A new tradition has taken root in the Digital Analytics world. Every year in the beginning of October, Google announces a host of new features and functionality for Google Analytics and Google Analytics Premium at the annual GA Summit. Years past have seen the birth of Real
Time Analytics, Google Tag Manager, and Universal Analytics. This year was no different with fourteen distinct new features being announced. As the picture below illustrates, this year’s theme at the summit was Act, Empower, Access. These fourteen features all fit into one part of this theme.
Most businesses demand a 360 degree view of how their companies are performing and aim to grow with every angle. This requires multiple data analytical platforms like Google Analytics, Omnniture etc. Enterprises need to manage large volumes of data efficiently and then transform and present that data in a meaningful and structured format.
However, integrating structured and unstructured data remains one of many challenges facing these companies. The use of multiple analytical tools would help to understand customers, customers’ actions, as well as discover potential opportunities and develop business predictive modeling.
Some of the most popular tools are Google Analytics, Omniture SiteCatalyst, Webtrends, Salesforce, Eloqua, Alexa, and social media analytical tools like Radian 6 and SM2.
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PHILADELPHIA, Sept. 26, 2013. MaassMedia, LLC. today announced the release of a new Google case study that documents Maass’s success in doubling conversion rates for a large telecommunications firm by using the new Google Analytics Premium Data-Driven Attribution Model, in partnership with Google Analytics.
MaassMedia, LLC., a leading digital analytics consulting firm based in Philadelphia and an Authorized Reseller for Google Analytics Premium, used the attribution model to evaluate different networks, placements, and creatives in its client’s marketing campaigns and uncovered opportunities that were undervalued by the previous model. These findings were used to optimize marketing spending. Subsequently, the team saw leads from Display increase 10% while cost per lead remains flat. Conversion rates also doubled thanks to optimized display placements.
The results of this project also provide an ongoing evidence-based framework for optimization and decision making in marketing investments. “The possibilities going forward is immense,” says Melissa Shusterman, Director of Strategic Engagement at MaassMedia, “we are excited to help other Premium client benefit from this attribution model.”
This case study is one of four published success stories from the newly developed Data-Driven Attribution Model. A new feature in Google Analytics Premium, the model uses statistical and economic principles to analyze all touch points in a customer”s interactions across search, social, display, email, and other media. Each marketing channels are then assigned values through automatic and dynamic analyses.
About MaassMedia, LLC:
MaassMedia is a digital marketing analytics consulting firm based in Philadelphia that helps organizations collect and use data to generate actionable customer insights, drive higher site conversions and make better business decisions. Since its inception, MaassMedia has helped numerous clients like Comcast, Coldwell Banker, Gore-Tex, NASDAQ and Lenovo design, develop and implement improvements to their analytics capabilities that deliver measurable and immediate benefits to their bottom-line. For more information, visit http://www.maassmedia.com.
About Google Analytics & Google Analytics Premium:
Google Analytics tells you exactly how visitors got to your site and how they use services and support team, service guarantees, and higher monthly hit limits. For more information, visit http://www.google.com/analytics/premium/
It’s that time of year again and I know all of you fantasy football fans are out there trying to set your lineups. Week 1 has passed (I won my match up, thank you) but there is still a lot of season to go and lots of line up tweaking to do.
I’m assuming like everyone else you troll all of the typical fantasy sites to find out “insider” information on what players are going to be hot that week. Then you take that information and make a best estimate on who to pick. This is standard protocol for most fantasy competitors. So why not take the guess work out by using data, analytics and maybe a little bit of statistics?
1. Getting Data
So one option is doing all of the heavy analysis lifting yourself. Do you have Excel? Awesome, because it’s actually a really powerful analysis tool. Before we get to the analysis though we need the raw data. I use Pro-Football-Reference.com for all of my stats because you can download raw data in CSV format which works really well in Excel.
Once you download the data in CSV format you can just use the “Text to Columns” function under the data tab to clean it up for analysis purposes.
If you’re going to analyze a group of running backs I would grab at least three years worth of data. Then pick some metrics that you want to focus on: age, rushing attempts, rushing yards, total yards, touchdowns, fumbles, etc. Once you get the data cleaned up and in a usable format you can move on to the analysis.
2. Analysis Tools
Excel comes stock with some data analysis tools that can be really useful and easy to manage. Two that I use on a regular basis are located in Functions: Forecast and Correl.
The Forecast function returns the predicted value of the dependent variable for the specific value, x, of the independent variable. What does this mean? If you have several years of rushing data this function will use linear regression to predict future values e.g. rushing yards in 2013. This obviously is not fool proof, but the more data points that you have the more accurate it can be.
The Correl function in Excel Returns the correlation coefficient of two groups of data. You can use the this to determine the relationship between two properties. For example, I may look at data on running backs to try and determine if a players age is a factor in their performance. I could compare age with rushing yards or total fantasy points last year to determine if there is an age range or specific age of a running back that generates the most fantasy points.
3. Add-Ins and 3rd Party Tools
Besides the stock functions that Excel comes with, there are a lot of other analysis tools out there being built by developers (some come from Microsoft directly) that are free. These are usually referred to as “Add-Ins”. You can find a whole group of them here.
The Data Analysis Add-In from Microsoft has a whole range of tools for manipulating data. You can get this for free from the Microsoft site. Once installed it will sit on your data tab to the far right of your screen. Some of these are quite complicated and use advanced statistics, but there are a few that are easier to understand and useful for the novice Excel user.
Another great tool is a fantasy football draft optimizer built by a PHD student located here. This is a front end tool that uses statistics in the background to help a user select the best fantasy team. I know that we’re past draft time, but you can tweak it to find gems off of the waiver wire as well as select your lineup from week to week.
It may take some time, but if you put a little analysis behind your fantasy team if can pay off in the end. Also, since there are such a wide range of data tools for free out in the market you don’t have to be a statistician to get started. Have fun and good luck!
MaassMedia, a Philadelphia-based digital analytics consulting firm and a Google Analytics Certified Partner (GACP), today announced its new strategic relationship with Google to become a Google Analytics Premium Authorized Reseller.