How to Do Data-Driven Content Marketing

Content marketing is all about selling your business through great, engaging content that has a red thread, and an overarching story. Content marketing requires great writing, editing, design and storytelling skills. But data-driven content marketing also requires you to put your analytical mind on.

Here’s how to move from content marketing to data-driven content marketing.

Understanding the Importance of Data-Driven Content Marketing

Data-driven content marketing has a distinct edge over the old way of doing content marketing. It allows you to identify audience preferences and behaviors, optimize content for better engagement, improve content ROI, enhance customer experience, and predict future trends and needs. By using data to guide your content marketing efforts, you can create more targeted, relevant, and effective content that drives results.

Setting Clear Goals and KPIs

Before diving into data collection, defining your content marketing goals is essential. Common objectives might include increasing website traffic, generating leads, boosting brand awareness, enhancing customer engagement, and driving sales. KPIs to measure success, such as page views, time on page, bounce rate, conversion rate, and social shares, is crucial for successful data-driven content marketing.

Collecting and Analyzing Data

Identifying Data Sources

To gather data effectively, various tools and platforms can be used. Google Analytics provides insights into website traffic and user behavior. Social media analytics reveal engagement metrics across different platforms. SEO tools like SEMrush or Ahrefs assist in keyword research and SEO performance, while tools like Google Tag Manager (GTM) give you deeper insights into customer journeys and trends. CRM systems offer a deeper understanding of customer interactions and sales data, while surveys and feedback provide direct input from your audience.

Analyzing Data

Once the data is collected, segmenting your audience based on demographics, behavior, interests, and engagement levels is important. Recurring themes in your data can help you understand what content resonates most with your audience. Assessing which pieces of content are performing well and which aren’t by analyzing metrics like engagement rates, shares, comments, and conversions is a cornerstone of data-driven content marketing.

You also need to make sure that your data is as clean and accurate as possible. This can be easier said than done. Take GTM as an example. It requires a lot of time and highly-technical talent to set up, and still leaves plenty of scope for mistakes. That’s why it can be good to automate as much of the data analysis process as possible. TagInsight can help automate your GTM work, giving you greater trust in what your customer journey data is telling you.

Developing a Data-Driven Content Strategy

Creating Audience Personas

Detailed audience personas based on your data analysis can significantly enhance your content strategy. These can include demographic details such as age, gender, location, interests, and, crucially, their career path. Understanding their pain points and challenges, preferred content formats (blogs, videos, infographics, etc.), and commonly used platforms can provide valuable insights.

Ideating and Creating Content

Content ideas generated from data insights tend to be more closely aligned with your audience’s interests and needs. Identifying and filling content gaps where valuable information is missing, and targeting keywords with high search volume and low competition, can get your product in front of an even broader audience.

Distributing Content

A well-planned content distribution strategy, also known as a cadence, involves choosing the right platforms where your audience is most active. Tailoring your content to fit the nuances of each platform and maintaining a consistent posting schedule can help you keep your audience engaged. Developing a solid strategy is vital for effective data-driven content marketing.

Implementing and Monitoring Your Strategy

Carrying It Out

Creating and distributing your content according to your strategy is key. Project management tools, such as Asana, can help you keep track of your content calendar and ensure timely delivery.

Monitoring and Analysis

Continuous monitoring of your content’s performance using established KPIs is essential. Regular data analysis helps identify successes, understand what’s working well and why, as well as what isn’t working and why. Making data-driven adjustments to your strategy can significantly improve performance. Implementing and monitoring are crucial steps in data-driven content marketing.

Iterating and Improving

Data-driven content marketing is an ongoing process. Refining your strategy based on gathered insights helps it evolve. Experimenting with different content formats, headlines, and distribution times can reveal what performs best. Incorporating audience feedback enhances content relevance and value. Staying updated with industry trends and adjusting your strategy accordingly is key to maintaining the effectiveness of your data-driven content marketing strategy.

Tools for Data-Driven Content Marketing

Several tools can turbocharge your data-driven content marketing efforts. These are:

• Google Analytics provides valuable insights into website performance. 
• HubSpot offers CRM and inbound marketing analytics. Hootsuite or Buffer are useful for social media management and analytics. 
• TagInsight helps you fully understand your customer journeys, and detect shifts in them. 
• Ahrefs or SEMrush are excellent for SEO and keyword research. 
• Mailchimp provides comprehensive email marketing analytics.

The Main Points

To implement a data-driven content marketing strategy, you need a systematic way to gather, analyze, and use data. By understanding your audience and tailoring your content to their preferences, you can boost engagement, achieve better results, and meet your marketing goals. The secret to success in data-driven content marketing is to continuously monitor, analyze, and refine your efforts based on the insights you gather, and not be afraid to use that data to take calculated risks.