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Data-driven marketing has been a massive industry trend for years, and for good reason: Marketing strategies built on data produce results. However, a recent study shows that 60% of CMOs will cut the size of their analytics departments in half by 2023 because of a lack of promised improvements.

Leaders in marketing have determined the challenges of data-driven marketing — such as inconsistency, biases, and accessibility — are more of a liability than an asset when making marketing decisions. But as a CMO myself, I’m here to say that the problem isn’t data — it’s your people and tools.

When you leverage high-quality data strategically, successful results follow. Currently, the digital divide between data and meaningful KPIs leaves businesses clueless about how to read their data. As a result, they lean on their gut instinct to translate the data instead of understanding the data journey and overall impact. That’s where the problem takes root: If data is misunderstood, it cannot be leveraged strategically.

Why Is High-Quality Data Analysis Necessary for Your Data-Driven Marketing Strategy?

In my experience, I’ve learned that a business culture of innovation only exists by making mistakes. However, the secret to getting your strategy back on track is stepping back and taking the time to break down your process, tools, and data.

Start by asking yourself and your team a few questions: Is the data consistently showing us the same results? Are we comparing apples to apples or correlating data that is actually unrelated? What are the leading indicators that truly show we are succeeding? For a better-performing data-driven marketing strategy, you might need to reevaluate or even rebuild the framework for your data dashboard.

Revamping your data analysis process will elevate the metrics that truly impact business and leave vanity metrics behind. Once valuable metrics are known, it’s essential to properly define them in business terms with leadership and work with necessary teams to create a process that leverages the data for your business’s success.

What Does High-Quality Data Analysis Look Like in Action?

I worked with a client whose business was decimated by a website relaunch and who needed help resolving the issue. At the time, this client didn’t have the ability to track her inbound calls, so I started by setting up call tracking. Once leading indicators were established, I was able to dig into the sales process and find ways to integrate the two components.

Creating this feedback loop can be a six-month process, but in the end, I was able to provide a complete picture of relevant data. The truth is that this process requires something many business people don’t have naturally: patience. It takes time to fully understand the story that the data is telling. Fortunately, it’s always worthwhile. Based on the end revenue data, I could then reverse-engineer to the source to find what was working positively.

The key to success is peeling back the layers of data to see how you got to this point and trusting what you find because, at the end of the day, data never lies. Businesses that don’t make data-informed decisions are going to fail. Now is the time to dig into your own data and find new ways to succeed.

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