t's easier than ever to create endless content but how do you know whether what you’re making is any good. Yes, the ultimate test is whether people are engaging with your content but what if there was a way to predict whether what you make will be engaging before you release the content.
That’s where content analytics can come in.
What is content analysis?
To be honest, I’m not even sure if content analytics is actually a thing, a quick google doesn’t seem to come up with much. But anyway, the way I define content analytics is as measuring, reviewing and analysing the stuff you say in the content you make. At the moment this has most often looked like for me as analysing the emotions and sentiment of the words spoken in podcasts and comparing it to similar podcasts. But, in the future, I believe it could go as far as picking up the tone of someone’s voice or even picking up body language and facial expressions, to coach you on how to be more engaging.
How can content analysis be used?
A present example of content analytics is measuring the emotions that come through in the words spoken in a podcast. It can answer questions like:
- Am I using words that are overly fear-based?
- Does my positivity go through a dip in the middle of a podcast?
- Was I lacking in confidence in this episode?
All these questions can be answered by content analytics and it’s a sure-fire way to measure that “oh I was a bit off” that episode felling and see specifically what happened.
Why do I think it’s the new frontier?
It's so easy to get obsessed with numbers that are out of our control. How many likes, downloads, subscriber do I have? But the problem with these figures is that a creator has no direct influence over them. By shifting to analysing the content itself the creator is given a completely download independent view of their performance and empowered to course-correct well before downloads start coming in.
It's like in traditional media where you have producers or directors whose sole job is to look at your performance and give you advice. Today most creators are the whole end to end media company from producer to performer, all the way to editor and while on the one hand, this results in authentic content, there is also the chance to get overwhelmed and lose direction. This is where content analysis comes in and can take the load off the already overworked content creator by giving them actionable steps to improve their content.
Sounds great but how do I do this?
Like I said earlier a quick Google doesn’t come up with much. The closest thing I could find for a consumer was Grammarly which gives you a basic idea of the tone of your written content.
Beyond that I see 3 clear options for content analysis:
Hire a producer or director to help you create your content
- This is how it has been done since the dawn of performance
Wait for your audience feedback
- Probably the most accurate, but you first need an audience and then you have to bug them to help you out
Use AI to analyse your content
- The advances in AI mean that it can do the hard yards of looking through your content and provide objective insights into your performance
AI enables Content Analysis for the masses
With all the major tech companies opening up their AI products to people like you and me the possibilities are endless in what you can use them for and I think one of the biggest uses is Content Analysis. The problem is you need to know how to code to use these AI products in any meaningful way.
That why I’ve been working on WhalePod AI to enable everyday content creators (podcasters at the moment) to be able to analyse what they say in their content and see where they can become more engaging. Like I said I think this is the next step for content creators and I really think creators of all sizes should be measuring their performance more on the quality of their content rather than the size of their downloads.
I’d love to chat about this more, so please reach out below!