Choosing an analytics platform is a lot like purchasing a car. It’s an investment with a variety of factors and considerations, all of which weigh into an eventual, well-informed choice.

Yet even the most disciplined car buyer may instinctively be drawn to the flashiest available option. Wow-wee, wouldn’t that stick-shift convertible with a V-8 engine look nice in my driveway? Seconds later they remember, wait, I don’t know how to drive a stick-shift, it mostly rains in my region, and my state has speed traps galore.

Back to the drawing board. After reworking their original plan, outlining their family’s priorities with their spouse, and assessing the value of a range of automobiles that fit their specific needs, they decide on a sedan with outstanding gas mileage, folding seats to fit an up-right bass and Sparky the dog, all at a rate that will saves $330 dollars a month compared to the next best choice.

For marketers, an analytics platform selection should mirror the strategy that leads them to that sedan—a well outlined and vetted plan that ultimately produces value for the company. In our Analytics Platform Comparison Report, we’ve outline the top criteria that marketing leaders should consider when vetting an analytics solution. However, the key part in the selection truly relies on mapping this criteria to your company’s unique objectives.

Here are some helpful tips to consider when outlining the most important factors for an analytics platform that aligns with your company:


Who will need to sign-off on the ultimate decision for a new analytics platform? Which departments will be impacted by this change? Before you begin your research process, it’s important to interview your internal stakeholders and outline what role they will play in the selection. Consult the “About,” “Support & Resources,” as well as the “Security” sections of our report to align your recommendations with the correct analytics platform audience, level of support, and security features that match your stakeholder needs.

Business Requirements and Goals

Like any technology investment, your analytics platform should directly support your current business requirements as well as future company goals. By first having a keen understanding of what these critical activities are, marketers can then map them to the “Data Availability” and “Reporting and Features” sections of our report. It’s vital to select the analytics platform that provides access to data that will allow you to achieve these business objectives and reporting features that solve the data challenges that can roadblock reaching company goals.

Data Governance

Every company should have a data governance plan—an overall strategy of maintained processes that enable the proper handling of data throughout an organization. Look at the sections of “Usability,” “Support and Resources,” “Tag Management,” and “Security” to identify if the procedures outlined in the data governance plan can be supported by line items in those sections. For example, if 24/7 support and separate staging and production libraries are needed for your governance plan, make sure to select a solution with those options.

Program Integration

How does your analytics platform align with the other systems in your marketing technology cloud? Consult the “Integrations” section to understand how your analytics platform can connect with 3rd party data sources and other marketing cloud platforms. This integration is key to achieving a single view of the customer which can then drive more relevant targeting and personalized experiences.


How much can your company invest in an analytics solution? Make sure you are fully aware of the cost structure of the analytics solutions you are vetting—not all analytics solutions bill the same and there are often different tiers of costs suited for a variety of company structures. Identify the different cost structures in the “Cost” section of the analytics matrix.

About the Author: Kristen Dunham

As a Digital Marketing Analyst for R2i Kristen illuminates marketing performance and opportunities by threading together data from multi-channel experiences into a tapestry of visual stories. Motivated from a background in anthropology, she firmly believes that data analytics is the new archaeology, aiding in the understanding of human behavior through analysis of prior activity. When she is not acting as the Indiana Jones of analytics, Kristen likes to test her problem solving skills on the rock climbing wall.

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