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Product Review

Move Past the Hype: Tips for Selecting A Marketing Automation Platform

By | Marketing, Product Review | No Comments

This article was originally published on CMSWire.com on March 7, 2018.

How do you determine which marketing automation platform is right for your business?

The answer has become increasingly complicated as more vendors are promising AI and machine learning capabilities, dynamic content, and direct integrations with analytics tools, SSPs and DSPs, and social media advertising. The number of platforms available continues to expand – In 2017, Gartner ranked 22 different products in its Magic Quadrant assessment of Multichannel Campaign Management tools. Read More

Dashboarding with Data Studio vs. Google Sheets

By | Analytics, Google Analytics, Product Review | No Comments

Google Sheets was not originally created as a data visualization tool, but it has been flexible enough that many people use it for dashboarding. But with recent and ongoing improvements to Data Studio, including unlimited free reports, Data Studio has become a real contender against Google Sheets.

Which tool should your organization use for dashboarding? Each has its own pros and cons. Deciding on which tool to use depends on your role within your organization and your business needs. Are you a marketing executive looking for an intuitive tool to display high-level metrics? Or are you an analyst that will need to incorporate advanced calculated metrics in a dashboard?

The following checklist of benefits can help you make a decision. Read More

Tableau 10 Review: A Solid Upgrade with Some Room to Improve

By | News, Product Review, Tableau | No Comments

Tableau announced on August 22nd that Adam Selipsky, a former Amazon Web Services sales and marketing exec, will be taking over as CEO of the company. Christian Chabot, their former CEO, will stay on as chairman to help guide strategy. It’s a change designed to help Tableau capture bigger deals and reinvigorate some lagging confidence in the company. It seems to have worked already – at least in the short-term – since Tableau stock saw a nice spike this week (up 15.22% on the NYSE the day after the announcement). Read More

Testing Platforms: Monetate vs. Test & Target

By | Analytics, Optimization, Product Review, Testing | No Comments

As testing and optimization become even more influential to a website’s success, it is important to choose the platform that is right for your business model. I specifically want to talk about the difference between Monetate and Test&Target.

Each platform has its own positives and negatives. Depending on how robust your testing program is or how focused you are in certain areas of your business, you may find that you’re using the wrong tool for your situation.

I am making the assumption that you have already implemented your tool and are just starting your testing program. For the purpose of comparing apples to apples, we will use the example that you are testing a new home page hero image. You have two challenger heroes that you are testing against the default. All the art is finalized and you are about to start the test setup phase.

In Test&Target, you do not need to upload the creative into the tool, and if you have the technical background you can code the challenger pages yourself using custom JavaScript. In Monetate, you will need to request that the “action” be developed on that particular section of the homepage. Once Monetate has finished the action development, the test setup requires no additional coding. After uploading your creative, the rest is pretty much just checkboxes and final approval.

Test&Target distinguishes itself with the ability to run a test that splits traffic evenly between the challenger pages and the default. In order to reach significance in the Monetate setup, each challenger page must have its own designated set of default traffic to use for comparison.

In our example, each challenger page receives 25% of total traffic, and each would be compared with a 25% portion of the traffic to the default. So, essentially, the default is getting 50% of total traffic. In Test&Target, you are able to have an even traffic split between all three experiences, which allows you to more quickly gain significance.

As for reporting, Test&Target has a clean reporting interface with the ability to set up multiple custom success metrics. If you are looking for in depth reporting with custom success metrics, Test&Target is most likely the tool for you. Monetate’s reporting interface is difficult to read and only allows five custom metrics per campaign; however, if you don’t have a dedicated developer with  JavaScript experience, and you don’t have additional custom metrics you want added to each campaign, Monetate is probably the better solution for you. Overall, Test&Target is more robust and easier to work with if you have a technical background and an interest in analytics.

(Monetate Reporting Interface – notice the scrolling you need to do if you have custom metrics)

(Test&Target Reporting Interface – Easy snapshots that can be graphed within the interface)

If targeting or segmentation is important to you, you may want to keep in mind that Monetate does not allow you to target at the offer/experience level. Let’s say you have two promotional offers: one for people in California and another for people in Pennsylvania. With Monetate, you would need to set up two separate campaigns for California and Pennsylvania because you can only target at the campaign level. Using Test&Target, however, you have the ability to target both regions in the same campaign at the offer level. Also, Monetate only allows for up 5,000 different zip codes per campaign, which is something to keep in mind if you have large zip code lists.

Overall, Monetate still has some work to do to provide a better user experience, while Test&Target has a lot of great features but requires a higher degree of technical competency in order run a robust testing program. While neither tool is necessarily “better” than the other, each has its pros and cons. Weighing these against the needs of your business will help you choose the better tool for testing and optimizing your company’s online experience.

Analyzing web analytics data with a BI tool

By | Analytics, Insight, Product Review, Tips and Tricks | No Comments

The world of web analytics is an exciting field that will continue to see tremendous growth with the coming years as the demand for in-depth analysis of web trafficking data increases.  More companies are realizing the importance of using web analytics to their advantage.  Whether the website is based on e-commerce, lead generation, or simply delivering content, all companies can use web tracking to more efficiently accomplish their specific goals.

Gathering the data is the first step, and although it is not the easiest it is indeed the most straightforward part of the analysis process.  After tracking tools such as Google Analytics or Adobe Site Catalyst are implemented in the source code on your website, data will begin pouring in.

You can access the data by logging into your GA or SC account, and, within the web interface, you can generate countless reports implementing various segments and filters for more customized results.  These results can be exported to file formats like Excel workbooks, CSV, and PDF files for immediate use or future reference.  You can certainly use Microsoft Excel to create a multitude of charts and graphs from this data, but the real challenge comes when there is interest for deeper statistical analysis and multi-faceted dashboards.

There are a slew of different business intelligence tools out there, but each company should choose one based on their specific needs.  Ease of use, display attractiveness, statistical rigor, learning curve, and price are just a few of the factors to consider when choosing your BI tool.  In my experience, I have found there are two main categories of tools: those that perform all types of statistical analysis, and those that produce aesthetically pleasing displays.  Unfortunately, I have yet to find a tool that accomplishes both with ease and (relatively) reasonable cost to the user.

Without a doubt, the leading software for statistical analysis is SAS (Statistical Analysis Software).  SAS is moderately easy to learn and the SAS website (www.sas.com) provides excellent documentation on every procedure.  What questions cannot be answered by this documentation can be found elsewhere on the web, as SAS is a widely used tool.  Data can be both imported and exported to various file types with ease, making simultaneous use with other tools uncomplicated.  SAS has the unique ability to generate complex data subsets and manipulations through just a few lines of simple code.  The standard output is quite mechanical looking, and SAS does provide a “ODS graphics” option that makes things look a little prettier, but still there is no “WOW” factor to the graphs.  The main drawback of SAS is the price tag – small companies needing only one or two licenses may find it unrealistic to spend several thousand dollars per year on software that might not be utilized to the full extent of the cost.

An alternative to SAS is R freeware which, as the name states, is completely free to all users.  The user interface is much plainer than that of SAS, and sometimes the coding has more steps, but I have found that R can still accomplish almost everything that SAS can.  There is also a considerable amount of documentation provided by both R (www.r-project.org) and other users on the web.  The main problem with R is data exportation, especially to an Excel format.  Code must be submitted to “write out” data, but only to a CSV file.  You can open this file in Excel, but it takes a few more manipulative steps within Excel to break the comma-delimited files into separate columns within the spreadsheet.  It is not terribly labor intensive, but the additional steps can often become tedious when working with many data sets.  Additionally, R output is even more computerized-looking than that of SAS and the graphs it produces are extremely one-dimensional.  The most appealing aspect of R is definitely the price, which is none.  For most users, this probably outweighs the shortcomings of data exportation and display attractiveness.

Another alternative is Minitab Statistical Software.  For users not familiar with or willing to learn computer programming, Minitab provides all statistical tests through a point-and-click GUI, similar to Microsoft Excel.  You simply import your data and manipulate it within Minitab’s interface.  A wide range of options for calculating descriptive information, test statistics, and regression analyses are available.  Generating all types of plots, charts, and graphs could not be simpler, and users can easily color code, add trend lines, and change display type with the click of a button.  Minitab also provides thorough web documentation and support (www.minitab.com).  Minitab has just as much capability for statistical testing as SAS or R, but SAS is the most versatile and R is free, thus Minitab is my third choice.

For companies interested more in producing beautiful reports than sophisticated statistical analysis, there are numerous products that will deliver stunning, detailed, and informative dashboards and displays.  To me, the most important considerations in choosing this type of BI tool are depth of detail and ease of use.  I have not even begun to scratch the surface of discovering all of the many display tools that exist, but I have found one product that meets all of my expectations.

Tableau is by far the easiest and most user-friendly software of those I have tested.  It is also the 2012 winner of the Digital Analytics Association award for New Technology of the Year.  It allows you to drag-and-drop different dimensions and metrics to various locations within the interface, showing instantaneous results.  Users can create multiple full-screen sheets allowing a high level of detail for each individual display.  Several of these sheets can then be consolidated into one dashboard in which synced filters can be implemented for interactive data segmentation.  Tableau provides free tutorial videos and weekly webinars for continuous education (www.tableausoftware.com).  For users interested in sending automated reports to clients or interacting with dashboards over the web, investing in the pricier Server option is the solution.  Otherwise, Tableau offers both Desktop and Professional versions depending on the complexity of the data source being accessed.