Earlier this month, the company I worked for launched its first two European sites dedicated to mobile – the Toyota German mobile site and the new Lexus CT 200h pan-European site.
The Toyota German mobile site was specifically designed for high-end mobile devices such as iPhone and provides information on “hot” topics, Toyota models (pictures, specifications, colours, prices…), a simple configurator and a retailer locator based on Google Maps services.
The Lexus European mobile site supports the launch of new Lexus C-premium hybrid car, providing pictures and information on the car features plus the possibility to register to the newsletter.
Enough with the promotion… From my perspective, as a Web Analytics freak, this meant my first steps in mobile analytics! Hurray! (me jumping in the air, full of joice and happiness ;-))
Mobile vs. Web analytics
This is an exciting experience as it is opportunity to expand my expertise and learn new things. It also means new challenges to tackle as measuring mobile sites does not work the same way as measuring Websites. The differences come from the specific aspects of the mobile platforms and devices.
The biggest challenges with mobile analytics are
- Identifying unique visitors because mobile devices do not support cookie and the changing of IP addresses
- And finally, retrieving geographic information (if important) can be difficult as well – again not all devices enable geographic detection.
Well there are other methods to collect data. Phew! We are saved. So what are these alternatives? Basically there a four main solution types:
- Server log-based: process the raw data coming from you web server (My take is to forget about this one except if you are really a geek and that you have plenty of time to loose! :-))
- Packet sniffing: a hardware device or software is added between your server and the Web. It listens and analyses requests sent and received by the server. No need of having tags here but additional hardware or software is required (meaning you will need help from your IT best friends!)
- Image tag-based: A call to an image is added in the content with appropriate parameters & value in the querystring. Data are sent to a collector server by the client device each time a page is rendered. Parameters can be dynamically set by the server back-end when the content is generated. Easy but it has some limitations (see previously) and can not be used for event tracking.
- Server-side script: A script is added on server side that sends data directly to collector server when requests are processed. It doesn’t rely on the device to get the data. Data are extracted from the received requests and set dynamically based on the request/content. This solution is getting more and more used by traditional Web Analytics vendors.
AdMob(1), Bango, Percent Mobile (2), Amethon to name few of them. But mobile analytics has become almost as hot as social media monitoring and it only took a few months to see most Web Analytics vendors offering technical solutions for mobile site tracking whether this is Google Analytics, WebTrends, NedStat, Omniture, AT Internet… Just check with you nearest local vendor for more info.
here if you need a good methodology to define your online KPI's). For example, do you need to go as deep as identifying model of a specific device brand or knowing the platform is enough for you? Keep in mind that it is not the quantity of data you can get that matters, it is what you do with it!
My personal opinion is that mobile specific vendors have lost a big part of the edge they had compared to traditional Web Analytics vendors. If possible, you should try first using your existing Web Analytics solution. Why? Here are some points to consider:
- Tagging & data consistency: using same platform for both your Web and mobile sites means you can tag & measure content in the same way. If you need to compare web vs. mobile performances, at least you will be comparing apples with apples.
- Web & Mobile data integration: By having both Web and mobile data on same platform – data can be aggregated and segmented at will. For example, what content is more efficient on mobile? It will give you a global view of your online ecosystem on one platform while being able to isolate each main segment.
- Leverage existing knowledge & expertise: why learning a new tool when you can leverage years of expertise you already have? It can be fun of course to learn new tools but do you have the time? Can you or your business stakeholders afford the risk?
- Reusability: If your mobile site is an extension of your website (or very similar), you may reuse existing tagging guidelines, mechanisms but also reports and indicators. No need to reinvent the wheel! In my case, for our mobile site, 80% of reports are existing ones (from main site) and 20% are mobile specific ones
- Costs: If you go for another solution there may be additional costs involved either for the software/hardware or for the technical expertise and implementation.
Use a Kaizen approach
If Mobile analytics is new to you (as it is for me), I also recommend a Kaizen approach – start small & simple, use first the tools and expertise that you have. It is a learning process. It is better to take the easy way and improve & develop your mobile analytics capabilities step by step rather than a big leap with the risk to make it more complex and more risky than necessary.
If you find out it is not enough or too limited – think how you can enhance it easily. For example, you can use a image tag-based implementation using your existing Web Analytics tool and complement it with a free mobile specific solution to get missing information such as used devices & handsets, screen resolution…
When you reach the limits of your framework then it will be time to consider moving to something else – plenty of choice there – by that time you should have gained enough experience and expertise to make the right choice and justify any additional investments in time, resources and money. Well, that’s what I think. Future will tell if I am right.
So what do you think? Does it make sense? What are your thoughts on the different methods & solutions? Any other key aspects you would consider before making a choice? Any experience with mobile analytics you are willing to share? I would be curious to know.
- "Lost in the Mobile Maze", White paper on mobile analytics by Bango
- "The Truth about Mobile Analytics", white paper by Eric T. Peterson (June 2009)
- "Mobile Analytics", post by Anil Batra (October 2008)
- "The Challenge of Mobile Analytics" (Part I and Part II) - CMS Watch (May 2008)
(2) Former TigTags analytics solution has been "absorbed" by Percent Mobile.