INBOX INSIGHTS, August 24, 2022: Vague Content, PPC Ad Performance, Market Research

INBOX INSIGHTS: Vague Content, PPC Ad Performance, Market Research (8/24) :: View in browser

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Vague, Unfocused, Pointless Content

What do you do when your content is vague, unfocused, and has no point?

Excellent question – this is the problem I find myself having at the moment. I’ve been working on this week’s newsletter and to be honest, what I wrote is terrible. I won’t subject you to it.

It was mostly disconnected thought with no point. Unfortunately, a lot of content ends up like this (not just mine!) I have lost count of how many times I’ve read a post or an article that has no real point (I’m looking at you, thought leadership pieces).

How do we fix this?

I’ll be honest with you. I’m coming up short this week on solutions but the problems are glaringly obvious to me. Eventually, I will have to face my other post and rewrite the heck out of it to make it useful.

In the meantime, I’ll leave you with some thoughts from our free Slack group, Analytics for Marketers.

I recently asked them what their current pain points are. Here are some of the responses:

“GA4. Everything about it is a challenge”

“Gaps in data and a long pathway from lead to enrolled student”

“Talent. We need more hands on deck…to execute the strategic opportunities in front of us”

What struck me most is that these are common issues. I see and hear about a lot of teams that are struggling with similar issues.

So where are the solutions if these issues are so common?

I see I’m coming back to the same question as I had earlier, “how do we fix this?”

The content I was working on earlier was some vague thing about how a lot of our problems aren’t technology problems. The problem starts with people. That is what you need to fix first.

The first pain point – GA4 (Google Analytics 4) – that’s a people problem. Not that the people using the system are the problem, but that the people who designed it and rolled it out are the problem. GA4 was rolled out suddenly and then slowly in disconnected pieces. Had there been better communication around the whole experience, marketers may not be so frustrated.

The second pain point – gaps in the data – that’s also a people problem. Sure, there are technologies that could start to fix this but first, there needs to be a process around how this data is collected. The technology that you put on top of the problem won’t work correctly without a process. To create the process, you need people to decide what it’s going to be.

The last pain point – talent – is, you guessed it, a people problem. The person that mentioned this point is working with a staffing agency as the solution.

So what’s the point here? The point is that most, if not all, problems start with people. Whether there is a lack of clarity on what they want to do, whether you don’t have enough of them, or perhaps it’s just the wrong fit all around. People dictate the process. The process dictates the platform. Not the other way around. Oh, and people create technology. So if it’s not working, start with who made it.

My problem is 100% a people problem – me. I can’t get my head around the concept I was trying to write about. I’ll get back to it though and keep trying to work it out. Stay tuned for that piece.

In the meantime, join our free Slack group, Analytics for Marketers, and come tell me about the “people” problems in your company. .

– Katie Robbert, CEO

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Binge Watch and Listen

In this week’s In-Ear Insights, Katie and Chris discuss market research capabilities. What kinds of resources should an organization allocate towards market research? How often should you be doing market research? What are the different kinds of market research? These questions and many more answered – tune in to find out!

Watch/listen to this episode of In-Ear Insights here »

Last week on So What? The Marketing Analytics and Insights Live show, we looked at how to use economic indicator data to inform your marketing decisions. Catch the replay here »

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Data Diaries: Interesting Data We Found

In this week’s Data Diaries, let’s look at some ad data. One of the questions we’re always asking ourselves as marketers is whether or not there are ways to improve the efficiency of our ads. What could we do to get more results while spending less?

First, as we do with all data, we look to see what data we’re able to get. Using the SEO/SEM tool SpyFu for a series of keywords around marketing, we get the following data for 14,435 search engine ads:

Basic SpyFu data

There isn’t a ton of data here, but that’s okay for now. What we do have is an objective – placement in ad position on the page. The closer to 1 that number is, the closer it is to the top ad placement spot. That’s what we want – our ad to be at the top of the chart.

We also have a few other variables, some of which are helpful, and some of which are not. We have, for example, the domain of the competing advertisers, such as amazon.com and other companies. We have the number of keywords an ad is running against. We have the budget being spent on the ad. And we have the ad text itself.

This is a case where we don’t have a lot of other information. However, we can engineer additional data from the information we have. What kinds of data could we engineer from it? We could look at the length of the ad copy – headline and body. That could be useful. We could even engineer the different parts of speech from the ads to see if ads with more verbs do better, for example.

When we do a machine learning-powered regression analysis against the ads, what do we find of our newly-engineered features?

SpyFu XGBoost analysis

What we see here is a clear indication that the ad copy length – title and body – has influence on how the ad’s position works. However, one of the challenges of this particular type of regression is that it doesn’t tell us about the polarity. For that, we need a more nuanced analysis:

SpyFu Spearman correlation

What we see here is a negative correlation between ad copy length and position. This is fascinating; the longer the ad is, the better its position. Bear in mind that position is an inverse correlation – position 1 is better than position 10. If shorter copy were more effective, then you would see a positive correlation between length and position, because as length increased, position would increase (bad).

What else does this tell us? It tells us what isn’t a factor – and a huge surprise to us is that budget, ad spend, is not the biggest driving variable of position. This is consistent with what search engine marketing companies like Google and Bing have said publicly – just because you spend more doesn’t necessarily mean you’ll do better. It’s still a factor, but it’s not the deciding factor.

What’s our next step? If you’re running search engine ads, perform this style of analysis on the ads you’re running and all your competitors’ ads. You’ll gain some insights about what’s really working for your industry or niche, and know what to tweak in terms of ad optimization next.

Trust Insights In Action

Weekly Wrapup

This is a roundup of the best content you and others have written and shared in the last week.

SEO, Google, and Paid Media

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Content Marketing

Data Science and AI

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