Measuring content performance with content/audience fit

Content is queen. It’s a crucial asset for any startup trying to build traction without an epic marketing budget. Before you get people to sign up for your waitlist or try your public beta, you must communicate what your product does, what makes it unique, and your grand vision to change the world.

Well-written content helps you nail your product positioning, convince people you’re building something worthy of their attention, and build early traction.

For a growth-stage startup, content becomes an invaluable asset for driving organic traffic and boosting product-led growth. Testimonials, case studies, user-generated reviews, and detailed documentation can help turn website visitors into paying customers.

With the emergence of AI-powered tools like ChatGPT and Midjourney, marketers and founders can create content at scale. You could create a hundred blog posts per day, but it wouldn’t make much sense if the content doesn’t resonate with your audience and help you reach your marketing goals.

This is why you must understand if your content hits the right notes with the right people.

The sweet spot where content meets your audience

Many startups fail because they fail to reach product/market fit. PMF basically tells whether you have something people love to use, i.e., the product solves a real problem and satisfies the market. Marc Andreessen says it’s the only thing that matters for a startup.

Content/audience fit is very similar. It signals how your target audience feels about your content.

Before you hit product/market fit or even have something people can use or try, you need some early traction signals. Content/audience fit helps you identify those signals.

If your content isn’t engaging site visitors or not driving them to take action, you either have:

  1. poor content that doesn’t resonate with your audience
  2. the wrong audience.

For example, talking about Javascript frameworks to marketers might be a poor fit, even though some marketers want to get their hands dirty with code.

Or, you could have a sizing issue. Suppose your ideal customer works in a small or medium-sized company. In that case, selling your idea or vision to an enterprise company with a more complex infrastructure is challenging.

Or, you may be targeting people who don’t care about your cool product or vision. It happens. For example, data scientists who feel religious about Google Analytics are not our ideal customers. We’re building a simple, privacy-friendly web analytics tool with insights on autopilot. Deep customization and data visualization with BigQuery is not our thing.

The sweet spot, where content meets the audience, boils down to three things:

  1. The problem. What is the specific problem you’re trying to solve? What keeps your ideal customer awake at night?
  2. The value. How does your product solve the problem and make your ideal customer’s life easier?
  3. The message. What is the best tone and format to deliver the message? Do you have a story to tell?

Where to look – engagement vs. conversions

The key to measuring content/audience fit is not what but where.

When marketers think about performance, they often think about conversions, which can strongly signal that you have something people want.

But the problem, especially for early-stage startups, is that you might not have that many conversions. You don’t even have a business yet. You only have a vision and a story.

I love this quote from Sean Ellis:

The mistake that many marketers make is that they are optimizing for short term conversions. They think it’s all about maximizing clicks and signups. But if the product isn’t truly great a delivering on the promise, then you will likely lose these people anyway. It is better to convert fewer people with a promise that reflects why the product is truly a must have. These people will not only stick around, but they will also become the customer advocates that boost your organic growth rates.

This is why, to understand content/audience fit, you can’t just stare at conversions. You have to start at the top-of-funnel when visitors express their interest, and you get instant user feedback on how they feel about your content.

AIDA funnel image

The problem with bottom-of-funnel metrics is that there are always two events: the moment the visitors consume your content and the conversion event.

When random website visitors get goosebumps after reading your product vision, it might take days, weeks, or even months before they convert, for example, to sign up for a product trial.

These two events have a massive distance between them, making them disproportionate.

To understand whether your content resonates with people, it makes sense to use metrics closer to the moment they became interested in your content. Or, didn’t think much of it, which is a signal you either have poor content or the wrong audience.

The good thing with top-of-funnel metrics is that you get relevant results much faster.

For example, a thousand visitors reading your product manifest already give you actionable engagement data on your content. You get results in days and can start optimizing your content immediately.

If you were to focus on bottom-of-funnel metrics, you’d have to wait much longer. Only a handful might convert from a thousand visitors, which is insufficient to make business decisions.

Measuring content/audience fit

Volument introduces a content funnel, which helps you discover how site visitors engage with your content before they take action.

Top-of-funnel metrics

Visitors tell you the number of visitors who saw your content.

Stay rate tells you how many percent of visitors spent more than three seconds on your website. If people leave a page in three seconds, that usually indicates a poor user experience.

Engage rate tells you how many percent of visitors spend more than fifteen seconds or more on your website. If people leave in fifteen seconds, the content is not engaging.

Bottom-of-funnel metrics

Actions are user interactions on your website. Action rate shows the percentage of how many visitors took action.

Volument tracks some events automatically, but you can add custom events and track interactions such as playing a video, clicking on an element, etc. Learn more about automatic event tracking.

Conversions are desired user interactions – filling out a form, signing up for a newsletter, making a purchase – with a more immediate business impact than actions. Conversion rate shows the percentage of how many visitors converted.

We can look at pages, or any other dimension, with these metrics and identify your best-performing content and biggest bottlenecks:

  • pages with a great/poor first impression
  • most/least engaging content
  • most/least converting content

Volument also gives you a score for content/audience fit, essentially a site-wide engagement rate. The cool thing is that we can set a baseline and compare your engagement with all the sites we measure so you get a good idea of where you are.

The end of bounce rates

For a long time, marketers and founders have been staring at bounce rates to understand visitor engagement. But it’s a profoundly flawed metric, which is easy to interpret in any way you want.

It is the percentage of visitors who enter your website and leave without taking any subsequent actions.

A high bounce rate is commonly equated with bad user experience or irrelevant content. A high bounce rate could also indicate site performance issues.

A low bounce rate, on the other hand, signals a positive user experience and indicates kick-ass content.

But it’s not that simple.

A visitor might spend minutes enjoying your content, but if they click the back button, it only adds up to your bounce rate. This means that bounce rate puts a visitor spending two seconds and a visitor spending four minutes into the same basket if they only view a single page.

Maybe this is why Google has also ditched bounce rates in GA4.

One response

  1. […] Again, if your primary purpose for collecting data is to understand how to make your website more relevant for visitors, you only need to find out if they like your content. You can use a simple metric for this: engage rate. […]

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