content-pattern-optimization

Blogging is considered a well-established, highly effective form of marketing. We’ve moved beyond the experimentation and exploration phase. On the eve of 2020, blogging is regarded as a top marketing technique.

To illustrate this point, let’s take a look at some stats from the latest Hubspot reports on content marketing:

  • Marketers who prioritize blogging efforts are 13x more likely to see positive ROI.
  • 81% of B2B companies use blogging as a content marketing tactic.
  • Content marketing gets three times more leads than paid search advertising.

Given these figures, it should be no surprise that content marketing is set to be a >$400B industry by 2021.

Creating high quality, engaging content consistently builds trust and rapport, provides education and ultimately converts customers at higher rates than, say, pay-per-click ads aimed at cold audiences.

But content marketing is expensive. High caliber writers command high rates, content distribution can add up quickly and managing large content efforts takes (ideally) a dedicated in-house team. It’s expensive because, if done right, the payout is huge.

If done right is the key phrase. Content marketing is currently in an adolescent phase; it’s well-established as an effective marketing strategy, but no rigorous systems that can quantitatively measure its success are available.

In an effort to optimize content, most seasoned content marketers pull stats from Google Analytics and attempt to draw connections between their content and user behavior. The problem is that these stats describe user behavior but they don’t explain the why behind user behavior.

We can do better. We are in the optimization era of the web. We have Search Engine Optimization (SEO) for traffic and we have Conversion Rate Optimization (CRO) for funnels. But, when it comes to content – arguably our greatest marketing tool – we still don’t have a reliable system for optimization. We throw around phrases like “create engaging content,” or “find out what people want to read.” But these are not easy asks, and in the absence of validated tools or systems, marketers have no choice but to eyeball superficial, non-content specific stats and then guess why users interact with content in the way that they do.

My team and I are creating a system and a tool to address this problem. The system is called Content Pattern Optimization or CPO, and the tool is called Writtio. Here, I’ll only discuss CPO as a system.

Content Pattern Optimization

Content Pattern Optimization, or CPO, is a system that identifies how content patterns affect user engagement and conversions.

But before we dive into CPO, it’s important to make one thing clear: content marketing is still a long-term strategy. Blog posts aren’t designed to be an immediate converter; they are meant to be a relationship builder. Long term success, however, depends on hitting some very important short-term metrics.

For example, a long-term goal of content marketing may be to build brand credibility. Building that credibility (which then leads to conversions) can only happen if the very first article a visitor engages with inspires trust.

How do you know if the article inspires trust? You can tell by taking a peek at the short-term metrics. If, for example, visitors take an action within the article or if they read another article shortly after reading the first one, then they’re probably interested and you’re on your way to building trust.

On the other hand, if a visitor lands on your article, and within seconds leaves your domain altogether, then you didn’t hit that short-term metric (inspire their trust) without which you cannot reach the longer-term goal of conversion.

By identifying how content patterns affect user engagement, CPO can bring you one step closer to fulfilling your conversion goals and building successful long-lasting relationships with your visitors.

What Patterns are we Optimizing?

Writing, like design, can be optimized.

To optimize something, you have to be able to measure it. There are quite a few parameters in writing we can measure. Some are straight-forward, like the density of adjectives. Some are more complicated like readability or rhythm.

Different types of writing fall within different ranges of optimization. For example, the readability score of an academic journal article might be optimal in the 25-35 range, whereas a blog post aimed at the general public with the same readability score would perform terribly.

Similarly, the audience of a science magazine blog might tolerate a much lower readability score than, say, a fashion blog. The intended audience matters.

For example, with CPO, you can ask the question: Does my rhythm affect whether or not people read a second post in my blog? If the answer is yes, you can then ask: What is the optimal rhythm index for my readers?

What should you optimize for?

It’s difficult (but possible) to measure long-term relationships, but short-term actions that predict long term relationships are measurable through behavior tracking.

CPO tracks visitor behavior in two major categories: engagement and conversions.

Engagements

Engagement refers to how a visitor interacts with your posts and includes metrics such as social shares and likes, scroll length, time spent on post, and comments.

You can combine all of these metrics to come up with an engagement index for a post. The engagement index will allow you to identify how your posts perform in relation to each other. This way, you’re not pitting yourself against large publications with endless distribution resources, but rather pitting one of your posts against another one of your posts, which is a more relevant measure of what resonates with your audience.

Conversions

Conversion refers to the immediate actions visitors take during or after interacting with your posts. This includes things like clicks on target links, completion of a call-to-action, navigation to a target page, and other target actions.

Like engagements, creating a conversion index will allow you to measure your conversions against your other posts performance. In addition to creating a conversion index, you can also set conversion goals (eg, visitor navigates to pricing page) so that you can relate all writing patterns and engagement index to that one conversion goal and tweak each metric’s dial to optimize for that goal specifically.

Here’s an example of optimizing content patterns to achieve higher conversions:

Conversion goal: to get a visitor to opt-in at the end of a blog post.

(1) You find that visitors who engage with your posts at an engagement index of 75 or higher are 2x more likely to opt-in.

(2) You identify that the main driver of that high engagement index is scroll length (which makes sense because if people aren’t getting to the end of your post, they’re not even seeing your call-to-action).

(3) You identify paragraph length and rhythm as the main determinants of scroll length.

(4) You discover that paragraph lengths smaller than 3.2 and a rhythm index of 1 – 1.4 are the optimal ranges for your audience.

(5) You can now use this data to optimize your posts. You make sure your paragraphs are smaller than 3.2 and ensure that your rhythm metric falls within the ideal range of 1-1.4. By optimizing the content parameters that matter (those that actually affect user behavior), you successfully increase your engagement index and ultimately fulfill your conversion goal.

A couple things to keep in mind

Long-term system

When using any optimization system, you have to keep in mind that the results of optimization emerge over a period of time. You won’t see the results within days, possibly not within weeks. This is true for SEO and CRO as well. But I would venture to say it’s even more true for CPO.

Just as with CRO, CPO will require a large enough data set (ie, enough users, enough actions) to make accurate predictions. Larger blogs can iterate faster as they gather data quickly, but smaller blogs may take a while to see results.

Optimization is dynamic

The beauty of optimization is that it’s never really done. An optimization that increases your conversions by 6% may be just the first step to optimizing further and getting to +12%.

Further, especially with CPO, your audience may be segmented. An audience that lands on your posts from a Facebook ad may respond to different patterns than audiences that land on your post organically from a search engine. These differences will need to be taken into account to further optimize.

Conclusion

CPO is a brand new system for optimizing written content, one that is missing from the current world of content marketing. While content marketing is a long-term strategy, there are immediate signals we can measure that predict long-term success. CPO is a system for relating writing patterns to those signals so that we can get to the core of what turns a blog visitor into a paying customer and double down our efforts where it matters most.

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