How Marketers Can Create a More Effective and Agile Content Strategy with a Data-Driven Approach

200-page annual content plans are dead

Marketers are more focused on "filling" their "annual content strategy" rather than creating real value for their readers based on actual events:

• Target audience interest in terms of what they are searching for and where they consume content (social media, digital magazines, blogs)
• Changes in search engine algorithms, ranking methods, and keyword trends
• Competitor activity, including reactive and proactive approaches.
• Current events, which can be used as a hook for a product, service, or idea we want to embed in our target audience's mind.

A flexible, data-driven approach will help you incorporate this into your daily workflow.

Creating content in a vacuum doesn't work

The agile approach is not "against" having a plan; rather, it is "for" quickly assessing the space we want to operate in to:

• Grab attention ("Awareness")
• Build relationships ("Interest")
• Help customers make informed decisions ("Consideration/Intent/Evaluation")
• Successfully sell a product or service ("Purchase").

Once we have successfully assessed our space in terms of "audience" (who are they? what is their pain point? where do they "hang out" in the digital sphere?), we can move on to assessing their "current interests" (what content are they consuming on social media and actively searching for).

This allows us to make an "educated guess" about what content we should create to achieve the desired result (awareness? interest?). Once we start creating content, we can use our predefined key performance indicators (KPIs) to determine whether we achieved the goal with a particular piece of content. If yes, we can create more of what works and continue following that model. If not, we need to iterate and try again.

This "agile content creation" process can be taken to the next level by using data to inform all stages of the content creation cycle, feedback, and iterations.

How data drives resonant content marketing

Let's examine the above content strategy using a data-driven approach:

Step One: Map Your Audience

Mapping your audience using data may vary by industry and goals. But generally, you need to know and collect data on:

Key search engine trends and keywords, i.e., what topics interest the audience in specific geographic locations. A good example in the travel sector could be discovering that Australian customers are searching for "best vacation spots this summer in New York," based on which you can create specialized, targeted content clusters.

Social media sentiment - this involves reviewing groups, influencer profiles, etc., to find out which posts/stories/articles get the most engagement and responses (likes, shares, comments, etc.). For example, an e-commerce company selling kitchenware might discover a chef on social media who posts short cooking videos and popular recipe posts. This data-driven insight can become a starting point for collaborative content creation, helping you reach a new, relevant, and targeted audience.

Step Two: Monitor Competitors

Knowing where your competitors are investing their efforts and how they interact with consumers can be crucial when deciding how to approach a specific audience. You don't want to be "blatant copying" or "passively reacting," but you do want to make more informed, data-driven decisions. Here's a vivid example:

Paid promotion - one of the best ways to track competitors is through their paid advertising. You can gather data on their messaging, imagery, and consumer engagement to understand what works for them without spending time and money on advertising yourself.

For example, a marketing agency promoting a financial analysis and trading platform might notice that its competitors are successfully converting customers by advertising their "financial academy." This could prompt them to seriously invest in building a cross-platform product and promoting educational materials. They might start hosting webinars, recording YouTube videos, writing blogs/eBooks, based on the fact that their competitors managed to attract an audience through self-education. No additional proof of concept (POC) required. Only data.

Step Three: Monitor Interest and Trends

Many platforms have built-in tools for monitoring such phenomena, but alternative data, for instance, can be much more effective for real-time insights. Here's an example:

Consumer reviews and purchase trends - for example, a marketing team promoting a cosmetics brand might choose to collect data on:

• Customer reviews
• Transaction data.

As a result, they might discover a particular interest in eyeshadows that create a very striking effect, and find that women are leaving negative reviews for competitors and are disappointed with the final result their products deliver.

This is a disguised data opportunity: you've just discovered a clear consumer interest in a niche, as well as dissatisfaction with competitors' performance. This can not only inform a content strategy in the form of a video or social media tutorial on how to properly apply eyeshadow, but also help with product line selection, branding decisions, and messaging/creatives for paid ad campaigns.

Step Four: Gather Insights - Skip or Repeat

Whatever data you decide to collect and use to inform your content strategy, you also need access to a data-driven feedback loop. If the data indicates high engagement and desired outcomes (purchase? consideration?), then you can repeat the approach; if not, you can discard that type of content or iterate from a new angle. Here are a few examples of data you can use to evaluate content performance:

• Link data collection - one way to tell if content is gaining traction is to search the web for links to your content (backlinks or shares). You can create a chart and update the number of links across the web to determine which pieces are absolute winners and publish more of that content.
• Content scraping - more often than not, if your content is good, you'll find sentences, paragraphs, and sometimes entire pieces republished on another site or blog. Besides being a great brand protection tool, it's also a good way to see how valuable your "peers" consider the information you provide. The more plagiarism of your content, the better it performs, using schoolyard logic: "average kids only copy from smart kids."
• Web traffic data collection - you can do this for your own blogs and landing pages, as well as competitors' blogs, and compare web traffic as your content strategy evolves to become more agile. The more traffic a page generates over time, the more engaging the content must be, which seems a logical conclusion.

Collect search engine data - this can include data related to your ranking in search results, how your posts rank for specific keywords, and the number of clicks and impressions your posts receive (largely indicative of the quality of the title and metadata, as well as "time on page" and how well your content has been indexed by Google/Bing/Yahoo spiders).

Conclusion

Content strategies still work and are an important component of any marketing strategy, especially when it comes to creating "evergreen" content that will always provide value to the target audience. But in a world where audiences, competition, and algorithms are constantly changing, it is wise to use data for a marketing approach that aligns with what is happening online in real time.