The unification of quantitative and qualitative in new web analytics

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No one can deny the fact that we are in the midst of an industry upheaval, and that the current web analytics is quite different from what it used to be. The new web analytics is no longer just clicks statistics, not limited to it statistics, but adds a lot of creative measuring methods, not just to the IT and related departments, but also to the leaders who don't always know it's terminology.

First, let's look at how our Internet environment has changed, web Analytics started, data comes from logs, mostly technical information, not business information. Because of this unique way of development, web analytics tools and visitor intentions come from Clicks Analytics, where a lot of data, metrics, metrics are sorted by the IT department, and often include the following: page views, hits, exit pages, and so on, the data they submit have one thing in common, and that is, They wanted to illustrate something, but it was almost impossible to understand what it said, especially when it was an era of very popular ROI, which led to the leadership's disregard for web analytics because it had neither the ability to solve the company's problems nor the ability to solve the user's problems, and we couldn't take action.

So, we think of the expansion, enhance our ability to listen to visitors to the site, through the log statistics and the placement of JS code, through interviews and exchanges with users, through the investigation-oriented web site updates, and so on, we will adopt another new analysis, it is called the key understanding of insights Analysis,kia).

Perhaps you have the question, the user interviews, the investigation these are not the user experience aspect content, can change a place to be able to put the Web analysis to the new web analysis.

Next, let's give a description of the Web metrics we already have:

Click density analysis Click Density Analysis Use the site overlay feature in the Web Analytics tool to help you see the problem from the user's point of view. It helps you to know how real visitors look at their site and click on which parts. Combined with site traffic sources and search engine keywords, we may be the user's intention to visit the site to do an analysis, users want to find some words, came to the site (not necessarily the first page to enter) after browsing the page, click on the information you want to know (exit) or click on the link in the site jumped out of the website, while the user browsing the process, Whether the user understands information in a predetermined manner or in a prearranged layout, these key metrics will be pooled into a series of measurable behaviors and will be targeted for other (e.g., content adjustment, layout, and marketing).

The main purpose of the visitor is in the new web analytics, instead of relying entirely on the pages we've browsed, we're asking customers to help us understand why they're visiting the web, because using a browsed page is based on the assumption that your site provides what he needs, and in fact there are many things that don't. Use research, interviews, etc. to find out the reasons for the Web site.

Task completion rate for the past page views to measure the completion of the task, we make an improvement, will include more comprehensive qualitative data, let us know whether the user completed their task, they have not found what they want. The way can be done through research, lab usability debugging, Web site testing, and so on, and then find out the results for further action.

So that there will be more measuring methods in the future. However, whatever the tools, ultimately this data will help to understand what has happened. "No matter how tortured the data, he could not explain why it happened".

We have more data on clicks, page views, and more, but why they are coming, and why they end up on these pages. This is a core issue, and that is where our potential advantage lies.

That's why qualitative data is so important. It gives us an idea of why, and 90% of Web site Analytics does a lot of aggregation, but we still choose the reason for 1% of the data.

Common qualitative data include: opinion satisfaction, visitor interaction, brand effect, etc., the form has many kinds, but it is important that the customer interacts with the Web.

In the quest for critical understanding analysis, the first step should be to learn as much as possible about the customer interaction on the Web site, and to understand the impact factors of visitor decisions and actions. Focusing on quantitative analysis can be a waste of time and resources without a good understanding of customer satisfaction and task completion metrics on a Web site in advance.

There are a number of ways to collect customer qualitative data, such as:

Laboratory usability testing;

Website visit;

A/b or multivariate testing;

Research and so on.

Why do some people think of the user experience aspects of the way to introduce them, we think that this approach reinforces the result-oriented factor, because if there is a way to explain what you're doing, you're going to have to use it for ten reasons, because it might affect your source of funding and effectiveness assessment.

The combination of why (intent motivation, etc.) with what (click, Access) will be an important component of the Mission's successful implementation of web analytics.