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Beating the Spreadsheet Blues

3 minute read
Pierre DeBois avatar

Remember the old days when it seemed that all you need to know from your computer is how to save a Microsoft Excel file? If you are a marketer those days seem rosy compared to what’s happening in digital media. 

New ways of capturing data has introduced challenges in inspecting data and developing models.  Marketers with a limited knowledge of traditional query language must access data. And as I wrote in the post, How Marketers Can Get A Better Handle On Their Data, new markup language elements raises the number of ways data can be associated with web and app elements.  This has increased the ways the data can be used in calculations for desired results.

Because of this new data challenge, analytic solution providers have created a number of options to simplify data usage.

Enhanced Analytic Reporting 

By deemphasizing database syntax, new solutions have emerged to quickly blend data into reports and calculation models. These options permit marketing managers to adjust data models based on their judgment of the business application rather that entirely upon query language concerns.

Plugins for Google Spreadsheet and Microsoft Excel, for example, can enhance analytic reporting with a nuanced review of marketing data. 

Google introduced a Data Import feature for Google Analytics. The feature imports external data into standard and custom reports at the user’s discretion. The types of data that can be selected are complimentary to the dimension and metrics reported. 

For example, Google suggests in its Data Import description that refund data can be incorporated into the ecommerce report.  This merge  provides a useful picture of cash flow from sales and insight into point of sale activity. 

Google Analytics is not the only web analytics solution that offers a data import feature. But there are limitations — Google does not blend time-based or geographic data for example.  Moreover, your team may require additional calculations after importing data. 

Learning Opportunities

Making the Most of Spreadsheets

This analysis scenario highlights how a spreadsheet can be used effectively. A tab can be used for inserting the data, can the cells can be referenced on another tab to calculate the data or provide graphics.  To ease this process developers have created plugins for both Excel and Google Spreadsheet. 

Supermetrics Data Grabber can export Google Analytic data into a spreadsheet, allowing for more combinations of dimensions and metrics. Excellent Analytics, which was purchased by Next Analytics earlier this year, and Tatvic are other examples of Excel plugin.  

Google Spreadsheets are similar to Excel, but for plugins, they rely on Google App Scripts. Google App Scripts are JavaScript plugins meant to work with the APIs and functions of various Google applications.  Developers can create and develop their own custom script to suit their spreadsheet purposes, but there are ready-to-use scripts available.  These scripts can be published via the Chrome Web Store. For Google Analytics, marketers can search and use Google Analytics Report Automation as a ready made script for custom dashboards.    

Be Aware of Limitations

Despite these spreadsheet features, capacity limitations still exist, and thus should be considered when planning analytic capability.   The number of rows and columns available limit the amount of data that can be imported into a spreadsheet tab.  Thus, more advanced, cloud based dashboards like Tableau are popular for large datasets.

But for instances of modeling data segments, investigating initial assumption, or working with data from small businesses, a spreadsheet combined with a plugin can bring back the simplicity of the good ‘ol days but with a bit more of today’s sophistication.