As the one or two people that used to read the blog know I have been out of touch. I am going through some job transitions so I might be able to get back into updating the blog. I am also open to any guest contributions, so if you have some wise words of wisdom you want to share please feel free to contact me.
Update your Lookups for Windows Phone 7
November 3rd, 2010
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Windows Phone 7 Home Screen
If your company is starting to focus on Mobile news of new phones should always make you think about updating your lookup files. The OS lookup file is the primary one to update but you might have others. Now I am assuming you have already added iPhone, iPad and Andorid since you installed Omniture Insight, so now is the best time to add a new line for Windows Phone 7. It launched in Europe, Singapore and Australasia on October 21, 2010, and is due to launch in the US & Canada on November 8, 2010, with Asia to follow in 2011.
The new user agent will be
Mozilla/4.0 (compatible; MSIE 7.0; Windows Phone OS 7.0; Trident/3.1; IEMobile/7.0)
I plan on adding “Windows Phone OS 7.0″ with a name of “Windows Phone 7″ to my OS lookup file. I also have a custom dimension that groups all the mobile phones that I will need to update. Good luck trying to stay ahead of the mobile OS wave.
KM
Small Elements Explained
October 25th, 2010
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Reading my twitter feed this morning I found this little gem posted by @MichaelHalbrook, a consultant at Adobe, back in July on the Adobe Omniture Blog. It is a very nice overview of one of the most asked questions any one that supports Adobe Omniture Insight gets, what is “Small Elements”. It is a very good read with a lot of good information.
http://blogs.omniture.com/2010/07/15/insight-small-elements/
Unfortunately a denormal dimension isn’t “always capable of showing you the real top elements”. When you have well over 5 million unique items and thousands added daily there isn’t enough ways to filter things down to just 1024 items, but fortunately we have Segment Exports or even a full Visual Transform to pull out all the uniqueness. That data could then be stored in a warehouse so that you can get at the “Long Tail”.
KM
Opening the Black Box
October 19th, 2010
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Black Box
Omniture Insight, SiteCatalyst, Coremetrics, WebTrends, Unica NetInsight, Google Analytics and Yahoo! Web Analytics… the list of analytic tools goes on and on. Most analytic solutions, particularly web traffic analytic solutions, claim to have accurate data yet each one will give very different results. So which one is correct and what are the differences?
All these solutions are correct in their own way but understanding how the counts are derived is a challenge. In fact, it all seems like a Big Black Box. For most Software as a Service (SaaS) solutions you may never know all the details. You are totally dependent on the documentation and vendor technical support to explain the details. However, with Omniture Insight, the Black Box is opened for the customer to see and reconfigure as they wish… every detail, not just a few customized settings.
So what about those differences? They are probably more numerous than most folks realize. So many differences that the likelihood of counts from different tools exactly matching up is nearly impossible. Some of these differences are standard default vendor decisions while others are customer configured. It’s according to what the decision makers feel is important to count and not count. It may be based on the purpose of the data or even if the administrator understands what the setting means.
Omniture Insight is very straight-forward in how it determines the data to be included and how it is configured. There are three phases within the real-time process that defines the data included within a dataset. These are…
- Data Collection – determine data sent to logs
- Log Processing – determine data pulled into the dataset
- Transformation – configure the data to be viewed in the dataset
Data Collection within Omniture Insight is incredibly versatile and drives the ability for multi-channel analytics within a single dataset. Data Collection may be based on web logs, page tagging or flat files from any other enterprise systems. If your dataset includes web traffic then the best method is to collect using a Visual Sensor. It puts you in control of what is collected within the special Visual Sensor log files. A Visual Sensor provides several benefits that include…
- Ability to configure the data to be collected independent of web log settings for Apache or IIS. Usually this is dictated by your web operations team.
- Exceptional data compression many times smaller than standard web logs.
- Ability to drop a configurable cookie for Visitor identification
- Controlled Experimentation for A/B and multi-variant testing
Visual Sensors are controlled via a simple configuration file that you can provide to your web operations team. Typically, this configuration file is used to exclude unnecessary data like graphic images, text files like CSS and application files like JavaScript. It is also used to define your log file name, any special tracking cookies as well as if Controlled Experimentation is to be used.
Data Collection via page tags is possible if the web site is coded with a JavaScript page tag for each applicable page and directed to a host tracking domain that uses Visual Sensors. So Visual Sensors are still used with page tagged data and can provide an added benefit of bridging Visitors that jump between domains.
One of the great benefits of Omniture Insight is its multi-channel analytics. Flat delimited data files from your other enterprise systems can be imported into the dataset by building special Decoders to read the data. You will need to have special data fields that can be used to join data together for a single customer or whatever suits your needs.
Log Processing config
Log Processing is what brings all this data together within a dataset. A profile is created to define the entire configuration for the dataset. The profile defines the Log Processing and the Transformation properties. Log Processing is commonly used to…
- Define the Start and Stop Times
- Define your fields
- Define your Log Sources. This includes both Visual Sensor Logs and special log files that use Decoders.
- Identify any special Transformations that need to occur during the Log Processing phase instead of during the Transformation phase. This might be a lookup file that gets automatically updated daily. If the lookup file is read during the Log Processing phase the changes to the lookup will be processed immediately in real-time.
- Define your Log Entry Conditions. This where you define specifics of the type data included or excluded. The most common inclusions into the dataset are by domain or DNS values and by HTTP Status Codes that may not include 400 or 500 level errors. The most common exclusions are the robot filter by User Agent and IP Address and URI page extensions (.GIF, .JPG, .JS, etc.).
- Transformation Config
Transformation occurs immediately after the completion of Log Processing and defines what shows up in your dataset. Log Processing brings the data into the dataset but you would not see it without defining Dimensions and Transformations in the Transformations phase.
Dimensions are defined segments of data for viewing in a workspace. Dimensions can be cross tabbed and must have Metrics applied to them within a table to show any counts. Transformations are manipulations of the data to format it in a special way to be presented in a Dimension. For example, you may want to take only a specific parameter from a query string and union that with another data field such as the Referrer. Transformations can be used in a number of ways such as Changing Case, Copying, Categorizing, Unioning, Splitting, Flattening, Merging, Formatting and many others. Transformations give you near limitless power to define your data exactly as it is needed.
By reviewing the straight-forward configuration of the Data Collection, Log Processing and Transformation phases you uncover the black box and make the contents inside understandable. This ability is not to be taken for granted. Through proper understanding of your configuration, you significantly reduce misinterpretation of the data, which is prevalent particularly in web analytic solutions. Proper interpretation leads to accurate actionable results and will improve your company’s bottom line.
Guest post by Craig Ketner
Omniture Insight Cool Tricks #1
October 13th, 2010
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Using the Filter Editor to audit workspace selections:
Ok, so partly inspired by Yo Gabba Gabba’s “Cool Tricks, Cool Tricks” and partly by the annoyance of having users pass filtered data that they seem to think is not being filtered, we come upon my first post.
Anyone in the Analytics world will tell you the most dangerous thing about data is data Misinterpretation which can lead to bad decision making. Business analytics professionals are not only tasked with capturing data, but creating a coherent and easily digestible story to accompany the data. But if the data is not what you think it is, WHOA buddy, you are in for a world of pain when someone tries to work your math backwards to the starting point. (Sadly, when this occurs, you undermine your future credibility and take the focus off the analysis and put it squarely on your now heavily weighted shoulders)
Cluttered Workspace
Omniture Insight, proof of God’s existence and love for data geeks, offers a really neat way to overcome the urge to shoot out findings which may not be representative. Enter FILTER EDITOR, bump bump bum…… Filter Editor is a tool which allows the user to create and store filters which then can be applied to the dataset, applied @ segment export and has various other uses. My personal favorite use for Filter Editor is as a workspace selection auditing tool. Now you may ask, “Why would I need a workspace selection auditing tool?” The answer for people like me is easy, many times I load up my workspaces with many tables and visualizations and it can get a little cluttered.
Simple Workspace with a filter
Using the Filter Editor (Right Click -> Add Visualization -> Filter Editor) you can include or exclude data based on whatever rules you want to apply. Once the Filter Editor window is dropped on your workspace you are ready to roll. Right clicking on the Right-Click to build filter text will open another window allowing you to choose New Condition. (More about conditions and multiple conditions to be written in later posts) Here you have two choices, INCLUDE or EXCLUDE, for auditing purposes we want to focus on INLCUDE GROUP WITH WORKSPACE SELECTION. If this option appears @ this stage, you have workspace selections being applied to the data, in order to see what they are you will want to INCLUDE GROUP WITH WORKSPACE SELECTIONS. Very quickly you will be given all of the selections which are currently made on your workspace. Here you can quickly audit whether or not the data set is representing what you desire in your selections, or whether you have some selections you may not want applied for this analysis.
I hope this helps you as much as it has helped me over time. Sometimes when the data looks amazing, I get a rush and need to slow myself down and start crossing off my “Landing Sequence Checklist” before sprinting down the hall exclaiming, “HEY LOOK AT THIS AWESOME DATA”. Tune in next week, same Green Time, Same Green Channel. Later Homies!
ARJ
Plans for future posts
October 6th, 2010
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In an effort to keep my focus on the blog and give some insight on some future posts I thought I would list out some potential topics and possibly solicit some other ideas from the one or two people that might stumble on the site. If you have any ideas post them in the comments.
- Tracking Video
- Upgrade to 5.3
- Raid 1 or Raid 10 on the DPU
- Exporting Data to a Warehouse
Sorry for the Vacation
October 6th, 2010
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Sorry I dropped off the face of the earth. Life got in the way but I am still a very active user of the Adobe Omniture Insight product and I am sure I can come up with a few things to say about it that might and or might not be of interest to the other Insight users. I might also be getting a guest blogger that will be contributing to the site so stay tuned for the reboot of About Insight!
Synchronization Stops on Cluster
March 23rd, 2010
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Since Wednesday I have had an issue where none of my files were synchronizing from the primary server to any of the child servers. I tried everything I knew to try under the sun. I called tech support and we worked though everything under the sun again. The issue was escalated up to professional services and we tried everything under the sun. Nothing worked.
Now I should note in all the instances above each time the same basic things were tried, no one had any additional items to try just what I would call the standard things you do with Insight when it isn’t working as expected. The biggest hint into the problem happened after the standard troubleshooting when client care and I moved two servers from my production FSU to my development FSU and we saw the DPUs synchronize. We then moved them back to production and say them start to synchronize again.
Could it be all was solved? Alas no, synchronization stopped mid way through. In that process we had renamed the Synchronization.log, which had grown to over 6 gigs in just under four days. Doing this caused the partial production synchronization to create a new smaller readable log file. Upon investigating the synchronization.log everything seemed to be fine until it encounters one file and then we see nothing but errors. What was that one file, a blank workspace file in a user workspace folder. So even though this user doesn’t have permission to save anything to the server, the system saves a copy of the users local files to the server in the user directory and then synchronize that out to all servers. A .vw with no name file was the cause of the whole system not being able to synchronize.
I couldn’t have found this out without having support on the phone with me every step of the way. It was great to bounce ideas off of someone and get feedback and confirmation on troubleshooting steps. While the troubleshooting took around 4 hours phone and screen sharing time, and additional hours of research. It was very much a needle and the culprit was not something I thought could bring down an entire Insight system.
If you ever have any kind of synchronization issue and the sync log is too large to review use the windows Find command to filter things down a little bit. Find is installed on every Windows system I would use the following command:
find /i “error” “d:\Visual Server\Trace\Synchronization.log” > error.txt
Then you can look through the error.txt file to see if any error might be causing the issue.
Using Multichannel Analytics to Optimize Ad Spend to Click to Revenue
March 8th, 2010
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Online conversion only is no longer enough. Business models have out grown the model.
The Status Quo Analysisvis done in Isolation. Without the backend data a campain that brought in three customers is viewed as successful, but the backend shows that one is good, one never used the service and one was bad, so that campaign wasn’t as successful as thought.
Extending Conversion: Subscription models. Know more data to focus the campaigns on the segments that give you the ideal customers.
Case Study as presented by the client.
The initial KPI was online conversion. But that didn’t show revenue because of the free trials.
Challenges:
- Membership model with latent success events
- Many data sources
- Campaign attribution
Key Requirement’s
- Marketing Attribution
- Broadcast vs online
Customer analytics
- What is a good customer
- Behavioral analysis
The information needed to get a full view of the customer wasn’t stored in the warehouse. By integrating the missing information into Insight they are able to get a better view on the effectiveness of the ads, the spend and the customer conversions associated to the adds. Using the APIs they are then able to push information from Insight back to Site Catalyst that allows the basic user to view the conversion data. By using Insight they were able to get at the data from multiple sources more quickly and more transparently which really allowed them to report on the overall effectiveness of the advertising and report on that through real data.
How Microsoft Optimizes Online Advertising on Bing using Omniture Insight
March 7th, 2010
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I have been trying to keep names of companies out of the blog just so I am not revealing information I don’t have authority to release, but hey they had it in the title so hopefully that’s ok.
This was the session I was most looking forward to, unfortunately I was really disappointed. The presenter was a marketing guy and it showed, the first 30 minutes were spent showing off Bing. I will admit some of the things that were shown were interesting but they didn’t seem to directly relate to how they were using Insight.
Key points made by the Omniture presenter:
- Insight is “the” insight multi-channel tool
- It provides the 360 view of the customers
- It is unbounded by cubes
- Grouped by customer based on time
- Is a huge segmentation engine
Interesting items from the customer presenter:
- They used Insight to track the performance and effectiveness of their advertising campaigns.
- By identifying the advertising initiatives they could report on the effectiveness of the advertising and the retention of the user.
- By incorporating data from the ad agencies they were able to report on the cost of acquisition and the long term value of the relationship with the user.
- It was also interesting to see how sampling the data was sufficient for them to get good value out of the data. - If only I could convince my users of the value of sampling.
Like I said I was disappointed with how little focus was given to Insight in this presentation. It was good however to see another example of how people use Insight to provide real business value. I am interested to see what other people thought.
