Website Analysis: E-business key digital Optimization online section (middle)

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"One sentence per issue"

He is Edmond Tantes, my father, my mother, my brother, my friend, me and you. --evey

Objective】

First of all to thank you readers, now one months an article is far less than the original promise of a week article, but still have friends waiting, I live up to your expectations, really sorry. In the past, some articles were dedicated to some friends. Today, this article also wants to dedicate to a friend who is not a stranger, including each issue of today, I do not know whether there will be light in this world, there will be honesty, but because of him, I believe that all will have, because if you really do not fear to come to this world this country, and for this cloudy darkness bring a little light, Then, you step forward behind, it may be all bright. We are with you.

This article on the last: E-commerce key digital optimization (online section, ON)

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Start lifting the underlying drivers

We have in the previous article, the impact of E-commerce key numbers (KBR number) of the driving factors are divided into two categories: the basic driver and the non-basic drivers. We also emphasize the importance of the underlying drivers, and in gets, don't overlook the basics.

Lifting the underlying drivers, seemingly abstract, such as our last example-"The fundamental drive for conversion"-sounds a bit awkward, but the operation is real and concrete. For the last time, we put the underlying drivers that affect the conversion rate down to the following items, which we need to optimize individually. And the results of these project optimization, of course, the conversion rate of the good and bad play a crucial role.

Case study: How to optimize the conversion rate of KBR (3)--Optimization of key transformation process

Now we are starting to work on a basic driving factor that promotes the conversion rate of KBR. This is no mystery, these are web analytics practitioners of the basic skills, but also the Web site analysis of the subject must be used to learn the content. If you want to compile a website analysis of the textbook, these must be the possession of the main part of the textbook.

For example, for the key transformation process, which we are all familiar with, we identify the bad parts of the transformation process, and then examine where the problem occurs in this link and then improve it.

The left figure is such a transformation process, E-commerce site last product sales process is generally such a process. The product page may be the landing page itself, but more often, visitors to the product page will first browse other pages, such as the active page, the homepage or the Product List page, and so on, and then, a certain page on the display of goods caused by the buyer's interest, so they will enter the product Specification page (product page )。

We all know that in a series of links that go into the product page until the final payment is made, any problem in one link can affect the final transformation. For example, some of the problems shown in the following figure are:

Although this is not a typical E-commerce site, but "trouble" is consistent, in the two dotted box of the conversion is a clear problem. We can easily be found by Google Analytics's predefined transformations (goal and step) functions, or omniture Sitecatalyst conversion loss reports (Fallout). Knowing where the problem is, and how much it's going to do, we can use the data to further prove the cause of the problem, or sometimes just to guess, then to improve the existing problems and to test the real solution to these problems (the specific steps we will discuss later, this is not extended).

In short, this is a very sparse common methodology, I think if there is a website analysis of the textbook, this should be the basic methodology.

Sometimes, however, things are not so "perfect". Not all of the transformation has obvious problems, if the loss rate of each link is more uniform, there is no obvious short plate, what will you do? Or, for another extreme, where there is a significant loss of transformation in each link, how do you proceed?

Obviously, optimization is never-ending, no obvious short board does not mean that it is not worthy of optimization, and if each link there is a significant loss of conversion, you will certainly be more busy. At this point, the methodology above may not apply. Things are always step-by-step, you can't optimize all of them at the same time, so now there are three options available, which one would you choose?

A. You will start from the front end of the transformation to solve the problem, and then gradually into the transformation of the back-end link;

B. You will start from the back end of the transformation to solve the problem, and then push forward to solve the transformation front-end problems;

C. You will decide-this thing is not good, broken.

Option C Of course is a joke, if you really care about this site, you will not be so resigned. But sometimes we do have steel frustration, and indeed some sites can only be recycled.

A and B, we tend to follow a practice, but I will choose B.

This may not be right or wrong, but I prefer B.

The reason is that the deeper you go to the back end of the transformation, the more likely it is the "base driver", and the front end of the transformation, more often than not, is the "non-basic driver." I also think, sometimes, the front end is good, there will be a very direct and rapid benefits, but I still stubbornly believe that the back end is more important. There is no right or wrong, just my feeling.

This feeling stems from the difficulty of locating and solving the problem because the problem arises at the front or back end. Take a look at the example below--we optimize the front-end and back-end of the transformation, we optimize the landing page two jump rate, from 40% to 50%, the backend we optimize the payment conversion rate, from 40% to 50%. When other conditions are unchanged, the contribution of the two optimization to the overall transformation is the same. However, often our analytical and technical team resources are limited, how do we choose?

I am inclined to choose the optimal payment conversion rate. There are two reasons. The first reason is that it is clear that the rate of payment conversion is the basic driving factor, and its quality affects the whole situation. The number of landing pages is numerous, and landing pages are constantly changing, not the underlying drivers.

The second reason is that the optimization of the front end is relatively difficult. The more the transformation depends on the front-end, the more the factors that affect its transformation, the more dispersed, the harder it is to solve. For example, the impact of the two jump rate factors related to the design of the page, call to action, user guidance, traffic quality, merchandise attractiveness and so on, these are not quickly easy to solve. Of course, except for the obvious ignorance of small white errors (such as mismatches).

Another fundamental factor affecting the overall conversion rate is the transformation structure. I have mentioned this in several speeches, but my friend who has not heard my speech may not be familiar with it.

As shown in the results of the following three transformations:

Normal transformation is the picture on the left, there is a leak point (as we said above the port ticketing website) is the middle of this, and the transformation of the abnormal structure (the rightmost one), it is in the transformation process, very strange not in accordance with the conversion path of booking, but the cycle, or "scurrying around." Through the "Full Path Report" (This report is not available in Google Analytics, but Omniture sitecatalytics), we can find this kind of strange transformation structure. This structure has a significant impact on conversion efficiency. In the following illustration, the eighth main path (top 8 path) has a loop, and the loop occurs during the shopping transformation process.

Interest reading: A real case of transforming structural errors

Is there a real failure to transform the structure? The answer is yes. A real case is an airline's electronic ticket sales process, a significant flow cycle occurred.

We see that after the user chooses a good flight and clicks Next, more than 40% of the visitors return to the previous step, returning to the selected flight page.

This situation has been extremely serious impact on the overall conversion rate, booking conversion rate is low to less than 3%, but the site's peers on average nearly 10% of the overall conversion rate.

The reason for this phenomenon is quickly found, when the user on the Flight Selection page Select a flight, the corresponding price will not be displayed on this page, but you need to click the "Check Price" button, go to the next page, to see the flight you have just chosen the ticket price. It's a design that obviously won't make people happy, this design, too, clearly creates a cycle of transformation--when people see that airfare is not the price they expect, they have to go back to the previous page to choose a new flight and then click Check Price to see the new prices. In short, such a design is really bad.

Now, the site has changed the design. But the initial problem has become a good negative case today.

Case study: How to optimize the conversion rate of KBR (4)--Navigation optimization

We've solved the key transformation process, and now we're starting to focus on the second underlying driver: navigation.

Navigation optimization is also the subject of the Web site analysis must learn the course, and this piece is relatively mature methodology.

For navigation, we focus on a few things:

First of all, navigation being used too much doesn't mean it's a good thing. Maybe your product is not easy to find, or, people are always easy to find the goods they want, and constantly try to solve the problem through navigation.

Second, navigation is rarely used and is unreasonable, which means that your users do not have access depth.

Then, is the navigation area itself set reasonable? Are there some navigational portals that are not worth putting in the navigation area, while others should be filled in?

For the first to second question, we solve the following:

Evaluation of navigation utilization

Navigation utilization measures the overall use of site navigation, and then calculates whether the user is overly or too small to use navigation. Of course, the general phenomenon we see is the overuse of navigation.

Navigation utilization is represented by the total click density of the navigation in the site, and the formula is:

The denominator why subtract bounce off PV, because we measure this value only for bounce visitor is meaningful. Sometimes, for the sake of simplicity, I sometimes use a formula:

But the meaning of this formula is obviously not very accurate, minus the home PV means to discard the impact of the home page, which is the most important page landing page, but not scientific.

The results of the above two formulas calculate that if the number is larger, the probability of navigation area being used is higher. In general, for the first formula, I don't think it's reasonable to say that the ratio is no more than 40%, and if you exceed that number, it means that the user is wandering around in the navigation and doesn't realize what you want them to do-find the product they like and buy it.

Now, you're going to ask a question--total PV and bounce off PV is easy to get, but how do you get the number of clicks in the navigation area? My approach is simple, and the link URL for all navigation locations is appended with a parameter suffix to distinguish it from being used as a navigation link. For example, a certain entrance to the homepage of the navigation area, linked to the sale of Prada topic page, this portal link was originally http://www.chinawebanalytics.cn/ Prada.html, however, because it is in the navigation position, so I add a special parameter to it "From=nav", this link also becomes Http://www.chinawebanalytics.cn/prada.html?from=nav. In GA, this URL is written as a different page, but does not affect the user's use of the Web page. In this way, the number of clicks on the navigation area is converted to the PV number of the corresponding page that is opened after the navigation entry is clicked, so the value can be obtained more accurately.

Of course, this method has caused another problem, that is, the same page because of the increase in the from= such parameters caused by the duplicate pages, thus affecting the weight of SEO. But the problem is really easy to solve. Add disallow to the robots.txt document:/*?*

Can screen all the links with dynamic parameters, if only shielded with from=, Disallow:/*?from=* can. Thank my colleague Jay Huang for his professional contribution in this field.

For the third question, our common approach is as follows.

The rationality of the navigation area itself

It is reasonable to guide navigation area's rationality. These portals should be commonly used by users, and the classification is clear, logical, and more importantly, users can easily find, and will not be arbitrarily ignored, the role of navigation.

The following figure shows the user clicks for two navigation areas. In two navigation areas, there are a few clickable entrances, especially the help,contact us,agents of the previous navigation. And in the following navigation area, our Trips,your booking has too many clicks, even people almost is to these two entrances. So these navigation has the space to optimize.

Overall, we think that navigation is less likely to be evenly distributed, but if you have an overly dense click-ins or too few clicks, you should consider optimizing. Too dense means that the path on this page or the way the feature is entered is too simple to consider adding some additional entrances. Too little clicks mean that the value of the portal in the navigation area is worth weighing up again.

Another case is that there is a problem with the navigation of the history page of catwalk, there is a large area of almost nobody, this area has only one destiny, is disappears.

The rationality of Navigation path

Navigation path rationality is also an important evaluation of navigation. Method directly, using the Web site Analysis tool path function can be. Good navigation features a clear logical path, and bad navigation may have many paths that do not conform to expectations, and more loops. Don't repeat it.

Case: How to optimize the conversion rate of KBR (5)--Site Search

If we continue to explore the footprints of the optimized conversion rate, we will inevitably encounter site search in the path of the underlying drivers. Site search and navigation impact on the user experience is essentially similar, for some e-commerce sites, this impact is even decisive.

Extended reading: The inconsistency of user experience in e-commerce website

E-commerce Web site is different in type, resulting in electronic commerce must have different effects on user experience. The same E-commerce site, a certain type of users have a good user experience, for the other part is not necessarily.

Further, this is the nature of human shopping.

There are two kinds of things we do in shopping, one is buying with a certain purpose, the other is the stress purchase after a casual stroll. In contrast, men tend to be the first, while women are the majority.

E-commerce websites tend to be both, but relatively biased. Because of site positioning, category and commodity characteristics, the people facing different, e-commerce sites can still be divided into a preference for the service of a clear purpose of the purchase, and to favor the service to stimulate the purchase of interest.

The former, such as the improvement before the Jingdong Mall, or Taobao (you will find in Taobao casually stroll really difficult, your purchase will not improve). The latter example walks the net. These two types of e-commerce sites, the user's purpose is different, the main points of user experience optimization is not the same. In the first case, it is clear that the search function must be very strong; Of course, it's not that it's not important to navigate the first situation or that the second kind of search doesn't matter, but the emphasis is really different.

Site Search optimization also has a fixed set of routines, in Avinash's second book, "Web Analytics 2.0" in detail. I seem to have forgotten some of his original text, so I said what I used in practice.

I was in a long time ago that crowded sharing to do how to optimize the content of the website through the site search, at that time, my view is very clear, no user behavior is more valuable than the user directly search the keyword revealed information. Today, this view is still not outdated, especially if your resources are limited and you cannot directly talk to users.

The focus on the search is shown in my left image.

Search utilization is similar to navigation click Density, and the formula is simple:

。 Search for a site with high utilization, a preference for a destination, or a site with low utilization, might be an incentive to buy, or--the search is really bad.

In addition to our own calculations for search utilization, several other key points can be obtained directly from the Web Analytics tool. For example, for high search bounce and refinement, Google Analytics provides a good report, as follows:

and the 0 Search results page is a very important report (this report does not seem to Google Analytics), in Omniture's Sitecatalyst tool, there are special reports to provide:

In the report above, the search term "handicom" is the one that returns the most results, and if you are Sony, you will know what to do. If we save these search handicom users and satisfy their intention to understand Handycam, then our conversion rate will certainly benefit from Philip.

High search results return pages are those that carry the desired search results, and whether these pages satisfy (or at least partially satisfy) The searcher's expectations also affect the conversion rate.

For example, in the above report, for Handycam this search term, users will click on the first page of the search results. This means that the home page is best to meet the needs of these people, otherwise they may think that the site does not allow them to know more about the product, let alone buy the product.

The above examples just want to show how to create the possibility of improvement and optimization by studying the performance of the underlying drivers after identifying the underlying drivers. I believe these actions are meaningful. However, the above cases are analyzed, not the optimization of the proposal itself, more than the resulting optimization results. In the KBR optimization path above, there are other important things you need to do to ensure that the actions you take are effective. These, I'll cover in the last article in this series, including how to find real optimization methods through testing and how to better meet the user's transformation expectations.

Well, first write so much, please put forward suggestions and questions, look forward to your message!

Original: http://www.chinawebanalytics.cn/kpi_optimization_part2/