Using Data and Business Analytics To Improve Digital Marketing Strategies

Data is a powerful force in the business world. It’s long been used as a way to tackle business challenges head-on, but in today’s digital climate, where there’s so much information to sort through, the question becomes how to do so effectively. 

This article will take a look at techniques your business can use to start capturing data without getting overwhelmed, then discuss how you should turn that data around into actionable insights you can use to refine your digital marketing strategies.

Bringing in the Data

Without raw data, you can’t have any insights. So, the first step for your business is usually finding out what kind of data you need and getting your hands on it.

Broadly speaking, there are three types of data that are of interest to marketing teams:

  • Customer data: Straightforward, factual information about customers. Their names, email addresses, things they’ve purchased, and things that they’ve searched for online fall under this category.
  • Financial data: You can consider these as your internal numbers, such as marketing statistics, marketing costs, and any other transactions that your business is involved in. These are indicators that will come into play when assessing your business’ performance down the line.
  • Operational data: Data derived from your other business processes, such as lead generation and customer databases, falls into this category. 

As you can see, a large amount of that data is internally generated, so you should already have access to it.

analyze customer data
Image: Analyze Customer Data- Source

What about customer data that you don’t already have sitting around in your company databases, though? In some cases, you can simply ask for it.

Active data collection strategies involve you asking customers directly for the information you need to perform your business analytics. The most straightforward method is through online surveys, where you might have customers give you demographic information and answer questions about their preferences, opinions, and consumer needs.

Since you’re asking for personal details, going this route can present some difficulties in terms of customers trusting your intentions. You can allay these concerns by telling customers up front how you will use the data you collect, demonstrating that your collection process is secure, and offering something in exchange for said information.

If you’re not keen on having customers take an active role in your collection efforts you may opt for passive data collection strategies instead. These allow you to utilize web tools — such as cookies — to capture information from anyone who visits your site. 

It’s useful for learning about the browser histories and online lifestyles of the customers who interact with your brand, allowing you to form a better picture of who you’re appealing to. Similarly, many social media platforms have built-in analytic tools you can use to find out more about your followers and how they interact with your brand.

Many businesses find that some combination of active and passive data collection strategies work well for bringing in the data, but that’s only part of the equation. You’ve also got to turn that data into something actionable to be of use, something we’ll look at next.

From Data to Insights

The value of your data is largely in how you use it. This is where analytics — the process of cleaning up and visualizing data — comes into play.

Analysis is all about transforming raw data into more digestible forms so that you can glean information from it. From there, you can use it to draw conclusions and make important marketing decisions.

For example, data mining is often a first step in the analytics process. This subset of data analysis pertains to finding patterns in big datasets, making data more useful. It’s from there that you may arrive at something like customer analytics, where you start to organize and visualize your data. 

It’s a hefty task, which is why you’ll need to make sure you’ve got the appropriate big data software solutions to help you sort through whatever you’ve collected. 

In time, you’ll bring your data to the point where you can evaluate the performance of current marketing efforts and, through methodologies such as predictive analytics, understand the probable outcomes of future ones. 

How Data Can Power Marketing

Once you’re able to pull information from data, a whole world of possibilities awaits. 

With the right data collected from customers, you can paint a better picture of your current audience. Then you can build personas around what you know of them. 

buyer persona example
Image: Buyer persona example – Source

This allows you to better target your content for maximum resonance. It should also help you boost engagement from your marketing campaigns.

Data and analysis can help you accurately measure the performance of marketing efforts. Being able to show a precise ROI will help you justify your actions to stakeholders. It will also help explain how marketing actions directly influence profits.

Then there are the predictive powers of analytics — using past data to determine future probabilities. You can optimize future campaigns based on past campaign success. Then you only have to make subtle tweaks to adapt for different demographics within your broader audience.

Key Takeaways

Big data can bring big improvements to your marketing strategies. However,  you need to make sure you’re targeting the right data as well as reliably collecting and analyzing it.

Follow through with the process and you’ll gain insights that will help you better measure your marketing performance. These insights will also improve your decision-making so that you can enjoy better business outcomes in the future.

These benefits are essential for brands looking to gain a competitive edge in the digital age. Be sure to explore how data and analytics might apply to your marketing strategies. This will help you start making the adjustments you need to put these techniques into practice.

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Luke Smith
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