Content Marketing Metrics & Analytics: 5 Types Of Data Insights

Content marketers are increasingly tasked with making sense of large and unwieldy data sets.

However, they often lack the skills to process this data, which creates a paradoxical relationship between executive decision-making and implementation on the ground.

on one hand, 94% of companies feel that data is essential to their growth.

However, at the same time, 63% of employees say they struggle to process data in a workable timeframe.

As digital publishing moves towards a data-driven model, deep analysis is required for companies that want to remain competitive.

Content marketers must adapt their skill sets and build advanced, privacy-focused technology stacks that can handle first-party data.

This, in turn, enables them to create relevant, credible, and engaging content that meets Google EAT criteria (Experience, Authenticity, Trustworthiness) and ranks well in search engines.

Evolving Data: A Story of Complexity and Opportunity

Data analysis as it relates to content marketing presents a multifaceted picture.

Many factors come into play, including government regulations, growing concerns about privacy, and the prospective consumption of third-party cookies (to name a few).

However, the penetration and use of data in content marketing is expected to grow exponentially in the coming years and decades.

  • CAGR (Compound Annual Growth Rate) of spending on analytics solutions will increase by 12.8% Between 2021 and 2025.
  • 66% of marketers expect an overall increase in content marketing spending in 2022.
  • 81% of marketers say their business views content as a “core strategy”.
  • 85% of customers want brands to use only first-party data.
  • 86% of consumers are concerned about data privacy.

These figures highlight both possibilities and challenges in a future where data is widely available, but limited in its scope of use.

Content marketers are in a precarious position when balancing competing concerns. As a result, first-party data is taking center stage as a primary driver of decision-making in the digital space.

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The role of data and analytics in content marketing

Access to historical and real data allows content marketers to navigate a digital landscape where users’ interests can change in little more time than it takes to say “the World Wide Web.”

A real cacophony of circumstances influences consumer tastes, from political events to pop culture fads.

Data-driven approaches provide something of a bulwark against this uncertainty.

It enables marketers to tailor content strategy by gauging specific types of user behavior and reaching out to the right platforms.

Moreover, point solutions are being largely replaced by CDPs (Customer Data Platforms) that aggregate input from many sources.

These applications typically include AI (artificial intelligence) and automation mechanisms to generate insights without the direct involvement of data scientists.

Crucially, content marketers can generate useful insights without necessarily relying on advanced infrastructure or in-depth technical knowledge.

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Let’s look at five main types of data insights that are relevant to content marketers.

1. Projections of industry trends

Analyzing historical data enables content tags to predict topical trends, the emergence of new distribution channels, changing fashions and assertions within industries, seasonal keyword variations, and more.

Time Series data tracks a set of data points over a consistent period of time, providing insight into long-term user behavior and laying the groundwork for detailed forecasts.

Because time series analyzes typically require large amounts of data, trend projection represents one area where prediction engines and machine learning algorithms are essential for translating raw information into actionable insights.

Metrics that provide insights into industry trends: traffic, keyword search volumes, and retention rates for products and services.

2. Post by content direction and category

Categorical data associated with well-defined themes and topics provide insights into audience engagement.

This has clear implications for the direction of your content strategy and editorial choices.

In the same vein, understanding which categories visitors go to after they leave a page means you can add content that is lacking in basic landing pages.

Where topic category data provides general insights into user engagement, specific performance metrics such as conversions allow for high-level analysis of the ROI of content when grouped into categories.

Metrics that provide insight into engagement: bounce rate, time on page, return on investment, and conversions.

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3. Conduct and experience on the site

Data about on-site behavior provides an immediate window into the effectiveness of content types, formats, and channels.

Machine learning also enabled the rapid processing of qualitative feedback.

One such example is sentiment analysis, which relies on advanced technologies such as biometrics and text analysis to extract data about customer attitudes.

User behavior data enables content marketers to visualize the entire customer journey, from initial search to purchase or bounce.

Working with this data to track the customer experience provides opportunities to address breaking points and solidify the high-converting parts of a website’s sales funnel.

Metrics that provide insight into site behavior: shares, engagement, and qualitative feedback.

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4. Data, content, customer profiles and segmentation

Clearly defined user segments that include data points such as location, visit times, purchase frequency, interests, etc. enable content marketers to create personalized, highly specific content that is more likely to outperform performance metrics such as engagement and conversions.

In addition to providing real-time insights into the nature of users’ current interests and preferences, detailed profiles also form a solid basis for predicting future behavior.

The automated technology found in data platforms is particularly effective at streamlining this process.

Metrics that provide insight into profiles and segmentation: location, visit times, and frequency of purchase.

5. Data and content performance in search engines

Search engine performance is often confused with ranking tracking.

But there is more to measuring content effectiveness than simply monitoring SERP positions.

Statistics geared towards improving search performance need to take into account various data points.

This includes zero position rankings, long-term distribution, click-through rates, prevalence in featured snippets, content longevity, and more.

Research conducted by my company, BrightEdge, shows that content preferences can vary by industry. Thus, it is essential to use data to inform your content strategies.

All-in-one SEO analytics platforms (as opposed to point solutions) implement this functionality and enable content marketers to iterate on high-performance topics and content formats.

Likewise, they provide valuable, actionable data for optimizing promising but underperforming pages.

Metrics that provide insight into engagement: organic traffic, click-through rates, SERP positions, and voice engagement.

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Benefits of a data-driven content marketing model

Advanced analytics are essential weapons in the modern content marketer’s arsenal.

It’s no longer about whether you make use of the data – that should be a given.

Instead, you should think about how effectively you implement innovative technology solutions and generate unique insights.

Content usually lies at the heart of successful marketing, sales, and retention strategies.

Analytics platforms provide an invaluable opportunity to increase your competitive edge.

A first-party data-driven approach to content marketing accounts for several factors, including evolving user interests, shifts in channel preferences, and applicable legal restrictions.

As the world becomes more data-centric, digital companies need to take advantage of the opportunities on offer and measure the ROI of content marketing.

More resources:

  • Use these three SEO metrics to measure your content marketing return on investment
  • How to assess the SEO value of a piece of content
  • Content Marketing: The Ultimate Guide for Beginners

Featured image: Gorodenkoff/Shutterstock

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