Sunday Night Thinking on Mobile Analytics…
Mobile analytics for Internet-enabled wireless devices is a fairly hot topic for companies seeking to acquire customers, extend their brand, or expose content in “innovative” ways. Obviously, the iPhone and Blackberry are pushing development in this area forward, but there really aren’t a lot of players in this space.
Nedstat, CoreMetrics, and Omniture offer capabilities mixed into their current offerings. Nedstat even carves out some mobile specific reporting. You can gain some insight into mobile activity from companies that enable log file processing, like Unica and WebTrends, but be prepared to configure a bunch of filters to isolate the data.
Lesser known companies pushing mobile offerings include: Amethon, Mobilytics, Bango, TigTags, Xiti, and AdMob. Some of these mobile players are even offering capabilities where they cross-sell analytics as an integrated part of their ad networks, content delivery and transactional processing systems, marketing and barcoding services, and even as infrastructure or network appliances.
On the audience measurement side, we’ve seen comScore acquire M:Metrics, which was no surprise to me.
On the multivariate testing side, we see my friends at SiteSpect offering mobile MVT testing capabilities.
And I’ll bet we see Google get into this space within the next 6 months… I’d even wager an announcement at eMetrics DC…
From what I can gather, when we’re talking about “mobile analytics” we’re talking about “mobile browser” activity across a variety of handsets, not everything that happens on the device.
Measurement issues in this area include:
- Data Collection. As many of you know, not all mobile browsers will execute javascript. They cached the imagesThus, vendors offer us choices. Folks like Mobilytics and Bango use an image-based data collection method, while Amethon offers a packet sniffer (they call it wireline detection), and we even have Omniture and Coremetrics talking about “no tag” implementations - what my good friend Phil Kemelor mentioned on his CMS Watch blog (”To compensate, you need to stuff the image tag with query strings that will collect the data you require for reporting.”) Then we have Unica and WebTrends with log files. Interestingly, packet sniffing has some advantages here because some devices pass unique id’s (such as the phone number) in the HTTP header or other unique id’s.
- Unique visitor identification due to lack of cookie support and IP addresses changing. IP addresses change, I’m told, as they switch from tower to tower. In addition many mobile devices will take the IP address of the gateway, making all the devices look the same “person.” I’ve certainly seen evidence of the host changing pretty quickly during a mobile session. Compounding the difficulty in assessing “uniqueness” is that not all mobile devices support cookies. In web analytics, cookies are used to define uniqueness. The fallback method when you can’t use a cookie is IP address/user agent. If you can’t set cookies and the IP address and user agents are the same, how do you identify uniqueness? However, when you can detect a unique value in the header, you can easily detect uniqueness.
- Handset capability detection. Does the device support WAP pushing, streaming video, ringtones, downloading video clips, and so on?
- Phone and Manufacturer identification. Database from WURFL and DeviceAtlas can be used to identify phone and manufacturer device attributes. Larger vendors are further behind on integrating this data into their current offerings, whereas the smaller niche players are making use of it.
- Screen resolution detection. The Mobile Marketing Association’s (MMA) standards for the four “standard” screen sizes may carry enough weight to push this disdained piece of metrics trivia available from javascript based tagging in web analytics into a brighter spotlight.
- Traffic source detection. Capabilities for traffic sources seem rudimentary. I don’t just want to know about search and direct entry. But I want detection of sources from my marketing and advertising campaigns, rss feeds, and email newsletters, if mobile visitors are coming in from those channels. Interestingly, Bango solves the campaign tracking issue by pushing you to a Bango-specific URL.
- Geographic identification. Where are the visitors viewing your site coming from? And what does the mobile audience environment “look like” in each country. From this information you can extrapolate country-specifics for site optimization. But not all devices enable geographic detection because the gateway’s IP address is used or the IP address from the network is used, not a GPS signal.
- No standards. There are few, if any, commonly supported mobile standards and no web data standards, so the problem is no standards for the devices and no standards for the tools. There are no standards. Did I mention that there are no standards.
So I was thinking, what would I want to see in a mobile analytics solution? Allow me to riff here.
- Dashboards for KPI and specific-metric reporting. Views, visits, visitors, referrers, popular pages, traffic sources, resolutions, geography, time-based reporting and custom defined KPI’s….
- Support for multiple data collection methods. Logs, no-js image tags , and packet sniffers. Let me pick what I need for whatever application fits my goals.
- Support for mobile-specific constructs not present in historic web analytics data. Manufacturers, operators, handsets, and device capabilities.
- Advertising-based reports. CTR, CPM, eCPM, that stuff…
- Tracking for mobile downloads, installed applications, SMS, and MMS. Seems like a no-brainer.
- API’s. Closed systems are dead ends for integrated marketing, so give me an API or enable pre-built integrations with other systems, like CRM.
- Segmentation. By country, by device, by network, by manufacturer, and so on. It’s necessary.
- Repeat or return visitor identification. Simple measures of recency and frequency, core to media buying and planning and to site optimization, should be a data point available in mobile analytics.
- Conversion and goal metrics. Do visitors on mobile devices convert better, worse, the same? Do they reach site goals? Without tying performance data and outcomes to mobile visitor activity, I’m left wondering…
- Value scoring for engagement or proxy scoring for revenue and ROI analysis. I want to be able to score attributes or actions to approximate an engagement score or to identify value or indicate revenue.
- Non-human traffic and web-browser based detection and reporting. Mobile pages are full of links. The ads are links. Mobile vendors must support detecting, filtering, and reporting, non human and web-based agents from pure mobile agents - otherwise the mobile data gets muddled and skewed.
- Data Export. Must be able to export reports to Excel or Word, and email them.
So there’s a quick blogviation on Mobile. Am I right, wrong, what did I miss? Let me know…
Judah added the following ...
Hi Florian,
My apologies that I have been a bit slow to respond. It’s been a busy week.
JS tags do work that way. Parameters are generated dynamically via javascript. On mobile devices, you do what Phil said and I quoted (he did a good job describing it) - “stuff the image tag with query string (parameters)” by having the server generate the image tag and query string for you.
Make sense? Thanks for your comment, and for reading my blog! ![]()
Mukesh Sharma added the following ...
Thanks for sharing the knowledge.
I was completely blank before reading this article. Now i have come know about mobile analytics.
You said that image-based data collection method and packet sniffer.
Could you give me example of that so that i can understand mobile analytics better.
Thanks
Mukesh
jip added the following ...
thanks for this summary, Judah
tagging mobile sites is a nice challenge, since queries have to match the analytics tool, in opposition to standard websites, where tags are supposed to fit it.
BTW, you forgot XiTi as a mobile analytics tool, seems to be quite powerful to me ![]()
Judah added the following ...
Mukesh: That’s great to hear. I’m glad you found the blog helpful! Packet sniffers intercept and log traffic passing over a network. They capture and decode packets and decipher them. In Mobile Analytics, the packet sniffer sits on your network, and captures the requests from the phone/responses from the web server. In image-based data collection for mobile analytics, the server creates the image tag based on the requirements for the analytics technology, instead of browser/javascript method on the “normal” web. Hope that makes sense! Thanks for reading my blog and commenting!
jip: Indeed. You are correct! And you may have to use alt text on the image. In addition, the image may get cached, so you need to find a way to randomize it. I’ve added Xiti to the list above.
Thanks for the comment and for reading my blog! ![]()
Ray Anderson added the following ...
We have just released an upgrade to Bango Analytics (V3), to make the information collected easier to see / use. Have a look at bango.com/analytics
Sniffing is an interesting technique, but it can be difficult to deploy if you can’t “sit” in the request stream in front of the webserver - like if you are hosted somewhere for example.
Judah added the following ...
Thanks for the pointer Ray! I’m intrigued and impressed by what Bango is doing for mobile analytics, particularly your focus on API’s. Agreed about sniffing. I’d argue that it’s not only difficult if you are hosted by a third party, but it can also be challenging to convince a large company to deploy internally in a data center.

Florian Pihs added the following ...
Thanks Judah, for the quick summary. One stupid question I meant to ask on Phil’s post already… How do you “stuff the image tag with query strings that will collect the data you require” when you cannot dynamically assemble the query string.
My understanding was that “stuffing the image tag with query strings” was they way all JS based tags worked anyway.