Web Analytics in China

Online Metrics in the world of User Generated Content

Catching up with my analytics reading, I saw this interesting post from Dennis Mortensen explaining his Online Business Media Quadrant Model. His basic assumption is that in a world where user generated content becomes more important, measuring only what happens in the controlled environment of your site (with tools like Google Analytics and Omniture) gives us only half the picture (or one quarter, if you don't measure UGC on your site). He recommends a more holistic approach by looking at

• Controlled On site Content
• Controlled Off site Content (User Generated)
  
• Uncontrolled On site Content (Syndicated content - PR)
  
• Uncontrolled Off site Content (User Generated)

What a nice summary of some of the work we have been doing recently ;) A couple of thoughts on this (not yet well structured)

1. In China, but I assume in other countries as well, marketers still have a strong urge to control as much of the conversation as possible. This old reflex limits the reach of their message. Web 2.0 is a reality in China and marketers need to move away from a shouting mentality towards communication mentality, that emphases listening to the "voice of the customer".
2. Separating online marketing and PR becomes increasingly difficult, especially when looking at user generated content (or IWOM to use another term). Marketers need to find ways to tear down the organizational barriers that prevent better integration especially on the analytics side. Otherwise their understanding will be limited to one or two quarters of Dennis' quadrant.
3. Measuring user generated content (quantity, quality, key messages) is a new challenge for most advertisers in China. With the amount of conversation going on in the millions of blogs & BBS's in China, manual tracking and counting is not scalable. While Sam Flemming's CIC owns the conversation an IWOM tracking in China, looking at other alternatives might pay off, especially regarding integration with current analytics efforts.
    
4. Measuring off-site content provides a new challenge to advertisers as well. While some of the large advertisers in China just get comfortable with Web Analytics on their own site, some of our client already move away from viewing their site and their banner campaigns as the main medium for communication. They increasingly communicate with 3rd party vendors (e.g. video, sharing sites, business communities) to engage their audiences more effectively. While that makes a lot of sense from a marketing perspective, analytics team need to find solution for tracking the effectiveness of these cooperation. A low trust environment like China adds its own challenges (tip: never trust your vendors numbers). The best solution we have found thus far is forcing vendors to integrate our tracking codes on the pages / experiences they create for our clients. While this opens a whole different can of worms (explaining the differences between "our" numbers and "their" numbers anyone?) it seems like the best available solution.
5. Making your own content "mobile" will significantly increase your reach. Many brands in China have experimented with viral videos, hosted both on their mini-sites and video sharing sites and our numbers show a huge boost reach. Who says video's are the only "mobile" / "viral" content brands can create? Think about making your downloads available on third party sites, your mini-games and your widgets and you will be rewarded with an explosion in reach. At least as long as you can measure it. Users seem to be more willing to engage in advertisers content when they are in the "mood" to watch, play or download.

P.S.: You can find a version of this post on longmarch.chinalytics.com. Please leave your comments there since I plan to move this blog over there.

CTR and CPC Benchmarks for China (part II)

After getting all worked up about JPMorgan's metrics, my  colleague Sydney restored me to sanity today by pointing out that the table I was referring to, most probably was reporting only to Search advertising data. Can anyone confirm that the numbers make sense for Search? T.R.? Is there similar benchmarks for display advertising in the report? Too bad I was late downloading the whole thing as Kaiser Kuo recommended. But then again I was relaxing my mind and stomach from a stressful Germany holiday ;)

CTR and CPC Benchmarks for China

Thanks Kaiser for pointing out this article at the China Web 2.0 Review with a summary of the China section of the new JPMorgan “Nothing but Net” report from Morgan’s Internet analyst Imran Khan and his team.
Apart from the interesting market size predictions (past data curtesy od CNNIC) the most interesting info for me was the average CTR and CPC numbers supplied for the China market (curiously called Price per click). I have been looking for industry benchmarks for ages, and this could fill this gap. (Insert exclamations of happiness, for frenzy forward to friends here) But looking at these numbers, they seem to make little sense. Click-trough-rates I have seen globally (incl. China) are usually less than 1% (not >20%) and CPC in China varies between USD 0.02 to USD 1. RMB 0.40 seems out of this world. I checked with CNNIC and they claim innocence. Can anybody with a hotline to JPMorgan clarify?

Google Conversion University

Google is doing a great job in making Analytics accessible for everyone with Google Analytics. Now the key challenge  is how to use this new wealth of data effectively to drive change and increase the ROI. An interesting resource I recently came across is the "Google Conversion University" playlist at Youtube. Take a look at all these videos, but if you short on time, get the quick fix and watch Avinash talking about "Bounce Rate" my most favorite metric of them all. (note to self: find a topic to disagree with Avinash). For Chinese users, make sure you fire up your proxy before enjoying the wealth of learning available there.
And if you really want to do me a favor, share your experience with bounce rates for campaign landing pages with me in the comments or by mail florian-dot-pihs-at-ap-dot-mccann-dot-com.

More Engagment - the counter argument

It seems Avinash stirred up a lot of controversy with his post on engagement (see Sunday's post). In a series of thoughtful comment I want to highlight Gary Angels response, which is leading the pack in terms of clarity among analytics experts that defend "Engagement" as a metric. I especially like what Gary responds to Avinash's last point. He says:

• Engagement isn’t a proxy for measuring an outcome on a site at all. It’s more often a means of aggregating a set of outcomes into a single visitor score or segment. Since a set of outcomes can’t reasonably be described by just appending all of the events into one long name, the analyst is always going to have to pick a name that reasonably represents the overall concept. In many situations, and for many sites, “Engagement” does a pretty good job of carrying that baggage

My conclusion is that measuring Engagement can be an effective tool in the web analytics toolbox. But like every tool, it can used for good and bad purposes (much like nuclear energy, I guess). In order to use Engagement effectively we need to be aware of certain preconditions and caveats.

• Engagement is not a standard metrics that is the same for every company, or even every campaign of one company, which often makes it difficult to compare and improve on it over time.
• Engagement should never be an excuse not to define, track and analyze specific outcomes of a page. Without a clearly defined objective and target action a landing page has no value.
• What Engagement can do however, is summarize a set of outcomes (e.g. Video played, PDF downloaded, link clicked) and the compare this set of outcomes across different visitor segments (e.g. search vs. banner ads, media A vs. Media B, Landing Page A vs. Landing Page B). This can lead to valuable conclusions and actions.

Now the main challenge for non e-commerce sites is to prove beyond doubt, that a higher engagement leads to a better, faster or less expensive achievement of the objective. That again is very unique across companies and will often involve additional surveys.

Engagement & Strategic Web Analytics

Due to the Chinese National Day holiday I am little late on this one, but Avinash Kaushik just earned another feather in his guru cap with his post on engagement as a web analytics metric. His main points are:

1. Engagement is not a metric that anyone understands and even when used it rarely drives the action / improvement on the website.

2. Because it is not really a metric, it is an excuse. An excuse for an unwillingness to sit down and identify why a site exists. An excuse for a unwillingness to identify real metrics that measure if your web presence is productive.

3. It is nearly impossible to define engagement in a standard way that can be applied across the board. Definitions that exist are either too broad (to cover every nuance) or too narrow (hence very unique)

4. At the heart of it engagement tries to measure something deeply qualitative.
   Yet most efforts to measure it in our world tend to be hard core quantitative

Its great to see someone spelling it out so clearly, so please go ahead and read the whole post.

My own experience trying to implement Avinash suggestions for our own clients suggests a deeper meaning between the lines of this post. An answer to the question "Why do Web Analytics practitioners still use Engagement as a metric, when most of us should share Avinash's skepticism?"
Its because in most companies Web Analytics is in a silo, where it is not involved in strategic planning and decision making. Following Avinash's methodology we end up asking strategic questions over an over again, but in many companies web analysts are not expected and / or not allowed to ask questions like:

• What is the objective of your site?
• What is the objective of this campaign?
• Can that objective be measured by analyzing clickstream data?
• What action do you want the user to take on the landing page?

These questions are owned by other silos, so we end up defining metrics that are under our control. We look at the data from our web analytics tools and hope to gain additional insights from "Engagement" however we define it. This may not solve the problem, but it is within our circle of influence.

So Avinash, what I hear your really saying is this: "Web Analysts of the world unite, and increase your circle of influence. Make Web Analytics a strategic function". Oh, and one more thing: Don’t call your approach Web Analytics 2.0. Call it by its real name. Don’t hide behind a pretty moniker. Call it Strategic Web Analytics ;)

Unique Visitors & the importance of context

One of the key metrics in every analytics report is "Unique (weekly, monthly, etc) Visitors". In its easiest form, it will tell you how many people visited your page or site in a given period. Even given the problems of accurately measuring the advertised number (done with persistent cookies), unique visitors is the best headline number to evaluate the success of a campaign and add significant value compared to looking at page views or visits. The key reason is that it can answer the key marketing question: "How many people (prospective clients) have seen my message (e.g. website).
But just looking at the plain visitor number does not allow us provide actionable suggestions. And this is what web analytics is all about. Even adding general ratio like Visits / Unique Vistor or Page Views / Unique Visitor do not provide much additional room for analysis.
There are three simple questions that help us on our path to actionable insights.

1. Is this number good or bad?
2. Why is the numbers good or bad?
3. What can we do to improve this metric and is it worth the effort?

Today I will focus on point one.

"Is this number good or bad?".

The answer this question, we need a little help from a friend. This friend is context. In order to understand if we are doing well or not, we need to compare our number to other numbers. Let me use the example of school boy that comes home from school with a "B" in Chinese. (Luckily he is preparing from the future) His parents will naturally look at the context to interpret his performance. They would ask themselves question like:

• What were his previous grades? (A "B" is great if he got all "C's" before, but a little disappointing when we was all "A's"
• How well were his classmates doing? (If it was a difficult test, and all other classmates got "C's", this B is great!)

We need to do same in Web analytics, when looking at numbers like "Unique visitors".

1. How did the number of unique visitors develop over the last month? Is it growing or declining? How fast?
2. How are your competitors doing in terms of Unique Visitors? Who is getting more visitors, who less?
3. What is your share of the overall internet population? (Here I need to leave my school boy behind) Is  Is it growing or declining?

Most practitioner of web analytics will easily do point 1. Heck, most analytics tools will do it for us. Point 2 and 3 are more problematic, especially in China.

Competitive information
... is hard to come by. In the US and Europe Comscore and Hitwise will provide such competitive intelligence. In China we are less blessed. Startup companies still rely on their Alexa ranking (if favorable), but Alexa numbers have been discredited for some time. The only other provider I am aware of that can provide competitive web information is IResearch. The company started to run a panel of about 50K internet users, and provides its client access to their surfing behavior (adjusted to represent the Chinese Internet audience). Due to my past occupation, I am not a big fan of IResearch, but after initial tests their numbers seem fairly reliable.
Based in this competitive information your are now able to tell you client (internal or external). "We have 1000 unique visitors this month. This makes us number 3 in the industry. The best competitor is X." for more details on competitive analysis, that a look at Avinash's post here.

Share of internet population (Reach)
Another way of providing context to your Unique Visitor number is comparing it to the overall internet population. This is especially critical in a market developing as quickly as China. CNNIC provides a semi-annual report on the size of the Chinese Internet population. If your number of unique visitors is growing by 10% annually, while the internet population grows by 30%, you certainly have a trigger for a more in depth analysis of the cause (Why in my previous list). If you need reach data for your site on a monthly basis, you can refer to IResearch as well, which will have a monthly reach for your site.

The importance of context is true for any web metric, and I will continue to highlight it future post. If you have any thoughts or comments, as well as any recommendation for better competitive information in China. Please share with us in the comments section.

Why "Bounce rate" should be a key metric in any online campaign

As one of the more regular topics on this blog will be highlighting some key metrics that every web advertising campaign and web site owner needs to pay attention to, and how they relate to online campaigns in China in particular. These will go in no particular order, but I plan to cover the ones I see as most critical for China first.
The first candidate is the "Bounce Rate". The Web Analytics Association defines Bounce Rate as Single page view visits / Entry Pages . A more common definition used by most analytics tools is: Single Page Visits / Entry Pages. It measures how many of the visits that used a page as the entry page to your site, were single page visits. Or in marketers terms: Is your landing page interesting enough for users to take action (clicking links on the page).
Now why is this so important for online campaigns? In traditional media advertising, we analyze TV ratings, media circulation and other metrics to understand how many people have been exposed to our AD. Then we do surveys to understand if the AD broke though the media noise and how it affected the audience's attitude.  Most of the time, this is exactly what we advertisers in China are doing for online advertising campaigns as well. We measure the impressions recorded on the page the AD was displayed, then measure the clicks and click through rates on the banner (or search keyword in too few cases) to measure the "break through" of the AD, and then we survey the audience about brand preference etc. What is often ("most of the time" in China) completely ignored, is what happens after the users clicked on the banner! Since this is what makes web advertising so unique and in my opinion uniquely valuable, this is a complete and utter waste. Once a visitor clicked on our ad, we know that he is interested in our message. Even better, after the click he comes to an environment that we have 100% control of. This is the place where we can really impact the visitors/users/potential clients perception of our brand, increase his brand awareness, increase his brand preference of even let them buy our product / service directly.
The bounce rate tells you how well you have made use of that opportunity. How well you have used the web to do more that just show users pretty ads through a new channel. The answer is, that in China, at the moment, sadly, we are doing very badly. My discussion with clients, friend and industry experts suggest that bounce rates for online campaigns in China hover between 90 and 99% percent, with good campaigns coming closer to 90 but only rarely below. Comparisons show that the average bounce rate is closer to 60% in the US (in lieu of other data points). It means that, of the 6-7 billion RMB spend on online advertising in China in 2007, more than 5.5 billion fail to use the online channel effectively. In other words: If we come close to the US numbers, we can improve our online advertising effectiveness but at least 300%.
This is certainly a number to think about. Even though there are several factor that might help to explain parts of this outrageous number,

• Many netizens in China might not be able to differentiate well between content they are interested in or all relevant content is already available in. 
• the landing page might contain all the info the visitor is interested in, and he/she does not need to click further
• Sometimes visit where the visitor only clicked on a download link counted as bounces

it is critical for every advertiser to understand what their bounce rate is, how it relates to their campaign goals and to the bounce rate of competitor's campaigns. So here is a question to my readers (the one or two who might read this), what is your bounce rate, and what do you go about reducing it?