Author: Xu Ge
Hello everyone, I am Xu Ge, product manager of Aliyunyun Native ARMS. Today, I will bring you the third lesson of the observable series — Business & Digital Experience Management Scenario Interpretation. This paper is mainly divided into three parts, the first part is the necessity of digital experience management, from the impact of digital experience management on business and the value of digital experience management to the enterprise to introduce its necessity; The second part introduces the product capabilities of ARMS in digital experience management. The third part, combined with customer cases to share the best practice.
The need for digital experience management
Why do we need digital experience management? Foreign research reports show that 70% of users feedback that the speed of webpage opening directly affects users’ willingness to shop online. Amazon also found that for every 100-millisecond increase in website loading speed, overall sales decreased by 1%. Overall, the user experience will directly affect business performance. So what value does digital experience bring to the enterprise? We see the value of digital experiences in three ways:
The first one is quantification. I believe you may have heard the saying “if you can’t quantify it, you can’t optimize it.” Therefore, quantification of subjective user experience into specific indicators and visualization analysis ability are provided to help enterprises understand the overall user terminal experience level and existing problems. At the same time, in addition to quantifying the user experience index of our own products, we can also obtain the benchmark index of the industry, or even the experience index of competitive products. With quantitative data, we can use digital experience tools to gain insight into and leverage data. For example, identify usability and page performance issues, define boundaries on the impact of the issue, and analyze whether the issue is a geographic issue, a carrier issue, or a device issue. Finally, armed with these insights, THE ARMS USER experience interactive tool will also provide optimization suggestions for the experience problems, helping us to fix the problems in a targeted way. Faster problem detection, reduced service impact, and reduced overall fault recovery time.
As digital experience is so important to enterprises, ARMS provides a comprehensive tool for digital experience scenarios. There are generally two ways for digital experience, one is synthetic observation, and we are familiar with the concept called dial measurement. The other is called true flow observation. For synthetic ARMS, cloud dial testing products are provided. For real traffic, ARMS provides front-end performance analysis and APP performance analysis.
To put it simply, cloud dial-up is to conduct active simulated access to target websites through pre-built detection points in different regions, operators, devices and types to obtain availability and performance-related indicators. At the same time, thanks to the black box mode of cloud dial-up, the experience indicators of competing products can also be collected and analyzed. In terms of real traffic observation, ARMS is divided into front-end performance analysis for Web and performance analysis for APP. For web front-end observation, ARMS supports the management of websites, H5 and small programs. First, it provides operational analysis capabilities, including PV/UV data and page performance-related analysis. In addition, it can provide end-to-end link association analysis capabilities for API requests combined with ARMS application performance analysis. On the mobile end, APP performance analysis can achieve crash analysis, performance analysis, remote log pull for iOS and Android applications, as well as multi-dimensional analysis capabilities for different devices, different carriers, and different networks.
So what’s the difference between the two, and where do they fit in? Here’s a quick summary:
First of all, from a traffic point of view, cloud dial is not real traffic, it is simulated access traffic. Front-end performance analysis and APP performance analysis are based on real traffic for performance analysis. Therefore, it can be seen from here that cloud dial-up does not need traffic and can also achieve performance management for websites or API interfaces. Front-end performance analysis and APP performance analysis require real traffic to achieve digital experience management.
Secondly, in terms of form, cloud dial testing is an active means, it will take the initiative to visit the website or APP provider, faster and earlier to find experience or other related problems, to solve and repair these problems before users. Front-end performance analysis and APP performance analysis are more passive means. Only after user access traffic can relevant indicators be known, so as to achieve correspondence analysis.
Finally, from the perspective of data volume, the cloud dial access frequency and access times can be set well, controllable in advance, and the data volume is relatively small. Front-end performance analysis and APP performance analysis collect real traffic data, so interactive events on the website and APP will generate corresponding indicators and logs, which will generate a large amount of data.
In summary, cloud dial-up is more suitable for obtaining benchmark experience indicators. For example, if there is no user traffic in a certain region, the website can be dial-up through cloud dial-up to learn the overall experience indicators of the region. At the same time, it can also test the industry competitor’s website and obtain the industry benchmark experience index. However, front-end performance analysis and APP performance analysis are based on real traffic and obtain the real experience indicators of the website or APP. For example, after a new release, verify that the overall experience works as expected. In addition, cloud dial-up is suitable for diagnosing and focusing on short-term experience problems, while front-end performance analysis and APP performance analysis are suitable for long-term tracking of APP or website performance and identifying potential problems. In other words, what the cloud can help us answer are known questions, such as whether the site is available or not? However, there is no way to answer the potential problem, which means that this scenario is suitable for real traffic performance analysis when you don’t know what the problem is.
Therefore, in the digital experience management scenario, the combination of the two can provide all-round digital experience management for enterprises.
ARMS digital experience management product capability introduction
Next, we explain its core capabilities respectively for cloud dial testing, front-end performance analysis and APP performance analysis. Generally speaking, cloud dial-up is to simulate real users as much as possible by deploying observation points around the world, and to access the target website or APP from all parts of the world to master its availability and performance.
Cloud dial test has the following advantages:
- Distributed in the world’s massive detection points, both IDC room detection points, but also users LasMile detection points.
- Compared with application performance analysis, it does not require professional skills, nor does it require embedding. It is a non-invasive method. When the website is tested, it does not need r&d cooperation and can be configured in three minutes.
- As an active tool, testing at the 7×24 hour and minute levels detects problems before users do.
- Cloud dial-up has a variety of detection models, including availability analysis, web page performance analysis, DNS hijacking analysis, CDN quality performance analysis.
Let’s start with usability performance analysis. For digital experience management, availability performance analysis is the first experience management problem that needs to be solved. Only after availability, can we talk about the following access performance and error and exception correlation analysis. For cloud dial-up, observation points of different regions and operators can be selected to carry out active access to the website, and the successful visit is marked as an effective visit. By dividing the effective visit by the total number of observations, the specific availability of the website can be obtained. For usability, we also provide long-term trend analysis; It also provides the ability to drill down on a single trip and learn the details of that trip to help us locate the key points that are causing specific feasibility problems.
The second scenario is performance measurement. Cloud dialling performance observation can be divided into three aspects, the first is for web page performance, including the first screen time, 100K time, as well as the network layer DNS time, TCP time, download time, SSL handshake time and blocking time; The second is network performance, which is mainly reflected in the delay and DNS query time. Finally, for file transfer, cloud dial-up can grasp the average file transfer speed and the first package time and other indicators, and observe the performance of the scene requiring file transfer.
The third scenario is hijacking analysis. Cloud dial-out analyzes common hijacking types, including DNS hijacking, traffic hijacking and element hijacking. In addition, cloud dial detection can check DNS and CDN quality, including real-time analysis of DNS resolution policies and the performance of each host node, and adjust DNS resolution policies based on the analysis results.
Cloud dial-up can also evaluate the service quality of CDN providers during CDN selection and assist in selection decisions. After the CDN service is purchased, the CDN can also be continuously detected through cloud dial-up to obtain the detection data resolved by THE CDN to tune the CDN scheduling policy.
Finally, due to the active black box capabilities of cloud dial-up, competitive product analysis can also be implemented. In view of the industry competitors in the website to initiate an active test, learn relevant indicators of experience, guide their own website optimization, make us in a relatively favorable position in the competition.
Next, we will talk about ARMS ‘product capabilities in real digital experience management, mainly including front-end performance analysis and APP performance analysis. Front-end performance analysis and performance analysis are based on the APP to access the data of the real traffic, geared to the needs of different terminal digital experience management tool, can from the page performance, error and abnormal analysis, network request and other multi-angle analysis of digital experience, at the same time provide area, equipment, network operators and other multidimensional analysis ability.
ARMS ‘real digital experience management product has the following characteristics:
A, compatible with multiple platforms, support web, H5, small program. Common platforms like wechat, Alipay, Dingding and small programs are supported. It also supports iOS and Android devices on the APP.
Secondly, the combination of ARMS application performance analysis and link tracing can realize the end-to-end analysis. The API request of a page can be associated with the call chain of the back end to realize the end-to-end performance analysis and problem location.
Simple access, no need to bury, also support a variety of access methods.
In addition to analytical capabilities, it also provides online diagnostic capabilities to assist in locating the root cause of problems.
Front end performance analysis before the first ability is very different end-to-end performance analysis, we can in the very different front-end performance analysis through multiple dimensions, such as version, operating system, device, browser, regional and network and various dimensions of API performance is analyzed, and application performance analysis can also, Implement end-to-end call analysis to help users locate specific applications and codes that cause slow API requests.
The second capability is front-end performance analysis and multidimensional analysis. You can analyze performance indicators by geography and terminal, including browser, device, operating system, resolution, and network. In some scenarios, the device, region, or network problems can be identified to provide data support for service decisions.
Finally, it is the JS error analysis ability of front-end performance analysis. ARMS counts the number of JS errors, error rate and the impact of this error on business from different dimensions to assist us in making business decisions.
Here is also a brief introduction of digital experience management products for APP.
Firstly, correlation analysis of APP stability and PERFORMANCE analysis of ARMS APP are divided into three types for stability problems. The first is crash analysis, including Crash and Aboard; The second is exception analysis, we will actively find your exceptions, including memory leaks, the main thread IO such exceptions; In addition, in terms of stability, we also support multi-dimensional analysis, including which version, which device, which operator, which region, and which network, and calculate the proportion of different dimensions to help us determine the root cause and impact surface. At the same time, detailed drill-down support for stability problems helped us locate the specific cause.
Secondly, API performance analysis capability can be combined with ARMS application performance analysis to achieve end-to-end network performance analysis. In addition to the statistics of the network performance of the APP end, it can also be linked to the application call link of the back end with one click, so as to quickly locate the specific microservice or component, or even the line of code, that causes the slow call.
Finally, the APP performance analysis remote log pull capability. For such logs, ARMS APP performance analysis is relatively light, and there is no need for burying or collecting, or accessing full-text search system. As long as the SDK of APP is integrated, ARMS can pull crash logs as needed, restore the site of errors, and quickly locate complex problems. You can also specify the device, version, and system to create a pull task and actively pull the logs of the user APP device. At the same time, it also pulls out the machine memory and CPU environment when logs are running to assist in problem location. In addition to active pull, intelligent pull can also be implemented for crash scenarios. After detecting such crash events, tasks are automatically created, devices are intelligently selected, and logs of faulty devices are obtained in advance and retained on site to save troubleshooting time.
Best practices for digital experience management
The above is an introduction of ARMS ‘product capabilities in digital experience management. Finally, we share some best practices based on several customer cases.
The first case is Jika Robot. Jika Robot is a domestic intelligent robot manufacturing service provider, working closely with more than 300 automated airlines around the world to serve global customers. In order to better serve global customers, Jieka robot takes online marketing as one of the important marketing means, and has carried out a large number of overseas advertising on Google. In order to ensure the effect of online marketing, the card robot should first ensure that the landing page of the official website can be accessed normally. If a page or website has a usability or performance issue, it can affect conversion rates and potentially cause Google to stop serving them. With observable team communication, valentine card robot decided to adopt very different cloud measuring sustainability in overseas website, select the main customer areas, including North America, Europe, South America and southeast Asia and other regions of the netizen testing point, based on the browser’s task, on the website for performance testing, finally found two questions:
First, CDN scheduling is not accurate in some areas, mainly concentrated in the Eastern United States and Southeast Asia. CDN scheduling does not realize the optimal scheduling scheme. Second, there are some large image files on the official website, which affect the loading speed of the website. After diagnosis, and based on the two positioning, valentine card after the robot and the CDN suppliers, comprehensive optimization of the east and southeast Asia CDN mobilize logic, but also promote the research and development team on page image compression, the overall problem after repair online, through the cloud dial test detected website open speed increased by 50%, ensuring the full online marketing effect.
The second case is the front-end performance analysis case of ARMS. Walnut Programming as a leader in the domestic children’s programming education industry, the overall business is developing very fast. With the development of business, the system architecture is becoming more and more complex, and the back end is using micro-service distributed architecture. How to improve the observability of distributed system is a big problem that we are facing at that time.
For the online education industry, user experience is very important. Because user experience directly determines brand image and conversion rate. However, due to the micro-service architecture, in a teaching scenario, a user’s simple teaching may involve calls between different applications, and even some third-party service interfaces. So any link failure or line bottleneck, may affect the user experience. After investigating the open source method and enterprise-level scheme, walnut programming finally decided to adopt the front-end performance analysis of ARMS, and at the same time combined with the application performance analysis to realize the digital experience management of teaching terminals. The first thing that impressed them at that time was the fast access ability of front-end performance analysis. Without burying points, detection data can be reported by introducing a script into the customer’s front-end code. The second is the end-to-end performance insight of application performance analysis to quickly locate the root cause of the problem. The third is the ability of multi-dimensional analysis. The front-end performance analysis of ARMS can conduct aggregated analysis of performance from multiple dimensions such as geographic location, operating system, resolution and network operator, and specifically locate the causes of performance bottlenecks. Finally, the alarm capability of ARMS enables the operation and maintenance team to sense the experience problems in the first time. Truly realize problem detection in 5 minutes, isolation in 10 minutes and solution in 30 minutes. For Walnut programming, ARMS ‘observable system helps them reduce the operation and maintenance workload by more than 30% and shorten the average time of fault location by 60%, greatly improving user experience and laying a solid foundation for sustainable business development.
The above are user case sharing for different products of digital experience management.
Click here to see more details on the ARMS website!