Tiff asks, "At what reading level should website copy be written? Is it the same as print?"
The answer to this question depends on two things: your audience, and what readability score you're using. There are 5 major readability scores:
- Flesch-Kincaid grade level - words/sentences - syllables/words
- Gunning-Fog index - words/sentences - complex words (3 syl)/words
- SMOG index - complex words / number of sentences (minimum 30 sentences)
- Automated Readability index - characters/words + words/sentences
- Coleman-Liau index - character-based, letters / 100 words - sentences / 100 words
Most tools use FK, but FK isn't always the best choice - often, for marketing copy, SMOG is a better choice, or Gunning-Fog if your software supports it.
The secret is this: measure the media diet of your audience and determine it from that grade level. Watch the video for an explanation of how.
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What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for watching the video.
In today's episode tip asks, at what reading level should website copy be written? Is it the same as print? So the answer to this question is dependent on two things.
The first is, what readability tool are using, what measure are you using? And second, what audience reading level do you have? What does your audience read at? So there's a bunch of different ways to tackle this.
Let's talk about the algorithms.
First, there's five major algorithms for readability.
There is the flesh Kincaid grade level algorithm, which is essentially the number of words divided by the number of sentences minus the number of syllables in the words divided by the number of words.
All these algorithms by the way are done in software.
You don't have to implement any of them yourself, but you do need to know which algorithm your software is using a lot of the time.
software will not necessarily tell you up front, you may have to ask the developers, but you're going to get different answers depending on the on the algorithms been used.
And different algorithms are appropriate for different use cases.
Second is the Gunning-Fog index.
This is a words divided by sentences minus complex words, which are three syllables or more divided by the number of words.
Gunning-Fog was intended for things like health care, and the same for the following measure.
Because you're looking for it, trying to reduce the number of complex words, to make something more readable.
The next one is called smog.
And this is a simple measure of gobbledygook, which is a simplification gutting fog.
It is simply the number of complex words divided by the number of sentences with a minimum of 30 sentences.
And there's actually a bunch of tuning parameters that go into each of these but again, the software you're using, done that I'm just giving you the basic idea behind each of these algorithms.
The fourth is the automated, readable to index, this is the number of characters divided by the number of words, plus the number of words divided by the number of sentences.
And the last one is the Coleman-Liau index, which is character based.
And that is the number of letters divided by the number of letters per 100.
Words, minus the number of sentences are 100 words Coleman-Liau was invented for machines, essentially machines, reading scanning of these different measures, the one that folks tend to use a lot in when they're developing tools is the flesh Kincaid grade level score.
But it's not necessarily the best choice.
And the reason for that is that if you're trying to reduce word, complexity of reading, it's those big polysyllabic words, those overly complicated words, long syllable words that can sometimes mess up reading level and with that, Gunning-Fog or smog are probably the two indexes that are the better choices for reducing the complexity of something that you're trying to read.
smog is used a lot in healthcare Gunning-Fog was used.
It was built for the US Navy, to, to reduce the complexity of technical manuals to the field manuals that soldiers are given is to make it easier for them to use.
So both of those indexes are good for marketing content because good marketers like to be fancy, right and use big words and stuff to make their their copy sound more sophisticated, especially b2b marketers.
We all love our flexible, scalable turnkey inter integrated solutions, etc.
As opposed to software that does the thing and that those complex polysyllabic words are the ones that make readability more difficult so for marketers Gunning-Fog and smug are probably the the two algorithms to use.
So you'll want to check which what algorithm your software uses.
Now, how do you determine your audience? There's a couple different ways you can do this.
Number one, if you have access to like your customer service inbox, or reviews written by your audience and things like that, you can copy and paste a whole bunch of them together and get an overall average readability level of the way that your audience writes.
The other way is to use social media monitoring software.
If you have a list of known customers, for example, like a Twitter list, you would put that into social media monitoring software, and then extract out from that data, the publications that your audience shares the most.
Go on to the Ito's publications take a sample random sample like 10 articles from those publications.
Put that through your readability software and that will tell you like your audience is consuming and sharing content at say a sixth grade level or an eighth grade level.
That way you can dial in on exactly where your audience is based on the stuff that they're already sharing.
If your audience isn't active on social, then you're gonna have to, you know, solicit content from other places.
A good way of doing that, again, is asking people in on intake forms or on customer service calls or in surveys.
You know, hey, what publications do you read? What newspapers or news sources do you read? What books do you read, that will help you again, dial in and calibrate on where your audience's reading level is based on their media diet.
Once you've got that, then you can start making content that's appropriate to the grade level that people are at.
The other thing that you're going to want to do is you're going to want to measure carefully.
readability is is a metric it is not necessarily an outcome.
So one of the things to do is to look at you run a, an attribution analysis at at the page level, across your web copy and look for the pages that convert the most.
And then measure the readability scores, and then do just a simple regression analysis to see Is there any relationship between readability and conversion capability? There may be there may not be if you run that analysis, and there's no correlation, then is readability a problem? It wouldn't hurt to dial things into where your audience is most comfortable.
But if you find that say, your top converting page is written at a substantially different grade level than the like your least converting page and there's no logical relationship between the two then don't invest a huge amount of time in changing the readability the rest of your site.
The thing to do is would be to set up a a have actual experiment like a clinical trial, take 10 pages of no take 20 pages, 10 of them have a gonna be ones you're gonna modify the reading level 10 of them mean, you're not going to modify the reading level, they should all be roughly about the same level of conversion power within your analysis.
And then once you've made the changes, observe and see if the conversion power changes over time.
Because you have you made those readability changes, don't change anything else.
Just make sure it's, it's, you know, 10 and 10.
each one's a control one's the experiment and see if readability changes make a difference.
If they make a difference.
Great, then, you know, even after a couple of weeks, right, that readability is actually important to audience.
If nothing happens, you probably don't need to spend a whole lot more time on it, but I would run that test.
So your steps are First, identify the media diet, choose the algorithm that you're going to use, then assess your site, look for that relationship and if there is relationship of some kind, then set up a test and and test and approve 10 pages and leave 10 pages alone and see how they interact.
readability is is part of natural language processing.
There's a lot of fun things you can do with it but that's for another time.
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