You know that old saying, "You can't improve what you don't measure"? It rings true, especially in the world of content marketing. But here's the kicker: just because you can measure something doesn't automatically mean you're measuring the right thing, or that it's actually helping you improve.
Think about it. We're bombarded with ways to score content – some simple, some incredibly complex. But often, the complexity doesn't translate into usefulness. What we really need are scoring systems that don't just track performance but actually guide us toward creating better content. Because let's be honest, nobody enjoys wading through bad content. High-quality content, the kind that genuinely answers a searcher's questions, is what Google loves and what keeps readers engaged.
Without a solid scoring method, it's like trying to navigate without a map. You might stumble upon something good, but you won't know why it worked or how to replicate it. Relying on gut feelings or just churning out more and more articles isn't a scalable strategy. A well-designed content score acts as a benchmark, a clear target to aim for, helping everyone on the team understand what 'good' looks like and aiming for it from the get-go.
But here's where things get tricky. A good content score isn't just about vanity metrics – you know, the number of likes or retweets that look impressive but don't necessarily predict success. We need scoring methodologies that are predictive, that help us forecast favorable outcomes. The problem is, many scoring processes end up being more about ranking and tracking than predicting.
Imagine using the percentage of visitors who downloaded an asset as part of your content score. A high download rate sounds great, right? But does it tell you if a new piece of content will perform just as well? Not really. The same goes for metrics like raw traffic or bounce rate. These numbers tell you what happened, but they offer zero insight into why it happened or, more importantly, how to improve it.
It’s a bit like the Toronto Blue Jays' win-loss record. Knowing they have 65 wins and 80 losses tells them where they stand, but it doesn't tell them what specific actions they need to take to win more games. In content marketing, we need scoring methods that help us win, that encourage appropriate action. Simply knowing a piece of content is 'good' or 'bad' based on a score isn't enough.
So, what defines a good scoring methodology? It needs to be actionable. While tools like Google Analytics provide valuable data, using raw metrics like traffic as a score doesn't inherently tell you how to improve that specific post. You might know it gets lots of visitors, but understanding why and how to boost that traffic is the real challenge.
Consider the Flesch-Kincaid readability test. It measures how easy a passage is to understand based on word and sentence length. A higher score means it's more readable, which is fantastic for your audience and can lead to better SEO metrics like reduced bounce rates and increased time on page. To improve the score? Simple: shorten sentences and words. But readability is just one piece of the puzzle. There's more to great content than just being easy to read.
Manually scoring content is an option, as I've discussed before, but honestly, the sheer amount of time it takes makes it impractical for most. This is where intelligent solutions come into play.
Content is the lifeblood of a business's relationship with its customers. But when content is off-strategy, off-brand, poorly written, or inconsistent, it can do more harm than good, leading to confusion and frustration. No business wants that.
Fortunately, there's a way to gauge content health before it goes live. This is where AI-powered platforms like Acrolinx shine. They help enterprises align their content with their overall strategy and guidelines. The Acrolinx Score, for instance, is a single number that reflects how well a piece of content adheres to an organization's specific strategy and rules. It moves beyond simple metrics to provide a more holistic view of content quality and its potential impact.
