Sing: The core index of network marketing effect measurement

Indicators is a meaningful indicator that measures the user's behavior and processes before and after the flow is generated, reflecting, in particular, the user's interest in marketing activities/web sites and the factors that affect the final transformation. Wen/World Network Business invited author, website analysis in the Chinese founder sing in the last issue, we explained the two most important ways to measure the effectiveness of Internet marketing--measuring changes in people's minds and measuring human behavior. The change of human behavior, according to the influence from shallow to deep logic, we are divided into four stages: traffic, indicators, conversion and retention, and detailed description of the traffic situation, below for everyone detailed indicators. What is indicators? Indicators does not mean a specific metric, but a set of metrics that measure the extent to which users are involved in a marketing campaign. Since the site is part of the marketing campaign, indicators is often used to measure the degree to which users interact with the content and functionality of the site. But indicators is not only that, it can also measure the user's other ways of interacting in marketing activities, such as the user's reading, commenting and forwarding in Weibo marketing, or the interaction between the audience and the rich media ads. Indicators is a meaningful indicator that can be understood in such a way that it measures the user's behavior and processes before and after the flow is generated, and in particular reflects the user's interest in marketing activities/websites and the factors that influence the eventual transformation. So, indicators is not a standardized metric like visit. In this regard, the Americans (Avinashkaushik and Ericpeterson) also have different views, one that it is worth popularizing to become a standardized measure, one that it should not be a measure, it is difficult to standardize the application. No matter who is more reasonable, in solving specific problems, indicators has very obvious value, so in our core index system, I always think indicators is one of the most important. Indicators can be divided into two categories, one is to standardize the measurement of user behavior of the target family, the other is based on the different circumstances on the basis of the definition of the target family. The two kinds of indicators have different meanings and similar functions, and they are very important. The indicators index of Standardization Indicators index is divided into macroscopic level and microcosmic level. Macro refers to a site-wide indicators situation, while microscopic refers to a specific page of the indicators situation. Macro-indicators indicators are mainly known as "kind"--bouncerate (bounce rate), pv/visit and Timeonsite, these three indicatorsDescribes three different types of user behavior. Bounceratebouncerate explains whether users have an interest in the content of the site after they enter the site. If not, then the user leaves without clicking on any of the links on the page, so he actually sees the landing page (landing page) that the site presents to him. Bouncerate is an indicator of the technological advances that have not changed much. Some friends asked me, if a person entered the landing page, he looked at the landing page for several minutes, but did not click on any of the above links to see other pages, he was bounce off? This is clearly stated in the Bouncerate definition of most web analytics tools, that is, whether bounce or not is in fact irrelevant to the time the user viewed on the landing page, only if he or she clicks into another page. If there are clicks into other pages, then do not count out, or even jump out. So the above situation regardless of how long the visitor looked at the landing page, as long as no click on any of its links into other pages, it is still a Bounce. So perhaps the definition of bouncerate is too harsh, and the length of the page does not seem to be reasonable (and will be devoted to the question of time). But the definition is technical simplicity and the "best solution" of the efficiency principle that captures the big probability event (viewing the page for several minutes without clicking on any of the links on the page is indeed a small probability event) and has been used. Interestingly, early on, Avinash's explanation for bounce was that it was less than 10 seconds on the page/website (or 30 seconds, which I don't remember very well). However, because the user page browsing time is not easy to accurately monitor (or accurately monitor the technical implementation simplicity of the Web Analytics tool), and the alternative (that is, the current definition of bouncerate) can still fairly accurately describe what is going on in reality, As a result, most tools do not use browsing time as the basis for the definition of jumping out and bouncerate. Pv/v differs from Bouncerate, pv/visit (often abbreviated as PV/V) describes the interaction of another type of user with the site, that is, the depth of the browsing site. The more pages viewed by the user during one visit (Visit), the more interested the user is in the site. Therefore, in general, the higher the pv/v the better. Of course, interest has the active interest and the passive interest points. Passive interest is because in the site can not find the content and constantly try to find, pv/v will be relatively large, but this is not a good phenomenon. Timeonsite since talked about the depth of browsing, there is a natural view of the length of the corresponding, that is, timeonsite, refers to people visiting the site's average stay time. For example, a website has 3 visits, one stays for 2 minutes, one stopsStay for 10 minutes, one stay for 0 minutes, then Timeonsite is 4 minutes. As with pv/visit, generally speaking, this value is bigger and better. It is worth noting, however, that the time spent on the web analytics tool is certainly different from the actual time the user is staying on the site. The length of time people visit the last page of the site will not be counted by the Web analytics tool. The reason is simple, because the average web analytics tool does not count the exact time people leave a site, but only the exact time of the second page of the site, so the last time the page he visited is actually completely ignored. You will ask why not count the time on the last page? Because the website analysis tool defaults to the user closes the page the behavior, or jumps from this page browser window to the other website behavior does not make the statistic, unless you make the special setting. If you do not make additional settings, this arrangement means two points: first, the website analysis tool statistics to the site browsing time is always less than the site in the browser opened time (although the browser to open the page does not mean that you are really looking at it every minute); second, all bounce visit ( That is, a visit that accesses only one page) stays on the Web site for a total of 0. There are some web analytics tools that break this rut and try to keep track of when people leave the site. However, I personally feel that the meaning is not particularly great, unless the last page of each visit is a great chance for those who specifically need more to stay and carefully look at the page. As long as the tool statistics method to maintain consistency, then even if the last page of the remaining time, still can achieve appletoapple comparison, still can help us grasp the user macro indicators situation. Moreover, the difficulty of technology implementation is reduced, the consistency of monitoring is improved, and the monitoring accuracy is improved. (because the method of recording the exact moment away from the site is not completely reliable, only a certain probability can be counted, which reduces the actual usability of these methods.) Visit/uv and other users of viscous indicators indicators of macro-indicators indicators there is also a common, we mentioned earlier the VISIT/UV this metric. It is used to measure the stickiness of visitors visiting the site. If you like a site, you will often come, a UV will take a number of visit. The higher the number of VISIT/UV, the higher the user loyalty of the site. Other indicators metrics that indicate user stickiness, such as access frequency distributions, access interval time distributions. I've never used these two indicators in particular, and I think the best way to read them is to compare the differences between different websites and their psychological expectations. Micro-level indicators index of micro-level indicators index is essentially describedThe behavior of the user on the concrete page, the more important one is exitrate (exit rate). Exitrate is a measure of the page's chances of browsing the page as the user exits the site (compared to its total number of visits). For example, the exit rate for a page is 75%, which means that all PV that is generated by accessing this page, Three-fourths of PV is the last browsing page before these visits exit the site. What I'm trying to say here is that exitrate can be more microscopic about page indicators metrics (the first measure of the whole site indicators), which measures the performance of the page, similar metrics and averagetimeonpage, Nextpageflow. The indicators metrics for the standardization of indicators metrics, as required, describe a variety of user behaviors, but are not sufficient to cover more specific measurement and analysis requirements. For example, a site has some very important specific user behavior (action), such as registering or logging in, applying for a trial opportunity, downloading a product description, or adding a certain item to a shopping cart. For these specific user behaviors, standardized indicators metrics have no additional consideration for them. This time we need custom indicators metrics to describe the specific user behavior that is valuable. There are two types of behavior: 1. Non-standardized behavior: These actions mentioned above, such as registration, login, trial, download, click on a particular location or function, add to the shopping cart, and so on, belong to this category. 2. More targeted user behavior as required for standard indicators settings. For example, the visit length of more than 3 minutes is a more specific user behavior than a single visit, or the visit of more than 3 browsing pages in visit is also a more specific user behavior. In addition, you can set up access to a particular page of the visit, also belong to the defined conditions of the user behavior. Depending on the criteria you set, the value of the corresponding metric is different. You will find these indicators quite "arbitrary". Yes, they are indeed freely defined according to your needs, which means that the indicators indicators used by others may be completely different from yours. But we do need these indicators, otherwise we can not fully describe the characteristics of user behavior and value, can not be targeted analysis and optimization. The existence of the indicators index on demand makes the network marketing analysis can really match the business. Otherwise, simply using visit or bouncerate to measure traffic and user behavior is too sketchy. Now that your problem may arise-since these metrics are customized, there must be no uniform standard report on the Web analytics tools to provide their data and we shouldHow do you get the data? On-demand monitoring of indicators indicators do not worry that any one indicator can be a necessary condition for an indicator that it can be monitored first. If it cannot be monitored, the value of its existence is lost, and that is what is called--it cannot be measured or non-existent. Custom indicators metrics must be able to be monitored. Web analytics tools actually provide a very comprehensive approach, there are several situations: 1. The user's action is to click on the link to open a new page this situation does not actually require us to implement additional monitoring tools, because click on the link to open a new page, that will record the new open page of the new PV. So we count the PV on the newly opened page to know the number of times the user clicks on the link. Of course, the number of clicks and pages Open is not 100% corresponding, but has been very close, completely does not affect our analysis. Download the data in Excel and then do a filter to record the data you think belongs to the indicators page. If you click the same link each time, the open page is not a static URL of the page, but each URL is not the same dynamic page, it does not matter, we can filter settings (such as the GA filter settings) to the URL is not the same dynamic page unified into the same URI, So GA doesn't think it's a lot of pages when it's recorded, but it's recorded as a page. However, this method must have a prerequisite, that is, the dynamic page URL is a certain format, that is, at least some common, completely random URL there is no way. 2. The user's action is to click on the link does not open a new page, but to open a number of specific features these features include: After clicking on the JavaScript or div floating layer, click on the Flash, click on the outside chain and so on a variety of situations. In these cases, we need to configure our GA monitoring code. (1) Click on the object is JavaScript or div floating layer. Use eventtracking functions (official documents, English) or Virtualpage functions (official instructions, English). The principle of this method is to add eventtracking or virtualpage calls to the OnClick event of the click Action itself. For example: style= "Cursor:pointer;" The difference between >yourcontenthereeventtracking and Virtualpage is that the former puts the click action record in the GA event report, which treats the activation of the action as a page record, and shown in the content report. These two methods are the methods that GA learns must master. (2) Click on the object is flash. The idea is similar to the above situation, also need to use EventtraCking or Virtualpage functions, but to write the corresponding method into flash, some complex, need technical department colleagues to help solve. (3) Click on the object is outbound link. The official approach is similar to the method of monitoring JavaScript or Div, which is to do eventtracking or virtualpage of the outbound link (outboundlinks) Click Behavior (onclick event). This requires each outbound link to do the OnClick event reference, and add eventtracking and other methods.