Web Application E-Client Behavior

Question

I would like to know what are the main tools on the market for analyzing / implementing E-client behavior in a web application.

I just know Google Analytics, which tracks activity on the client side, but there may be many alternatives that use client-side and server-side scripting.

I already posted this question on webmasters.stackexchange.com the behavior of the electronic client in the web application , but it was closed and can not understand why!

Answer 1

There are many tools for analyzing user behavior on a website. E-commerce or otherwise.

Google Analytics has options such as:

• Ecommerce
• Custom Ecommerce Variables
• Goals and Funnels
• Target Streams

etc .. which are useful for understanding things like departure points, conversion rates, typical customer paths and other customer metrics.

Other analytics packages useful for e-commerce / website behavior:

• Clicktale
• Crazy egg
• Getclicky

and much more. Some of them have a live / spy function that allows you to see what users are doing in real time.

And the best way is to actually observe the recording of the behavior of your users with keystrokes and mouse clicks / movements.

User Recording Tools:

• Mousestats
• Ghostrec
• Inspectlet
• Mouseflow

Most of the above also contain aggregated heat and overlay maps to give you an idea of ​​what users click most or what catches their eyes, etc.

Incremental improvement of your website:

A / B testing or multivariate testing is all a rage. When testing A / B, you should know the local maximum , as well as avoid common mistakes people make with testing. The expiration of Google content (formerly known as the Google Site Optimizer) is now part of Google Analytics, and you can use it for testing.

Links / more reading to analyze and customize the behavior of e-commerce users:

• Chasing Users
• Driving Online Sales

Answer 2

Web analytics solution

First of all, you need to choose the overall Web Analytics Solution offer. Since you are an e-commerce company, you want to choose one that has good support for tracking e-commerce data.

Google Analytics is the obvious choice here, not only because it's free, but also because it's better documented and easier to implement.

depending on your size, it might make sense to implement a more efficient e-commerce solution at the enterprise level. You can take a look at Adobe Omniture and IBM CoreMetrics . They are much more expensive not only because of licenses, but also in terms of implementation. It may take several months to implement one of these other tools, and the cost of implementation may be almost the same as the cost of a license. However, if you need more enterprise-level analysis and integration with other BI solutions, it might be worth a look at them.

Please note that Google Analytics has a Premium Edition . This is a fairly new alternative and provides some additional features and early access to beta features.

Product recommendation

Depending on your e-commerce platform, you may have some kind of product recommendation or sale. You can usually improve these systems based on analytics data. There are only a few options on the market, and most companies involved in this tend to develop their own recommendation mechanism.

If you are just starting out with this, it might be worth a look at LiftSuggest . I have not tried, but they seem light enough to implement and use Google Analytics data to improve cross-selling.

Heatmap

This is simple enough to implement and can provide some nice heights. I find them usually more distracting, but from time to time you can make good use of them. Most common: CrazyEgg and ClickTale .

Behavioral Targeting

This is a method of setting up your site based on previous visitor knowledge to increase your conversion rate. The tools here do not help, since you need to set up your site, and no tool can predict how to do this. One common approach is to create buckets depending on the factors you can do. For example: users with Internet Explorer may be less technical and, therefore, may be more interested in non-technical products. Linux users, on the other hand, are probably in the technology field. Thus, you can place users in buckets depending on which country they came from, which browser they use or if they are logged in, you can use the information that they entered in your profile, or based on previous purchases. One tool to help you do this is called BTBuckets .

A / B and multivariate testing

Google Analytics has an A / B testing tool integrated with the tool. Another good tool that provides A / B and Multivariate testing: Unbounce , Optimizely, and Webtrends Optimize .

Custom solution

These days everyone is developing customized solutions. If you still have the money and time to spend on web analytics after you have surpassed other options, you can look at creating your own. Collect data the way you want and analyze granular data. Here, solutions range from assemblies from the server to the client side, but for analysis they are usually run with Hadoop or with the OLAP Business Intelligence tool, such as Microstrategy .

Answer 3

What you are looking for is called Customer Relationship Management or CRM . They vary greatly, so without a deep understanding of your exact needs it is impossible to recommend specific ones. Any good CRM will allow you to analyze your site visitors in various ways. For example, you can see if customers bought X, they often returned and bought Y after a month.

The hard part is integration, because these systems need information about orders and other user actions. If you are using an off-the-shelf e-commerce package, CRM options are often available.

For a “lighter” system, you can use Google Analytics or the like, since it allows you to send information about tracking, conversion and sales in the browser. This is great for analyzing the overall success of the site and tracking user actions on different pages, but less powerful for reports and analysis specific to sales.