INBOX INSIGHTS, October 6, 2021: Consistency, Data-Driven Content Curation, Quitting Facebook - Trust Insights Marketing Analytics Consulting

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Consistency is Key to Good Data Health

Last week I restarted my strength training. You know what? It sucks to start over.

You know that saying, “it’s just like riding a bicycle”? What they don’t tell you is how frustrating it can be. If you took a few years off from riding a bike, or in this case, lifting weights, you can’t pick up where you left off. You need to rebuild your strength through new habits. Your muscles will be sore. Sitting down and climbing stairs will be challenging. You may even want to give up.

Why am I telling you this? Because this is a preventable problem. I could have prevented this from happening. I didn’t need to start over if I hadn’t stopped in the first place.

Ok, so let’s get to the point and why this is relevant to you. Consistency is key. Consistency with your data collection. Consistency with your data analysis. Consistency with your data-driven decision. Consistency with your data health.

I work with a lot of clients that may look at their data once every few months. It might not be their area of expertise or it might not be a big priority for them. It might not be presented in a way that is accessible or understandable. Data is an easy thing to ignore. You can make decisions without data. You can run a business without looking at historical data. Those are not great options, but they are realities if you choose them. If I only picked up my weights once every few months I would be forever starting over from the beginning, not making any progress.

So what’s the solution? Much like taking care of your health, you need to create a routine and stick with it. Start small and build up to bigger things.

In the context of your data health, start small. Make sure it’s set up correctly and make a plan to review your data once a day. You don’t need to look at all your data, you can start with one metric. Aim for five minutes a day or less.

How do you pick a metric? Walkthrough a simple KPI map. A KPI mapping exercise will help you prioritize your data to understand what is important.

Let’s say for example I run an eCommerce website where I sell widgets.

My business goal is revenue. Therefore, my KPI will be sales from my site. A metric that I’ll look at to track my KPI is site visits. Without site visits, people won’t buy anything, and I won’t have any revenue.

So once I have my website analytics set up, I can look at my site traffic every day. Does it go up? Does it go down? Is there a trend or seasonality? An easy to pull these stats is to connect your web traffic to an automated dashboard. Google Analytics connects natively to Google Data Studio. You can set up a simple table that shows you the daily traffic.

Once you have a couple of weeks’ worth of data that you’re reviewing daily, start adding in other metrics. These metrics should be ones that tell you whether you’re on track to meet your goals. are you collecting data about visits to specific product pages? What about cart fills? Those are great metrics that will help you to understand if you’re on track.

Again, the key is consistency. Just like working out, start small. If you try to do everything all at once, your chances of success start to go down as you relearn along the way. Data health, in the sense of forming a new habit, is the same as your own personal health. Do a little every day and build on that success.

How do you stay on top of your data health? Let me know in our free Slack group, Analytics for Marketers!

– Katie Robbert, CEO

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In this episode, Katie and Chris reflect on the revelations about Facebook Inc. and how a company’s business practices can put it so far out of alignment with your core values that you have to stop doing business with them if you want to stay true to your values. But making a major change like ceasing to do business with Facebook isn’t something you can just flip a switch on: you need a roadmap, a plan of action, and steps to take to determine how to reduce your dependence on Facebook’s platform. Tune in to find out more!

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 SEO keyword analysis basics – how to get started picking apart a list of keywords for prioritization.

Watch/listen to this episode of So What? here »

This Thursday at 1 PM Eastern, we’re going to take a look at performing basic SEO competitive keyword analysis.

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Data Diaries - Interesting Data We Found

In this week’s Data Diaries, let’s solve a content marketing problem. One of the challenges of content marketing is discoverability – the ability for people to discover our content. Certainly, search engines help to solve this problem, but they do so imperfectly. What’s more, if we solely rely on search engines, then we risk sending our key audience to our competitors – not ideal. Social media postings and email marketing are great for drawing attention to specific pieces of content, but aren’t a comprehensive, simple way to help people discover stuff.

What’s the solution? Curation. Not just “let’s copy a bunch of links to our Twitter account”, but real, intentional curation. Here’s an example. How many videos do we have on our YouTube channel? 205. How many of those have you watched? Probably less than a dozen. Likely less than a handful. Why? Because there’s no easy way for you to discover them.

Frankly, we have no idea what we’ve published on there, either, with all the livestreams, keynotes, etc. So how would we start the process of curating these videos? Start by exporting all of them from YouTube Analytics:

Next, we look at basic word counts. How much does any particular word make it into our video titles, once we remove our brand name and show titles (such as So What? and In-Ear Insights):

Already, we see a clear theme, obviously parseable topics and themes. We’ll build some categories like social media, content marketing, etc. to see how many videos fit in each of these categories:

With each category, we can now export specific videos to make things like YouTube playlists, or better, filtered content that can go in things like newsletters, blog posts, social content, and more. Let’s take a look at our summarized breakdown:

Suppose we wanted to just share a list of videos about SEO? Now, with this data tabulated, we can do exactly that, helping our audience find videos on that specific topic:

This is data-driven content curation, and it’s one of the best ways to help your audience find the content you’ve worked so hard to produce. It’s even more important now when AI-based content recommendations may not surface what you want your audience to find in search and social media. That’s what we’ll be doing with our YouTube content in the future.

This technique applies to any content where you have access to the content name, like email newsletters, blog posts, and more. Try it with your own content and curate better experiences for your audience!

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

SEO, Google, and Paid Media

Content Marketing

Data Science and AI

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