Getting Started With Web & Mobile Analytics

Greg Laugero, President, Industrial Wisdom | 2/27/2012 | 14 comments

Greg Laugero
In an earlier post, I discussed the problem of analytics as an afterthought for customer-facing systems. At the end of that post, I quickly outlined an approach that integrates analytics right into the application development process. Here I'll expand on that approach.

The reason we launch customer-facing systems is because we want to alter people's behavior in some way. We want them to buy more, serve themselves, and find us online, among many other things.

I use these desired behaviors to anchor the analytics requirements gathering process. Here are the steps:

  1. List the behaviors you want to measure
  2. Describe the event(s) that indicate users have behaved in a certain way
  3. Describe the metric that will tell you about the event(s)
  4. Define the tags that will be implemented to capture the metrics

Behaviors: Effective Web and mobile analytics start with identifying the behaviors you want to encourage (and discourage) and putting in place mechanisms to measure their occurrence. This you can do very early in the application development process -- as early as requirements. As you're gathering requirements (however you do that), begin asking the question, "What user behavior makes this a successful system?" Make that list.

Events: During application design, precisely define the event(s) that indicate a particular behavior has occurred. For each behavior ask the question, "What event will occur in this system that tells me this behavior happened?" Look at your flows and screen mockups. You're looking for things like button clicks (e.g., on checkout, order, or "share with a friend" buttons).

Metrics/KPIs: Translate events into meaningful data about those events. For each event ask, "Is there something that I'd like to know about this event whenever it happens?" For instance, you might want to know if the person executing this event visited your site from a specific campaign. If the event is clicking a "submit order" button, you might want to know if a special offer was accepted during the visit. This will allow you to measure the effectiveness of the offer against order conversions that didn't include the offer.

Tags: Develop meaningful data tags that describe the metrics you wish to capture, and place them in a useful hierarchy. Putting thought into the tags and hierarchy is important because any poorly thought-out job in the development stage can significantly increase the effort required to add metrics at a later date. Properly designed tags are placed in a logical system that is scalable to meet future needs.

As an example, here is a table that I've used to help structure the analytics requirements process. In this case, I was working with an e-commerce system that allowed users to create "favorite orders" so that they could easily order them again. They also could "reorder" -- they could select an old order and place it again. Both were time-saving measures. We subsequently learned through metrics that reorder (going back to an order automatically stored by the system as part of the customer history) was much more popular than favorite order (returning to an order explicitly tagged by the customer as one of their favorites).

Desired Behavior Event Metric/KPI
Place a favorite order. User submits an order that was based on a favorite.
  • Number and percentage of orders submitted as favorites
  • Percentage of orders for each user submitted as favorites
  • Percentage of favorite orders changed prior to submitting order
  • Conversion rate of favorite-based shopping carts to submitted orders
Place an order from history. User submits an order that was based on a previous order.
  • Number and percentage of orders submitted based on an earlier order
  • Percentage of orders for each user submitted based on an earlier order
  • Percentage of history orders changed prior to submitting order
  • Conversion rate of history-based shopping carts to submitted orders

There is a lot more complexity than can be fleshed out in a brief article, but for those just getting started with analytics, work on defining them as part of requirements and design. It doesn't have to wait until the very end -- or worse, after launch, in a subsequent release.

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Greg Laugero   Getting Started With Web & Mobile Analytics   3/1/2012 6:41:57 PM
Re: What will be the interface of the analytics?
white.space: just came across this blog post about "Big Data" and "Big Anaytics.
User Ranking: Blogger
Greg Laugero   Getting Started With Web & Mobile Analytics   3/1/2012 6:25:19 PM
Re: What will be the interface of the analytics?
white.space: Great question. As the amount of data available for analysis grows, the UI to work with it is going to have to change radically. The way we look at Google Analytics or SiteCatalyst today will look primitive in only a few years from now. Your question made me think about the issues surrounding "Big Data." It seems to me that the work going on here is going to "trickle down" in the next few years so that the ability to draw correlations among seemingly disparate sets of data will be easier. NUIs and RBIs are only a couple of ways of thinking about this. Do you have any thoughts on this?
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white.space   Getting Started With Web & Mobile Analytics   2/29/2012 11:58:49 PM
What will be the interface of the analytics?
Really interesting read.

Do you think we wil see a lot of NUI in the analytics in the coming days? What do you think will be the customer-facing interface?
User Ranking: Blogger
Skr2011   Getting Started With Web & Mobile Analytics   2/29/2012 10:57:30 PM
Pedro Gonzales   Getting Started With Web & Mobile Analytics   2/29/2012 10:07:05 PM
web analytics
great article, I think understading user behavior is a great way to discern pattern and discern better services to users, what kind of programs would you recommend to start understand more web and mobile analytics, my favorite example is google analytics
Hammad Masood   Getting Started With Web & Mobile Analytics   2/28/2012 3:54:10 PM
Helpful
Crisp and clear ! This piece was quite helpful to give me an intro on web analytics. This has made me curoius  to know more.
Taimoor Zubair   Getting Started With Web & Mobile Analytics   2/28/2012 12:21:16 PM
Re: Using this...
Great article, indeed. Though I am just a newbie in the field of Analytics, I was able to grasp the concept instantly.
Taimoor Zubair   Getting Started With Web & Mobile Analytics   2/28/2012 12:19:32 PM
RE: Getting Started With Web & Mobile Analytics
I agree with Kicheko here. If we start with the use cases and then derive the events and KPIs for them, it would avoid the rework in noting down the behaviors. But then again you're right that not all use cases would be important enough to become part of analytics.
Damian Romano   Getting Started With Web & Mobile Analytics   2/28/2012 8:27:29 AM
Using this...
I've run a few websites over the years and have sponsored several projects whereby I've provided input on web analytics. This article, though succinct, is a great way to introduce people to the groundwork of analytics. I'll be pointing a few this way...
Greg Laugero   Getting Started With Web & Mobile Analytics   2/27/2012 5:29:26 PM
RE: Getting Started With Web & Mobile Analytics
kicheko: I'm glad you brought up use cases. It's a logical place to start. I try to identify the appropriate KPIs as part of the important use cases. This ensures that everyone knows what the important use cases and KPIs are before the application is developed.
User Ranking: Blogger
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