Chinalytics Longmarch Blog

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When I was still in working in market research, I used to tell clients “If you see the US as an Internet country, you have to see China as a mobile country”. While that is somewhat less true today, when we have more than 330 million Internet users, the dominant from of communication is China is still the mobile phone.
The macro story these days then is the convergence of these two worlds, Internet and Mobile. Mobile Internet is growing increasingly popular. CNNIC is already reporting 155 million mobile internet users.

With such a large number of users, companies are turning their focus on providing mobile internet solutions to their audience. With this increased importance comes a focus on ROI, measurement and analytics. We will explore these topics in detail in this month’s Web Analytics Wednesday. One of the key difference between the fixed and mobile Internet in China is the important role carriers play in the mobile ecosystem. China Mobile, this weeks sponsor and its competitors, control a significant part of the data for mobile analytics. We will use this weeks event to explore their role more deeply and provide input into their considerations for mobile analytics.

We will start the day with a quick intro about WAW globally and in Beijing and then Dr. Zhenwu Tao of the China Mobile Research Institute will introduce their work and thought about mobile analytics. This will be followed by an expert panel on mobile analytics with representatives from China Mobile, Mobile Analytics vendors, Mobile advertising agencies, media agencies and advertisers. Please see the whole agenda below.

Agenda:

China Mobile;s sponsorship allows us to host this month’s event free of charge. We will have some snacks and soft drinks available, without the usual buffet dinner.

Please join me and 60 other web analytics enthusiasts to learn about mobile analytics, meet cool people and have
an all around great time. Bring any friends who might be interested to join our community along.

I am looking forward to meeting you on Wednesday September 2nd

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Bounce Baby Bounce (Source: Wikipedia

When I first started to learn the ropes of web analytics, I turned to Avinash Kaushik’s blog (Occam’s Razor) and book (Web Analytic’s: One hour a day) for a great deal of insight and actionable advice. One thing that stuck with me early, was Avinash’s emphasis on Bounce Rate as “The sexiest metric ever“. With all the caveats of generalizing metrics across different websites, bounce rate analysis is still a great place to start, when you plan to optimize your website.

Many companies and analyst have followed Avinash’s lead and are now prioritizing the reporting of Bounce Rate metrics. Talking to many clients in China I noticed a common question on everyone’s lips, tough: “My bounce rate sucks. What can I do?“.

Over time I developed a standard approach to address this question. Take a look at my 5 step guide:

Step 1: Does your bounce rate really suck? (Benchmarking)

Good or not? (Source: http://etc.usf.edu/)

In order to understand if you need to take immediate action to improve your bounce rate (as opposed to focusing on other KPIs), it is critical to benchmark your site’s performance.

Since user behavior and web design varies greatly among cultures, it is critical to find relevant local benchmarks for your site, ideally in your industry. In the US, services like compete.com provide valueable data. In China we have to do without any reliable 3rd party benchmark (what a shame). Even Google Analytic’s Benchmark function is not relevant, since it compares sites by industy, but does not provide country specific numbers.

A rule of thumb based on my experience in China (and please leave your ideas in the comments segment):

1. For micro sites for branding campaigns with mainly banner traffic: 85% to 90%
2. For landing pages of search marketing campaigns 25% to 40%
3. For landing pages of targeted direct marketing campaigns (20% – 30%)

If your numbers are higher, your bounce rate really sucks and you do need to take immediate action.

There are 4 common drivers for bounce rate.

Bounce Rate Causes

Lets take a look at each of them.

Step 2: Landing page segmentation

Bounce Rate is calculated by dividing the number of single page visits  to a page (bounces) by the number of overall entires (visits that started on this page) to that same page. Bounces can only occur on landing pages (the first page a visitor sees on a visit to your site). So when your overall site shows a high bounce rate, you should first look at which landing page contributes most to your overall site bounce rate.

The most effective way to do that, is to calcualate the weighted bounce rate of all your landing pages. Stephane Hamel wrote the defining post about the methodology in 2007 on his Immeria blog. In effect you calculate the impact the bounce rate of each landing page has on the overall site bounce rate, by weighing it according to each pages importance (measured by the number of page views).

Use this formula

Bounce Rate * (Page Views/Total Page Views).

to calculate the Weighted Bounce rate of each landing page.

Take Action: Focus further analysis and optimization efforts on the landing pages with the highest weighted bounce rate. Check if your problem landing page is implementing best practices, usability test it, make changes, then A/B test the new version vs. the old version.

Step 3: Traffic Source Segmentation

Another driver for a high bounce rate on your site is low traffic quality. If your advertising efforts drive visitors to your site that are not interested in what your site has to offer, the best landing page cannot convert them. So before to start getting all excited about remodeling the landing experience, take a look at the traffic sources for your problem landing page. Many web analytics tools (regrettably not Omniture) allow you to easily segment your bounce rate by traffic source and / or type of traffic.

Bounce Rate by traffic source in Google Analytics

When doing this segmentation, look out for high volume traffic sources that drive traffic with a very high bounce rate. Very high is relative and a good benchmark is usually the bounce rate of your direct and search traffic. Visitors from these sources are usually highly targeted. If their bounce rate is high, your landing page likely has a problem. If these traffic sources have a low bounce rate whereas others, especially banner ads, partnership links etc have a very high bounce rate, don’t change your site, change your (paid) traffic sources.

Step 4: Creative Segmentation

When seeing high bounce rates for banners or SEM campaigns, it makes sense to dig one level deeper. Often these campaigns run with multiple creative executions of the banner or multiple copy executions for the text ad. Sometimes that creates a situation where one banner’s creative or call to action or one text ad is not relevant to offer made in the landing page. That is turn leads to a high bounce rate.

To understand if that happened to your campaign, you first need to make sure that your banners and text ads are comprehensively tagged (Google Analytics: UTM _content; Omniture SAINT tags) to differentiate between different creative versions. In the next step, A/B test your various creative version in multiple spots, to measure which one leads to the higher bounce rate.

Action: Run a creative A/B test before launching a campaign to ensure maximum performance.

Step 5: Loading time (Geo Segmentation)

Another very important factor for bounce rate performance is the loading time of your landing page. Especially rich landing experiences (often Flash based) require the download of large amount of data before they are ready for consumption. The longer visitors have to wait before the experience begins, the more likely they are to bounce. So far so easy.

The key challenge for web analysts is that loading time data is not available in any  web analytics tool. In order to get reliable data, you need to buy the services of companies like Gomez, who specialize in web performance measurement (see last weeks Web Analytics Wednesday). This data is especially important in China, where loading times can vary widely across provinces and cities due to a unique network layout (see ChinaNetCloud’s presentation on SlideShare).

A good indicator for loading time challenges is a large variation of bounce rates across provinces in China. In order to get Google Analytics to show you the bounce rate by province in China, go to the map overlay report and click on China. This will go directly to the “by city” breakdown. Then go to the URL bar of your browser and replace the term “city” with the term “region” (** here magic happens **).

Bounce Rate by Province (China)

Action: If you see a large variation (especially between northern and southern provinces) you have a good indicator that your need to improve your hosting infrastructure to address your bounce rate problems.

These are my five steps. What are yours? Did I miss anything important? Let me know in the comments.

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One of the most elelgant features in Google Analytics is Advanced Segments. It allows analysts to quickly and easily segment visitors based on their behavior on your site and answer questions like:

• What share  of overal conversions comes  from visitors that were searching for brand search term vs. non branded terms?
• Which pages do visitors read that do not convert but don’t bounce? (Maybe you missed a goal, or the opportunity to add a call to action to critcal page)
• What is the conversion rate for visitors from groups of untagged referrers (e.g. social networking sites, blogs) vs. tagged traffic sources and search
• What is the best indicator for the difference between “super engaged visits” (>10 PV/Visits) and “normal engaged visits” (>1 to 9 PV/Visits). Is it the traffic source? Is it the landing page? Is it the conversion for a specific goal?

Just create 1 or 2 segments and compare the bahavior difference in almost any report in GA, instantly. Anyone who every tried to answer similar questions in Omniture or WebTrends will feel nothing but gratitude to Google to make segmentation that easy. You can find much more detail in Avinash’s great Google Analytics Releases Advanced Segmentation: Now Be A Ninja! post.

What Avinash didn’t tell us in his post is how to supercharge our advanced segment using user defined variables. I learned about this power of this combination, when trying to segment out the behavior of registered visitors. GA has no build in function that can identify registered visitors, but Google Analytics Help had the solution. User Defined Variabeles!

Adding  a small piece of JavaScript to your login script

<script type=”text/javascript”>pageTracker._setVar(‘registered_user’);</script>

tags this visitor as a member of the “registe

red user” segment by setting a variable in the GA cookie that is handed over with each tracking image request. That sounds complicated but in the end it just means that GA now allows you to create a custom segment based on this User Defined Variable and voala, you can segm

ent each report for registered visitors. Sweet!

But why stop there? Advanced Segments allow an unlimited number of variations. For example

• Compare “Converting Registered Visitors” (who convert to a Goal) vs. “Non Converting Registered Visitors”, to improve conversion
• “Returning Registered Visitors” (more than 1 visit in the time period) to “Single Visit Registered Visitors”, to improve loyalty.
• etc..

To take matters further, Convurgency provided a list of ideas for User Defined Variables in their Google Analytics – User Defined visitor tracking post in Juy 2007. They include ideas like:

1. Visitor Type Segmentation (Business Users, Technical Users, etc) based on form inputs
2. Simple A/B testing by setting a user defined variable for each landing page
3. Referrer Segmentation

This was before the new GA code and before advanced segments became available. Respect! Now implementing all these ideas became even easier.

What are you waiting for? Go segment!

Any ideas for cool segments? Please leave them in the comments.

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Attention: Location Change: This month we are back at Luga’s Villa.
Speaker: Yuan Cheng,程渊, GM of Gomez China

Topic: Introducing “performance” in web “performance” analytics

Please join me and 40 other web analytics enthusiasts to learn about web analytics, meet cool people and have an all around great time. Bring any friends who might be interested to join our community along as well to.

We will have a buffet dinner and soft drinks available for our guests. Be prepared to spend RMB 50 for the evening if you register in advance, and RMB 100 if you visit us without registration. As usual, the knowledge you get in exchange is invaluable.

Address:
Luga’s Villa (details and map)
7 Sanlitun North Street, Sanlitun
Right behind 3.3 Plaza
三六屯北里7号楼
3.3 大厦后边
Phone: 135-2013-7915

Schedule:
19:45 – Door open / Buffet open
20:15 – 20:45 Presentation
20:45 – 21:00 Q&A Session
21:00 – 22:00 Networking

I am looking forward to meeting you on Wednesday August 5th.

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For those of you who couldn’t join yesterday’s Adworld 2009 event, please find the presentations of the Web Analytics session attached. Regular readers of this blog will have seen my 10 Rules for Winning through Analytics presentation already.

Among the other three  decks I want to highlight the “Measurement and optimizations at Qunar” presentation Charlene Ng gave. Qunar is one of the leading travel portals and the leading travel search engine in China. They have presented atthe June WAW but the current deck is more detailed and provides a much better understanding about how they do analytics.

Thanks again to DCCI for hosting this event and of course for all the Speakers & Sidney Song (OMD) – as the moderator

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Adworld Beijing 2009

The Data Center of the Chinese Internet is organizing their big advertising bash tomorrow at the Grand Hyatt Hotel at Chang’An Jie. You can find more details at www.adworld.ord.cn.

I will be giving a quick presentation at the Web Analytics Salon in the afternoon (3PM to 6PM). While I can’t figure out why people in Beijing are so enarmoured with the word “Salon”, it sounds like a fun opportunity to spread the Web Analytics word.

So say hello if you are around.

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• Web Analytics Wednesday Review: Sinotech Group: Web Analytics Getting Social (longmarch.chinalytics.com)

Yesterday I had the opportunity to share some of my thought on web analytics with the geeks on a plane guys.  The most impressive part? They had a specific section called “startup metrics” . This fact alone is prove enough that these guys get it.

If you need more prove, please check out Dave McClure’s Startup metrics for pirates presentation that he reanimated for this event.

I had only 15 minutes to speak, so I made it short and sweet. Check out the presentation below and let me know what you think about it. Of course I liberally borrow from Avinash and Stephane Hamel. Standing on the shoulders of giants.

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One of interesting new features of Google Analytics, we didn’t have time to explore during the March WAW event, is Motion Charts.  Motion Charts are a fascinating visualization idea, displaying up to 5 dimensions of data in a very intuitive format. They were pioneered by Dr Hans Rosling in a famous TEDtalk discussing global health and are now available in Google Analytics to visualize web analytics data.

Motion chart or my blog traffic - click to animate

If you are interested to learn more about Motion Charts in GA, click on the image above to see my blog traffic visualized using motion charts and take a look at this training at the Google Conversion University.

The use of Motion Charts in not limited to Google Analytics however. They are also part of the visualization tools in Google Docs (see an example by the guys from Efficient Frontier) and can be accessed through an API. A good example for using the motion chart API is Eric Peterson’s Twitalyzer tool, that measures users influence on Twitter, and visualizes changes in influence over time. These interfaces open a wealth of interesting usage areas for data analysts, that can be integrated in dashboards and client presentations.

Now here in an idea: Use motion charts to visualize online buzz!

In China, product related discussions happen mainly BBS’s and sometimes on blogs. So these are the platforms we spent most of our time tracking and analyzing for our clients. to visualize user discussions on these two platforms, I propose the following motion chart setup:

The idea, of course, is to use this visualization to identify trending topics that need to acted upon. Those topics would clearly show in the top right corner (many posts, attracting many responses responses) of the chart with large bubble   sizes (many page views) and red color negative aggregate sentiment).

I you have any ideas on visualize social media tracking data? Let us know in the comments!

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• Video of March WAW with Google’s Stephanie Hsu (longmarch.chinalytics.com)

For those of you who didn’t have the  March Web Analytics Wednesday Beijing with Google’s Stephanie Hsu take a look at the video posted above.  Its a full recording of the presentation and Q&A session. The presentation last for 32 minutes and then we have 23 minutes of Q&A. Make sure you don’t miss the insightful questions from our audience. For Song Xing’s video of the event take a look here. We understand that image and sound quality are still sub-optimal and are working on it.

For those of you who have never attended a WAW, this is also a great sneak peak, to see if joining us would add value to you. What is missing from the video of course is the great food and the networking. For that you really have to turn up in person.

During the presentation, in front of a record crowd of 60 attendees,  Stephanie focussed on Custom Reports and Advanced Segments. Both are very powerful tools and Stephanie does a great job demonstrating that power. She is showing actual screenshots from GA, which sometimes makes it diffucult to read what is on the slides. This is compoundend by the fact that I had to use an evluation version of a video conversion software to get the video uploaded.

The video was graciously provided by one of our attendees, but neither of us are experts at filming and editing video. Any recommendations and support in the filming and editing process you can provide is highliy appreachited.

What did you think of this month’s WAW? Like it? Hate it? Want better Chinese translation? Let me know in the comments.

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With a record turnout of 60 attendees for last nights Beijing Web Analytics Wednesday (more details about that, including video!! to follow), we are setting our sights to spreading the WAW goodness to other digital hubs in China. Next stop Shanghai.

We have money:

Local Sponsor: Elliot Ng
Global Sponsor 1: Coremetrics	Global Sponsor 2: Sitespect

We have attendees:

Multiple comment and emails on my and Song Xings blog (Chinese) and in out Inboxes  have asked us about Shanghai events.

What we don’t have is someone who stands up and organizes it.

- Is that you? -

If you are interested, please get in touch with me. I am happy to share my experience and advice. Its not rocket science, it doesn’t take much time nor any money. But its very rewarding, seeing the community grow month by month. Sweet deal, right? So what are you waiting for? Shoot me an email florianpihs[at]gmail[dot]com or leave a comment to this post.

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