INBOX INSIGHTS, August 18, 2021: Prioritization, GA4 Attribution, News Headlines

INBOX INSIGHTS: Prioritization, GA4 Attribution, News Headlines (8/18)

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How Do You Prioritize Yourself?

I have a giant pile of work that I need to do. It feels like an unclimbable mountain. It’s the type of situation where feel the need to put on a hat to keep my brain from spilling out from the top of my head.

This morning, I prioritized a Peloton ride with a friend who was celebrating some milestones (happy birthday CM!). Then I took my dog for a walk, and (poorly) sang some Fall Out Boy at the top of my lungs.

What about all the work I need to do? It was still waiting for me. Is this irresponsible of me? Not at all. Before I decided to procrastinate (and yes, it’s a choice) I weighed out all my options.

Setting priorities is a series of trade-offs with a dash of risk assessment thrown in. In this case, I made the choice to push off my work until a little bit later in the day to enjoy the morning. The trade-off? I’ll have to work later into the evening than I usually do. The risk? Low to medium. Low – because the time-sensitive items are well underway and the larger items are not due until later in the week. Medium – because know that tasks for Trust Insights get pushed farther down the list in favor of client work. Can I live with this? For now, I can.

We all operate this way whether we realize it not. We make choices around what is important and what isn’t. In this case, I’ve decided that working on my business isn’t as important as other things this week.

Let’s put this in the context of annual planning. When we sit down to think about the year ahead one of the first questions we tend to ask is “what are the priorities?” What we’re asking is what is going to get done and what isn’t? In an ideal world, we could do all the things. In a more realistic one, we have to make some choices.

How do you decide what’s going to get done and what isn’t? One way is to think about the business impact. This could be revenue, growth, or reputation. Take each tactic and map it to business impact. The farther away it is from having a direct impact the less of a priority it likely is. It’s sort of like playing six degrees of Kevin Bacon. For what it’s worth, I’m two degrees away.

Another metric to consider is effort. When I worked with software developers we would break things down first by t-shirt sizes (XL, L, M, S). This helped put context around the task. From there we would break it down father into trackable milestones. The larger the effort, the more difficult it was to break it down into small, measurable pieces.

The third metric is resources. Do you have the team and budget to execute these tasks? Do you need to hire or bring in an outside company? Do you need to bring in a certain amount of money before you have the funds to start working?

Lastly, ask yourself, “what happens if I don’t do this thing?” This will help you assess the risk. Will people lose their jobs? Will customers be unhappy? Will nobody even notice?

When you put all this information together, you should have a good idea of what’s important. Your list should is now comprised of what is getting done now and what can wait. The caveat is that as you get new information, priorities can change. What was important yesterday might be long forgotten by tomorrow.

How do you prioritize yourself? Drop into our free Slack group and let me know!

– Katie Robbert, CEO

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Data Diaries - Interesting Data We Found

In this week’s Data Diaries, let’s look at an application of natural language processing (NLP) that we didn’t have time for on last week’s So What? episode. One of the challenges of things like subject line testing in email marketing is that we often don’t have enough data to do substantial statistical analysis about what works and what doesn’t. By the time you have enough data, several years have gone by (especially if you send only monthly or less frequently).

So how do we determine what might be appealing in a subject line? We turn to content headlines – specifically page titles of well-trafficked and highly-visible pages. As an example, let’s take the topic of “marketing automation”. We’ll extract about 10,000 headlines and the associated traffic for those pages and score them by how many referring domain inbound links they get, how much traffic they get, and how much social media interaction they get. A headline that scores well across all three measures is probably something that has broad appeal.

One of the challenges of headline analysis is that they’re not very long, so traditional NLP techniques may not apply, such as removing stopwords (a, and, the, etc.). These might play a real role in what causes a piece of content to do well. We also want to look at phrases more than individual words, to see if there are specific phrases that do well.

Results of marketing automation headlines click/tap on the image for a full-size version

The algorithm used in this particular analysis is SVM, support vector machines. In layman’s terms, it tries to separate out good from bad in a dataset and then identify what factors contribute to the good/bad split – ideal for understanding the words and phrases in headlines. Above, we see that phrases such as:

  • The top x
  • Best practices with
  • What it is
  • State of the
  • Why do you

Scored very highly for overall content engagement, while phrases like:

  • How to make
  • VP of marketing
  • Can make your
  • On social media
  • How to generate

Scored very poorly.

A warning: don’t assume these phrases hold true for any topic other than marketing automation!

What do we do with this information? If you’re creating content around marketing automation, test these exact phrases! See what does well and what does poorly. If you’re creating content on a different topic, use this overall methodology plus the SEO/data tool of your choice to extract and analyze the data for the topic of your choice, and then get testing!

Shameless plug, if you just want someone to do it for you, contact us. We’re happy to help.

Methodology: Trust Insights extracted 11,458 unique content posts on the topic of marketing automation from AHREFS Content Explorer, limited to the English language, working links, with explicit content and duplicates filtered out. The timeframe of the data is January 1, 2018 – August 8, 2021. The date of study is August 17, 2021. Trust Insights is the sole sponsor of the study and neither gave nor received compensation for data used, beyond applicable service fees to software vendors, and declares no competing interests.

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