Four steps: How to make the Web Analytics report more valuable

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Where do I start writing web Analytics reports? What indicators should be selected and used in the report? How to make the results of the analysis more valuable? These are the problems that we often encounter when we write our web Analytics reports. This article shares a process for creating a Web Analytics report that makes the analysis report more valuable in four steps.

First, clear analysis of the purpose of mining valuable analysis needs

The commercial purpose of the website produces the analysis demand, and the value of the demand directly affects the value of the analysis result. So before we start to write a website analysis report, we need to think carefully and fully explore the value of the analysis requirements. So what analysis needs are valuable analysis needs? Let's look at three of the most common customer analysis requirements.

The first type of customer has a clear analysis of demand, the second category of customers have a very vague demand, the third category of customers can not clearly express their analysis needs. For the second and third categories of customers before the analysis, must be clear their analysis purposes and requirements. And the relationship between these analytical requirements and the final business objectives. Without a clear purpose, there is no analysis of the need to produce, nor the meaning of analysis. In this case, you will not know how to do the analysis, not to mention the value of the analysis results. However, not all of the customer's requirements will be valuable. Sometimes the information the client conveys to us is not what he really wants in his heart. At this time we need to analyze the meaning behind the customer needs, to obtain truly valuable needs. Analyzing the value of the demand directly determines the value of the analysis result. And most of the valuable needs will be related to how to bring benefits to customers.

Ii. determination of analytical methods and reporting logic

After clarifying the value of the customer's needs, we go to the second step, choosing the analysis methods that need to be used and the logic in the report. The first is to select the analysis method. The choice of analysis method is mostly determined by the customer's needs and problems. For primary customers, most of the three questions will be raised in a progressive way: how are they doing? and how to modify and improve? These three problems can be applied to almost any scenario, such as advertising analysis, site structure analysis, page quality analysis, transformation analysis, and so on. For these three problems, we usually can use contrast analysis, subdivision analysis and quality analysis of three methods to answer.

For the logic of the report, we give a general analysis logic, user-impact-action-conversion-gain. This logic can be combined with most advertising and web business models. We map different phases of the analysis logic to users, ads, websites, and so on. and choose the correct metrics for each part of the goal and problem.

Third, use accurate metrics to measure

The first two departments we have identified the purpose of analysis, analysis methods and the logic of the report. The following begins by selecting the correct metrics for the different issues in the analysis. The selection of indicators will directly affect the results of the analysis. If the indicators are not chosen properly, then the analysis may also be wrong. There is only one rule for selecting indicators, which is to accurately measure the problems to be analyzed. This is easy to say, but many times we often use mistakes, and even sometimes to report the fullness, to avoid mistakes, many ineffective indicators are listed. result in data accumulation.

Here is an example: which metric do we use to accurately measure the quality of a page? Bounce rate, exit rate, browsing volume, conversion rate of these indicators can be, but we need to different features of the page and use the scene to choose the most accurate indicator, rather than all the relevant indicators are placed above. This is true even for the same page.

How do you measure page quality?

Bounce Rate: page as landingpage.

Exit Rate: When the page appears in the task process.

Browsing Volume: When a page is hosted as a content page.

Conversion rate: Interactive page with no other subordinate pages.

Iv. using charts and business languages to present analysis results

The last step, and the most important step, is to present all the work before, so that customers who do not understand the site analysis and data can quickly understand the information in the report. Here are two parts, the first is to select the appropriate chart to show the results of the analysis. A picture wins thousand words. The second is to translate the professional metrics of web analytics into business languages that customers can understand. And according to the business scene for the customer interpretation. We have to admit that no customer is interested in indicators, most customers don't want to know the difference between visitor and visit, they will not be interested in your numbers, they need to pass data and analysis of the business problem interpretation. So we can't simply list the numbers and indicators in the analysis report. You also need to tell the customer the specific business issues that are described in such scenarios.

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