How to Improve Content Marketing with IQR: Part 3

How do you know whether your content game is getting better or worse? It’s easy to rely on stock analytics tools, and for the beginning content marketer, tools such as Google Analytics are more than enough. For the veteran marketer who is creating content, how can we know with greater precision whether our content is getting better or worse? How can we more quickly diagnose the bad, double down on the good, and make our program sing?

In part 3 in this series, we begin to extract more meaning from the data we’ve collected in part 1 and charted in part 2. Be sure you’ve read and done the steps in those early parts first.

Let’s now consolidate the graphs of the good stuff and the bad stuff into one picture, so as to see everything more comprehensively. I’ll reapply the trend lines as well:

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We can see that both trendiness are going up. Let’s start with that basic form of analysis and examine some different combinations and what they could mean.

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Above, there are a total of 9 scenarios you might see in your trendlines. Let’s explore what they are and what they might mean. I’ll remind you from yesterday that good stuff refers to the best 25% of your content, the most popular content. Bad stuff refers to the lowest 25% of your content, the least performing content.

Scenarios 1-3: Content Marketing working well

[1]: Good stuff ascending faster than bad stuff. This is the best possible situation. All your content is improving, but your headliners, your big content, is punching above its weight. Keep doing what you’re doing, and double down on your best ideas.

[2]: Good stuff ascending at the same rate as bad stuff. This is a sign of an overall strong content marketing program, steady improvement across the board. The next important thing would be to develop some big ideas and amplify the great hits you’ve already got.

[3]: Good stuff ascending slower than bad stuff. Your least performing content is making strides to become better. Now’s the time to start dreaming up some big ideas to take your best stuff to the next level.

Scenarios 4-6: Content Marketing might be in trouble

[4]: Good stuff ascending while bad stuff descends. You still have great hero content, but your maintenance content is suffering. Either you’ve tapped out your audience or your content simply isn’t of interest most of the time. Find someone to do a better job with the topics and content formats you’re not good at.

[5]: Good stuff and bad stuff remain neutral. Your content marketing is working okay, but not improving. This is a sign that you need a jolt of creativity and different thinking.

[6]: Good stuff descending while bad stuff ascends. Often, this is a sign that you’ve spent so much time shoring up your weak areas that you’ve let the important areas go. Get your big ideas back on track.

Scenarios 7-9: Content Marketing definitely in trouble

[7]: Good stuff descending slower than bad stuff. Both areas are declining, but your top content still holds some influence. Use it to reboot your program. Do thorough analysis and throw overboard the types of content, ideas, and topics that are least performing.

[8]: Good stuff descending at the same rate as bad stuff. This is general bad news. You’re headed for the bottom. This is when you reboot everything.

[9]: Good stuff descending faster than bad stuff. This is the worst possible situation. Your best content is losing ground rapidly, and whatever traction your bad content has is probably so small that the rate of decline is meaningless, bottoming out.

If we take the chart from earlier and compress the axes down to just the ranges where the trendlines are, we can see which scenario is at work in my own data.

Screenshot_7_2_15__7_25_AM.jpg

What we see above is scenario 2. I now know what I need to do in order to move my content marketing program ahead.

In the next post in this series, we’ll look at measuring the distance between your good and bad stuff, and how to interpret that measurement.


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How to Improve Content Marketing with IQR: Part 2

How do you know whether your content game is getting better or worse? It’s easy to rely on stock analytics tools, and for the beginning content marketer, tools such as Google Analytics are more than enough. For the veteran marketer who is creating content, how can we know with greater precision whether our content is getting better or worse? How can we more quickly diagnose the bad, double down on the good, and make our program sing?

In part 2 in this series, we start to dig into the data we’ve collected and identify early opportunities. If you haven’t read part 1 to get your data, go and do it first.

We left off with all of our data in columns. Let’s tackle the bad news. How bad is the bad? Because this is social media data, I’ll prune out replies, leaving only the content I want to share. Once I’ve correctly sorted and cleaned my data, I’m ready to analyze.

Take the bad stuff column and chart a simple line graph. Depending on how much data you have, this may be a taller order than it sounds. Below, I’ve taken the bad stuff – my lowest quartile – and charted it out:

Screenshot_7_1_15__5_59_AM.jpg

This is tough to interpret, so let’s right click and add a trendline:

Screenshot_7_1_15__6_01_AM.jpg

In general, we can see that the worst of my posts, the posts that got the least amount of exposure, have still been on the rise. If we zoom in a bit, we can see that the trend in the lowest quartile has gone from about 1,800 impressions to a little over 2,200 over the span of 6 months:

Screenshot_7_1_15__6_07_AM.jpg

This is a solid improvement in the least well-performing content. The next step for me would be to go back over the data and identify when things changed. Was the improvement consistent over the same period of time?

What about my best stuff? How’s the boundary between good to great? Let’s repeat the same process, from making a chart to applying a trendline:

Screenshot_7_1_15__6_21_AM.jpg

We see improvement… but look carefully. The improvement from beginning to end in this six month timespan is shallower than we saw in the bad stuff. This tells me that the best stuff resonated more, but didn’t grow as fast as the bad stuff.

So, we know what the good stuff did. We know what the bad stuff did. Is there a relationship between the two? Is there some insight we can glean from both of them together? Stay tuned; tomorrow, we’ll look at the difference between good stuff and bad stuff, and how to interpret it.


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How to Improve Content Marketing with IQR: Part 1

How do you know whether your content game is getting better or worse? It’s easy to rely on stock analytics tools, and for the beginning content marketer, tools such as Google Analytics are more than enough. For the veteran marketer who is creating content, how can we know with greater precision whether our content is getting better or worse? How can we more quickly diagnose the bad, double down on the good, and make our program sing?

Today begins the start of a new series on an advanced measurement technique that will help you to understand your content marketing efforts better. To embark on this journey, you’ll need up to a year’s worth of data (at least 90 days), a spreadsheet, and an understanding of how to use your spreadsheet’s quartile and box/whisker tools.

What we’re going to do is break any given content marketing metric into four buckets, into quartiles. The lowest quartile bucket will be the really underperforming content. The middle two quartile buckets will be the average content. The upper quartile bucket will be the outperforming content, the good stuff. By segmenting our content into four buckets of bad, average, and good, we can better understand how good the good is and how bad the bad is. What we’ll be computing is called the interquartile range (IQR), the difference between the good stuff and the bad stuff.

Start by downloading and formatting your data so it’s in an orderly series, chronologically ordered. Here, I’ll use social sharing of posts from a Facebook Page, but you can use any sequential data: Google Analytics, Twitter, CRM, etc.

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You’ll next create 3 columns: bad stuff, good stuff, and IQR:

Screenshot_6_30_15__7_22_AM.jpg

Next, in the 31st row in the bad stuff column, insert the following formula:

=QUARTILE(E2:E31,1)

This formula says to give the value, the boundary of the first quartile, which 25% of the cells in column E can be found; put another way, only 25% of the values in column E will be below the number that appears in the bad stuff cell. This is our bad stuff number, the number at which a quarter of posts fall below. These are posts that were shared less than the other 75% of posts.

In the 31st row in the good stuff column, insert the following formula:

=QUARTILE(E2:E31,3)

This formula is the good stuff. 75% of content falls below this number, so it’s a good way to measure how much content forms the majority of your average to poor content. Anything above this number is going to be great content.

Now, we compute what’s called the interquartile range, or IQR. This is the difference, the spread, between the upper 75% that signifies great stuff and the lower 25% that signifies bad stuff. In the cell adjacent to the good stuff, subtract the bad stuff from the good stuff:

Screenshot_6_30_15__7_35_AM.jpg

This number is the interquartile range.

Drag all three columns down to the end of your data set (or double click on the little lower right hand blue square to auto-fill the columns):

Screenshot_6_30_15__7_40_AM.jpg

You’ve now got the data all set up. In the next post in this series, we’ll start digging into how to interpret it and turn it from data into analysis. Stay tuned!


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