Content advertising Metrics and Analytics: five forms of facts 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, creating a paradoxical relationship between executive decision-making and implementation on the ground.

On one side, 94% of companies believe that data is essential to their growth.

However, at the same time, 63% employees say they struggle to process data in a feasible time frame.

As digital publishing moves toward a data-driven model, in-depth analysis is required for businesses that want to stay competitive.

Content marketers need to adapt their skills and build advanced, privacy-focused technology stacks that can handle first-party data.

This, in turn, allows them to create highly relevant, credible and engaging content that resonates Google’s EAT (Expertise, Authoritative, Trustworthy) criteria. and it ranks well in search engines.

Evolving Data: A Story of Complexity and Opportunity

The data analysis associated with content marketing presents a multifaceted picture.

Many factors come into play, including government regulations, growing privacy concerns, and the upcoming depreciation of third-party cookies (to mention just a few examples).

Nevertheless, both the prevalence of data and its use in content marketing are expected to grow exponentially in the coming years and decades.

  • The CAGR (compound annual growth rate) for spending on analytics solutions will increase by 12.8% between 2021 and 2025.
  • 66% of marketers expects a general increase in spending on content marketing in 2022.
  • 81% of marketers says their company sees content as a “core strategy.”
  • 85% of buyers wants brands to use only first-party data.
  • 86% consumers feel anxious about data privacy.

These figures highlight both the opportunities and challenges of a future in which data is widely available but limited in its use.

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

Read more about SEJ

The role of data and analytics in content marketing

Access to historical and real-time data allows content marketers to navigate a digital landscape where users’ interests may shift a little further than the time it takes to hear the word “World Wide Web.”

A veritable cacophony of conditions influence consumer tastes, from political events to passing pop culture fads.

Data-driven approaches to provide a kind of buffer against this uncertainty.

They allow marketers to adjust their content strategy by measuring certain types of user behavior and accessing the right platforms.

In addition, point solutions are largely being supplanted by end-to-end CDPs (customer data platforms) that aggregate inputs from many sources.

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

Essentially, content marketers can generate actionable insights without necessarily relying on advanced infrastructure or deep technical knowledge.

Read more about SEJ

Let’s take a look at five key types of data insights that matter to content marketers.

1. Projections of industry trends

Historical data analysis allows content markers to they predict current trendsthe emergence of new distribution channels, changing fashions and emphases in industries, seasonal variations of keywords and more.

“Time-series” data tracks a set of data points over a consistent period, providing insight into long-term user behavior and laying the groundwork for detailed predictions.

As time series analytics typically require large amounts of data, trend projection is one area where predictive engines and machine learning algorithms are essential to turn raw information into actionable insights.

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

2. Participation according to content trend and category

Categorical data related to well-defined subjects and topics offers insight into audience engagement.

This has obvious implications for the direction of your content strategy and editorial decisions.

Similarly, understanding what categories visitors go to when they leave a page means you can add content that’s missing from your primary landing pages.

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

Metrics that provide insight into engagement: bounce rate, time on page, ROI, conversions.

Read more about SEJ

3. On-site behavior and experience

Site behavior data provides immediate insight into the effectiveness of content types, formats and channels.

Machine learning also enabled rapid processing of qualitative feedback.

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

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

Working with this data to track user experience offers opportunities to eliminate drop points and solidify high-converting parts of a website’s sales funnel.

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

Read more about SEJ

4. Data, Content, Customer Profiles and Segmentation

Clearly defined user segments that include data points such as location, visit times, purchase frequency, interests and so on allow content marketers to create tailored, highly specific content that is likely to excel at performance metrics such as engagement and conversions .

In addition to providing real-time insight in the nature of the user’s current interests and preferences, detailed profiles also form a strong basis for predicting future behavior.

Automated technology found in data platforms is particularly effective in streamlining this process.

Measurements that enable insight into profiles and segmentation: location, times of visits, frequency of purchases.

5. Performance of data and content in search engines

Search engine performance is usually related to tracking rankings.

However, measuring the effectiveness of content is much more than just monitoring SERP positions.

Insights aimed at improving search performance must consider a variety of data points.

These include rank zero, long-tail distribution, click-through rate, prevalence in featured snippets, content longevity, and more.

Research conducted by my company, BrightEdge, shows that content preferences can vary by industry. That’s why it’s critical to use data to inform your content strategies.

Comprehensive SEO analytics platforms (as opposed to point solutions) perform this function and allow content marketers to emulate the most successful content topics and formats.

They also provide valuable, actionable data to optimize promising but underperforming pages.

Metrics that provide insight into engagement: organic traffic, CTR, SERP positions, share of voice.

Read more about SEJ

The benefits of a data-driven content marketing model

Advanced analytics is an essential weapon in the modern content marketer’s arsenal.

It’s no longer about whether you’re leveraging data – it should be self-evident.

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

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

And analytics platforms offer an invaluable opportunity to sharpen your competitive edge.

A the first customera data-driven approach to content marketing takes into account a variety of factors, including evolving user interests, changes in channel preferences and applicable legal restrictions.

As the world becomes increasingly data-centric, digital businesses need to take advantage of the opportunities presented and measure the return on their content marketing investment.

More resources:

Featured image: Gorodenkoff/Shutterstock


Leave a Comment

error: Content is protected !!