor has a string of unique digits, and the only number is the ID of the visitor. The visitor ID returns the server for the Web Analytics tool along with other metrics each time the visitor visits the site or browses to the page. The Web analytics tool distinguishes the identity of the visitor through the unique number ID in the cookie string. If you find that the visitor IDs are the same in more than one log, you are judged to be from the same audience for these access or page browsing behavior.

Calculation method for unique identity visitor

Web analytics tools are used to calculate the weight of visitors. In other words, the Web Analytics tool provides unique identity visitor data. The following three tests show how the site analysis tool calculates the number of visitors.

In Test 1, the visitor is ranked by the time dimension.

By taking out the data for a site visitor for a week, and comparing it to the weekly summary visitor data provided by the Site Analytics tool, you will find that the audience rollup data in days as dimensions is greater than the visitor data in the Zhou dimension. The reason is simple, a visitor visited your website 7 days a week in a row. The day is the dimension, and every day the visitor is unique. The visitor data summarized by day is 7. And with Zhou as the dimension, in these 7 days only 1 unique visitors, visited the site 7 times. From the point of view of data accuracy, the visitor data after weight is more accurate.

Test 2, to rank the visitor by source dimension.

The exclusion of visitors by source dimension is similar to the previous example of excluding the time dimension, by summarizing the visitor data distributions from different source dimensions and comparing it with the site visitor data for the same time period, you will find that the visitor data summarized by source is larger than the site's visitor data. Because the same visitor may visit your site through several different channels or media over a period of time. This visitor is unique if viewed only from a channel or media dimension. However, from the perspective of the Web site, there are only 1 visitors, regardless of the number of visitors ' sources.

Test 3 to rank the visitor by content or page.

In addition to the time and source of the weight of visitors, there is one of the most likely to be misunderstood in the data statistics, that is, according to the page of the site to the audience weight. This sort of weight is very similar to the previous two types of tests, except that the time dimension and source dimension are replaced with the site pages. Therefore, if you will be able to access each page or each channel individual to take out and summary, then this data will be significantly larger than the number of visitors to the site dimension. Because a visitor may have seen multiple channels or pages, the visitor is unique from the dimensions of each channel or page, but there is only one visitor from the higher level of the site.

Wordy Here you may have noticed that in order to ensure that the unique identity of the data is accurate, the Site Analytics tool calculates the audience from the dimensions of the entire site. The premise of all this is that Web analytics tools can identify and differentiate this visitor in different dimensions. But in the actual access scenario, there are some dimension Web site analysis tools that do not have the means to do the scheduling. For example, different browsers, and different terminal devices. Because the site Analysis tool relies on the definition of the visitor's ID stored in the cookie, the cookie is based on the browser side. In other words, visitors have different visitor IDs in different browsers or devices. This leads to web analytics tools that do not have the means to rank visitors in the browser and device dimensions.

From the point of view of technology and index computing, the main function of this new function of cross screen tracing is to precisely define and identify visitors across different browsers and devices, and to cross screen, recognize and weight the equipment. Make the unique identity visitor data that we get more accurate.

2, the principle and implementation method of cross-screen tracing

At present, most web analytics tools implement the principle of cross screen tracking, which is to define and identify visitors among different devices through the unique identity of the visitor. Then, on the server side, the device that the visitor uses, the access behavior is excluded and summarized by the unique identity. But in a cross screen trace, this unique identity no longer comes from the visitor ID in the cookie. Instead, it relies on the unique identity of the visitor in the site. In other words, the web Analytics tool gives the Web site the task of identifying users across screens across devices. And this unique identity, usually the visitor's login account. When a visitor completes a login in the Web site, it is used as the unique ID for the visitor.

Take Universal analytics as an example, if you want to cross screen tracing for your visitors, you need to add a line of code in the global code to get the unique identity ID of the visitor in the site. and return this ID to the Google Analytics Server. For subsequent weight and rollup processing.

1ga (' Set ', ' &uid ', ' Visitor unique identity ');

We take bluewhale_test as an example of the unique identity of the visitor. This code should look like the following in your page's global code.

1234567891011<script> (function (i,s,o,g,r,a,m) {i[' googleanalyticsobject ']=r;i[r]=i[r]| | function () {i[r].q=i[r].q| | []). push (arguments)},i[r].l=1*new Date (); A=s.createelement (O), M=s.getelementsbytagname (o) [0];a.async=1;a.src=g; M.parentnode.insertbefore (A,m)}) (Window,document, ' script ', '//www.google-analytics.com/analytics.js ', ' GA '); GA (' Create ', ' ua-12347890-11 ', ' bluewhale.cc '); GA (' Set ', ' &uid ', ' bluewhale_test '); GA (' send ', ' PageView ');</script>

When the code is executed, we can discover and verify two things, first, after the visitor is successfully given a unique identity, we can see in the return data that this visit and page browsing behavior belong to the user bluewhale_test. Second, the visitor's unique identity is not stored in the cookie, but is sent directly to the Google Analytics Server.

When the visitor logs on to the site on another device, we will also give him the Bluewhale_test logo. This allows us to identify the visitor on the server side and merge the behavior of his access between different devices to achieve visitor tracking across the screen and terminal. But here is the problem, that the visitor must complete the login operation before it can be identified. What if the visitor only visits the site without completing the login operation? Here we introduce a strengthened version of cross screen tracing, which resolves the webtrekk user tag problem with the unique identity Id+cookie identification method.

3,webtrekk Enhanced cross screen tracking

When a visitor registers or logs on the site, the Webtrekk system identifies the visitor's user name as the unique ID of the caller. This is no different from the method and process described earlier. But Webtrekk also does one thing in the background, associating the current visitor's unique ID with the visitor ID in his cookie. So without deleting the cookie, the next time the visitor visits the site, Webtrekk can identify him again and associate him with previous historical behavior.

The chart above shows a clear picture of the process. When the visitor logs on, Webtrekk associates the visitor ID in the cookie with the unique ID of the URM. The URM unique identity ID is used to identify the user, and the different visitor ID based on the cookie is assigned to the unique ID. If any unique identity ID is sent to Webtrekk, the associated cookie visitor ID is added to it. The URM unique identity ID is only used when the first association (green Arrow) is associated. The association mechanism is then independent of the URM unique identity ID (Gray arrow). In this way, when visitors are no longer logged in, we can also identify the visitor based on the associated relationship that was established.

4, overview of cross-screen reports and changes in indicators

With the cross screen tracking feature, we can see more accurate visitor data and visitor usage paths between different terminals in the Web Analytics tool report. Let's take a look at how the tool calculates the number of visitors and the path of the terminal device by taking the Universal Analytics report and the Webtrekk Cross screen report as examples.

The first is the device path report in the Universal Analytics Cross device report. We can see two important information in this report. The first information is the device path. This shows that visitors have visited the site through two different devices, desktop and mobile respectively. The second message is the number of users and the number of sessions. When the cross screen tracing feature is not used, it is recorded as two visitors and 3 sessions. After using cross screen tracing, only 1 users and three sessions are displayed through cross device exclusions. Data more accurately.

The second is Webtrekk's Cross screen report. Through this report we can find out the use and order of different devices for each unique identity visitor at different times. This is much richer and more detailed than the content provided in the previous Universal Analytics report.

5, what are the issues that the cross screen tracking solves from the business?

We have been talking about the role of the cross screen tracking function from a technical perspective. But his greatest value is at the business level. Below we separately from the website main, the website analysis tool and the advertisement main three different roles embarks, looked down the cross screen tracing in the business solves what problem.

Site main role:,

From the site owner's point of view, the greatest value of cross screen tracking is the accurate positioning and tracking of human data, rather than browser data. The visitor's data is no longer an island of data fragmented between different browsers and devices. We can effectively correlate the access behavior of visitors to different devices and get complete access behavior and device paths.

Web Analytics Tool Angle:

From the perspective of the Web analytics tool, cross screen tracking is very promising to get rid of relying cookies to locate and retrieve visitor data. Cookies have always been an important part of web analytics tools to get visitors ' behavior, but the link is so fragile. Visitors, browsers, and plug-ins all affect the accuracy of cookies and data. Now, web analytics tools have been changing methods to reduce reliance on cookies, transferring most of the data records and matching work to the server side. The only thing that needs to be recorded with cookies is the identity ID of the visitor. And through the spread of the screen tracking function, most visitors will be marked by the site. This will greatly reduce the problem of data accuracy caused by the deletion of cookies.

Advertising Main angle:

Finally, it is also necessary to look at the value of cross screen tracking from The Advertiser's point of view. We do not know whether the data and information obtained by Web analytics tools will be used for accurate advertising. But from The Advertiser's point of view, the more accurate unique identity visitors and the long-term access to historical behavior data across devices is really valuable for accurate advertising.

-"From the" Blue Whale website Analysis Blog ""