There are roughly 500 million marketing analytics platforms in the marketplace right now. Or that’s what it feels like, at least.
The sheer number of platforms represents a major challenge for marketing teams that are shopping for new solutions. Not only is there a mountain of software to research,
And it’s not always clear if a platform will actually do what it promises. That’s a little scary considering how much time and money it takes to get up and running with a new analytics tool.
To help you find a solution that meets your unique needs, we’ve built the following list of questions, broken out by current skill level and goals. These are some of the most important, most illuminating questions you can ask anyone trying to sell you
Level 1: Basic Automated Reporting by Marketing Source
When you’re just getting started with analytics, your focus is usually on two things: automating the collection of your marketing data (so you’re not stuck manually downloading everything and sticking it in a spreadsheet) and displaying your results in a basic dashboard. This is what we call Level 1, and it’s where most marketing teams begin their analytics journey.
Good questions to ask are:
- How much time does it take to use this platform?
- Will you need to dedicate an employee to managing and supporting this tool? If so, how much of their workweek will it take?
- How does the solution store the marketing data it collects? Some tools don’t actually store data — they just display it in a dashboard, while the underlying data continues to “live” in the source systems. That means you can’t clean up errors, apply business rules or store data for the long haul.
- Can this analytics solution automatically collect data from all your sources of marketing data? Even offline sources like TV and radio?
- If a data connection fails or breaks, who is responsible for repairing it?
Level 2: Reporting Across Channels and Campaigns
At Level 2, your reporting becomes more complex. You’re not just looking at individual marketing sources — you’re measuring the performance of entire campaigns and channels. And your dashboards usually need to be more customized.
In addition to all the questions you asked at Level 1, you’ll want to know:
- Will this solution automatically blend your datasets together? To understand total campaign or channel performance, you’ll need to combine data from different sources into a single view. Some tools will ask you to do that on your own.
Doesthe solution offer BI or visualization capabilities? Will it “play nicely” with dedicated, third-party BI or visualization tools? Some analytics tools will let you bring data onto their platform, but if you ever leave them, or if you ever need to use that data with other platforms, it can be difficult or impossible to move your data to where you choose.
Level 3: Understanding Channel Value to Optimize Spend
Level 3 is exciting but also more challenging. You’re able to connect your marketing results — sales, downloads, leads, etc. — to the marketing activities that produced them. In many cases, you’ll need to incorporate sales and transactional data into your analytics.
You’ll want to ask the previous Level 1 and 2 questions, as well as the following:
- Does the solution support a common tracking methodology, so you can understand the value of each channel or campaign?
- Will you be able to bring additional contextual information — including sales and transactional data, budget and goals — into the solution?
Level 4: Predicting the Right Media Mix and Forecasting ROI
This is the most advanced, most technically challenging level of marketing analytics. You start using your historical data with statistical modeling to predict the results of upcoming campaigns so you can optimize your tactics.
If you’re shopping for Level 4 solutions, you’ll need to ask everything from Levels 1, 2 and 3, plus the following questions:
- Do you have people on your team — or does your vendor have people on staff — who know how to use R and other statistical modeling languages?
- Does your database architecture support the inclusion of these statistical modeling languages, especially for custom situations?
We’ve compiled these questions into a handy checklist you can fill in the next time you’re in conversation with a marketing analytics platform vendor.
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