There are more than 6,000 marketing analytics solutions out there, yet we still struggle to access the analytics we need to make the strategic decisions that arise on a daily basis.

The data is there — we have access to more of it than ever before. Still, marketers are left looking for a better way to inform decisions about budget allocation, ROI and beyond. So why, with so many analytics tools and data available, are we still left searching for information? The truth is, many of today’s analytics reports just aren’t actionable.

Many reports shed light on what happened in the past, but they don’t suggest what would happen moving forward if you were to implement a particular strategy. We’ve all been there: You get a report, you see interesting data in front of you, but you reach the end and you’re not sure what to do next.

Building a marketing analytics stack is a multiphased process. First you need channel analytics to help you execute and provide activity-level analytics. Then you need performance analytics to correlate your marketing activity to business impact. In most analytics stacks, there’s a missing piece: a forecasting or predictive analytics tool to help marketers decide what to do next.

Regardless of where you are in building your marketing technology stack and choosing which analytic tools to invest in, here’s a five-step approach to ensure you’re getting the most from your analytics.

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1. Define Your Analytics Purpose

The first step is to be crystal clear in the specific analytics need you are looking to fulfill. Do you need to improve your social media performance? Do you need to identify which shift in your marketing plan will ensure that you hit your sales goals? Whatever your objective, it’s important to be realistic in what the desired end state will be.

The biggest mistake I see companies make is investing time and money in creating an analytics dashboard without a clearly defined goal or purpose. They believe they will be able to make better strategic decisions if they have the data at their fingertips, so they centralize their data but then have no idea how to put the information into action. With a defined analytics purpose from the get-go, marketers will avoid wasted resources down the line.

2. Identify Your Key Data Points

Once you’ve determined your analytics needs, you must identify the most important data points to visualize and frequently report on. Whatever your KPI may be — revenue, impressions, clicks, reach, awareness or something else — define how you will measure success, and figure out what you’re going to focus on.

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3. Make Sure You Trust Your Data Sources

Next, it’s important to make sure you understand how data is being collected and, more importantly, to decide whether you trust the methodology. If you don’t trust the methodology of data collection, you won’t be able to trust the analysis. 

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However, it’s important that you don’t get hung up here. Sometimes people can become fixated on achieving perfect data. You need to recognize that there will always be some level of error in your data and that you just need to be comfortable with that level and not let it hinder you from making data-driven decisions.

4. Learn From the Past

Once you have your data ready, it’s time to get a clear understanding of what worked well in the past — and why. Many reports focus on totals or visualize one singular data point over time. With information in silos, the reports provide little value.

The most useful insights come from making comparisons across data sets. Those comparisons help you understand the relationships between variables. Make the most of your data by getting a good understanding of how variables have affected one another historically.

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5. Plan for the Future Through Forecasting Scenarios

The final and most important step is to combine your understanding of the past with forward-looking scenario planning. Evaluate what-if scenarios to predict what might happen in the future, informed by the data you already have.

For example, you might want to forecast what would happen if you shifted your digital expenditures from LinkedIn to Facebook, or if you invested more in podcasting or PR. This is where most marketing analytics solutions are lacking, and quite frankly, it is the key to unlocking data-driven decisions that will actually improve performance.

This final piece is what will help bridge the gap between chief marketing officers and chief financial officers. Typically, marketing executives have been mostly focused on looking backward while CFOs want to know how today’s decisions will impact tomorrow’s sales. If marketing can integrate a forecasting capability into its marketing analytics stack, CFOs and CMOs will finally both be using the same language and they will both be looking in the same direction — forward.

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