Practical Analytics by DigiKnow

Analytics for iPhone Apps

Usually when I talk about analytics, we are focused on websites or at least apps that live within a browser.  Today, I want to look at analytics within mobile apps, specifically for iPhone apps.  Although we’ve build iPhone apps before, we didn’t care much about analyzing usage previously, but today we launched a new app, the Latin Recipe Shaker, and because type of app it is and the scope of the advertising around it, we wanted to make sure everything we did was measurable.

The first challenge we faced was the decision on which analytics package to use.  We ended up focusing on two main solutions: Flurry and Google Analytics.  In looking at both tools from an analysts perspective, I didn’t see much difference in the reporting provided.  The way the user’s location is tracked seems to be a bit more robust in Flurry, but since the app isn’t mobile aware, that was not a factor for us.

The second question was about implementation.  After having my developers look at both systems, they said the implementation was nearly identical, so there wasn’t any preference on their side.  Both systems use an asynchronous processing of data so that every click and swipe isn’t pushed up in real time.  Flurry uploads the data from the previous visit when the app starts.  Google Analytics lets you set a delay, which defaults to 10 seconds, and then it uploads the data on that interval.  Although it uses more pushes, I prefer the Google Analytics route.

Since all things were equal, and since DigiKnow is a Google Analytics Authorized Consultant, we decided to go with Goggle Analytics.

The implementation basically allows for two types of tracking: page views and events.  From what I know, you can’t do custom variables yet.  We setup page views for each of the main screens and did events for the settings changes, adding/removing on the favorites page and the keyword recipe search. 

The only major hiccup that we’ve seen so far is that the Visits data doesn’t seem to be quite right.  Somehow a single real-life visit shows up as multiple visits in Google Analytics.  This may be related to the asynchronous processing.  The other data point that isn’t quite right is geography.  Since we didn’t want to use the iPhone GPS, our app just uses IP for location, and every iPhone that is on 3G or Edge looks like it is in Dallas (the home of AT&T). 

Overall, the process of implementing analytics was fairly simple and the data coming in is very valuable.

Questions from the field

DigiKnow continues to offer our analytics seminars that we started late last year.  Since we just had our latest one yesterday, I figured I’d take a few minutes today and blog about the questions that came from our attendees.

Question 1: We moved from AWStats to Google Analytics and our data doesn’t line up to compare year-over year.  Can you explain this?

Matching data between various analytics systems is always a tricky thing.  Moving from a log based system (AWStats) to a tagging based system (Google Analytics) is even more confusing.  Log based systems track every interaction on the website, including image views, PDF downloads, etc.  Tagging based systems only track page views, unless specific code is in place to track downloads.  If one system is considering PDFs as page views and the other is ignoring them, you will have a discrepancy in your data. 

A major area of discrepancy for this attendee was in their traffic sources.  Although I don’t remember the exact numbers, AWStats was reporting something like 30% search, 30% direct and 40% referrals whereas Google Analytics was reporting 60% search, 20% direct and 20% referrals and 2% other (I realized these don’t add up).  This is significantly different and as it turned out was due to two main factors: First, AWStats was reporting alternative domain names (ex: site is xyz123.com but abc987.com also gets you to the site) as referring sites, dramatically boosting the amount of traffic from referrals (I think it was 15K vs. 5K between systems).  Secondly, Google Analytics was tracking banner and paid search campaigns in the “Other” category, whereas AWStats was putting that either within direct traffic, referral or search.

 

Question 2: On our Ecommerce site, my development team said we can’t use Google Analytics because of the way the pages are structured.  Is that true?

This one is a little less obvious since we weren’t looking at the attendee's website, but given what she was describing, it sounded like they were able to get the data into Google Analytics, but it wasn’t displaying anything useful.  I’m speculating that, because this was Ecommerce, they were including a transaction ID value in the URL string, so that each visitor’s pages were unique.  Visitor #1’s visit to www.xyz123.com/product?id=4564&transid=1 and Visitor #2’s visit to the same page looked like www.xyz123.com/product?id=4564&transid=2.  They are the same page, but to Google Analytics, looked completely different.  The solution I suggested was to apply a Google Analytics filter to the profile that would strip off the Transaction ID (“transid” in my example) and then the two pages would look the same.

Question 3: To install a tagging based analytics packages, to I have to edit every page on the website?

This one is a little easier and the answer is yes.  But what marketers not familiar with HTML and server side scripting don’t know, is how includes work and how easy that can make update every page on the website.  An include is a sub-set of the full page HTML that is stored in a separate file for reference by a page.  A single include is often used as a footer for the entire website, so a single update can change the entire site, making adding a tracking script just a few minutes of work. 

 

If you have any questions that you’d like to see answered on this blog, please email analytics@digiknow.com and we’d be glad to help.  If you are in the Cleveland area and want to attend one of our seminars, please feel free to email about that too.

DigiKnow is now a Google Analytics Authorized Consultant

 

The main purpose of this blog is to provide training, advice, tips and examples to help you, our readers, with the every day analytics challenges.  Today, I must take a little diversion from that to announce that DigiKnow has been added to Google’s Authorized Consultant list. 

We are very happy to be added to this group of top-tier consultants and are excited to see how we can use this new status to further help our customers and provide input on the Google Analytics system. 

As you’ve probably gathered from examples in our blog posts, we are strong advocates of Google Analytics, both from it’s cost perspective (it’s free!) and what it can do.

DigiKnow’s analytics team guides clients through the code implementation, configuration, reporting and analysis within Google Analytics.  With our new status, we will continue to offer all of these services, and with access to a new community of experts, our own knowledge will continue to grow.

If you have any analytics needs, please contact us at analytics@digiknow.com or call us at 216-325-1900.

 

 

Technorati Tags: Google Analytics,GAAC,authorized,consultant,DigiKnow,expert

Google keeps the new features coming

Google delivered an early Christmas present on Monday announcing some new features that will be coming out soon.  You can read the full text at Google’s Analytics blog, but I wanted to both make you aware and give you my take on the new features.

Annotations

As I said in the comments on Google’s post “Hallelujah”.  Because “why” is such an important part of analytics, being able to record the cause of a spike (or dip) is very important.  Until now, I’ve had to manage that in Excel or in a screenshot with annotations in PowerPoint or Word.  Having those in separate sources meant that as time goes on, my records got messy and it was hard to overlay my info on the GA data.  Annotations fixes that.  You can now go into GA and on the timeline, make a note of what happened that day.  Because we have multiple agencies working together and multiple analysts even within DigiKnow, this is a great feature for sharing knowledge.

Although none of my logins have access to this new feature yet to try it first hand, from the video, I really like how they are handling sharing.  Notes can be public to the profile or private to the user.  For every other GA customization (reports, segments, intelligence) you have to share the information via link to other users, but with this, it’s just there for everyone.  I hope that they roll out this system to those other customizations AND leave in the cross-profile sharing too.

 

Custom Variables in Segments & Custom Reports

While I think annotations are for the masses, custom variables (launched in October) are definitely for the more advanced GA users.  I haven’t really talked about this yet (or played with it), but until recently, you could only have one custom variable per domain.  So for a client that I wanted to track two things, I had to jam it into a single field.  With unlimited custom variables, you can track anything without having to be cautions of “wasting” the variable.  Some great things to track are registered vs. non-registered users, previous purchasers, visitor profiles established through questions/surveys, etc.  This is very powerful stuff.  Having the ability to segment by and report on these data is an obvious next step.

Code Setup Wizard

Google keeps adding features that makes configuration of complicated things simpler, putting me out of a job.  Good.  Although setting up multiple domains, sub-domains, etc. is definitely an art, I’m all for a wizard that just makes it happen.  There are parts of analytics that should and do require deep thought, but configuration shouldn’t be one of them.  Just like the GA URL Builder (for tracking campaigns), having a form or system to make setup easier saves time that can be better spend on more meaningful tasks.

 

There is also an announcement coming this week about API updates.  Probably to give access to these new data points.  I’ll update this post with a link to it when the announcement is made, but I don’t think any of you will probably be lining up at the Googleplex to hear that announcement.

UPDATE: Here’s the link to the Google Analytics API updates.

 

So what’s still missing?  We’ll plenty could be added, but the one simple thing that I’m dying for them to add is an import/export or sharing feature for Filters.  Given that we are now able to share custom reports, custom insights and advanced segments, it seems like only a matter of time. 

Free Analytics for Enterprise?

Earlier this month, Forrester released a study (that Google funded) reviewing the merits of free web analytics products and discussing how and were they are used in enterprise.  This study, Appraising Your Investment in Enterprise Web Analytics, is available free from Google and is a very interesting read.

With this study as a backdrop, I figured I’d throw in my two cents about the good and bad of various analytics services.  Let me start by saying that I definitely subscribe to Avinash Kaushik’s 10/90 Rule.  In this “rule” Avinash proposes that you should spend 10% of your analytics dollars on technology (generally software or services) and 90% on people.  I will add to that rule by saying that some times that 10% of technology also comes from your development team writing a unique query or randomization script to help test or optimize some piece of the site.

So you can get Google Analytics ( and Yahoo! Web Analytics) for free or you can invest thousands of dollars in services from Ominture, Webtrends, Coremetrics and others.  What should you do… 

Of course it depends on your situation.  If you are a one-man marketing department at a small business, free is probably fine.  If you are part of an enterprise analytics team working on a ecommerce site, paid solutions are probably the way to go.  Then there is the rest of us in the middle. 

My recommendation is to start with free.  Get your feet wet, get an understanding of what is possible to measure.  Then move on to reading a book, attending a seminar or brining in a consultant to guide you a bit.  For some, the process will end there.  For others, you may find that the limitation of free solutions are big enough frustrations or time wasters that it is worth the investment into a for-pay commercial solution.

For DigiKnow, we live in the 39% overlap in the chart above.  For many of our clients, we use Google Analytics.  For a few we use for-pay solution from Omniture or ClickTracks (now Lyris HQ Web Analytics Software [catchy huh]) solely.  For others, we use a commercial solution as a primary and free solutions to handle small projects or specific tasks.  In the end, most of our clients want to pay for the analysis and insights, and don’t care about the technology used to get us there.

 

Technorati Tags: google Analytics,omniture,webtrends,free,avinash kaushik,enterprise