In the Headlights, March 24, 2021: Spring Cleaning, 3 Year Anniversary, Content Republishing

Spring Cleaning, 3 Year Anniversary, Content Republishing

In The Headlights

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Spring Cleaning Your Marketing Data

As the weather warms up, our thoughts naturally turn to digging out of the winter. Around our homes, that means spring cleaning – getting rid of junk, sending things off to charity donations, eliminating things that don’t help us. In business and marketing, much of the same is true.

With upcoming changes in things like ad tracking capabilities, Google Analytics 4, and the ever-evolving MarTech landscape, part of our spring cleaning has to be taking inventory of what we have and getting rid of what we don’t need any more.

What kinds of spring cleaning? Let’s talk data. Every bit of data you have that goes unused is a liability. At the very least, it takes up space and costs you money; at worst, it’s a massive security risk if you’re ever hacked. So, what specific tasks should we be considering?

Clean up access. Let’s say you’re in charge of your marketing automation system, or your Google Analytics account, or your sales CRM. Without looking, can you name the people who should have access to it? Now, go look in the user management section of your MarTech tools. How many people are in there that shouldn’t be – former employees, agencies you no longer work with, people completely unknown to you? Verify who should and should not have access to the crown jewels – your data – and remove anyone who doesn’t belong as quickly as possible.

Clean up tagging and tracking. If you use services like Google Tag Manager or other tagging tools, log in and see what tags are running on your digital properties. Are you collecting data for tools that no longer exist? Are you sending data to companies you shouldn’t be? Is there extra code running that’s slowing down your website or conflicting with other software also running? Verify what’s supposed to be running, and get rid of anything that’s no longer in use.

Clean up mailing lists and databases. It’s well-established by now that engagement rates matter in email marketing for deliverability. Send an email that no one opens, and services like GMail will punish you by reducing your inbox visibility. Send enough email to non-working addresses, and you end up on spam-blocker lists. Take the time once a quarter to clean your list. Remove old addresses. Process your bounces, and inspect a sample of them by hand. Ask subscribers to confirm their details. The less bad mail you send, the easier it is for your good mail to get through.

This is by no means a comprehensive list of everything we should be cleaning on a regular basis, but these are important first steps towards making sure we’re working with the best data possible, in the most secure ways available to us.

The Bright Idea

In this week’s In-Ear Insights, Katie and Chris discuss the lessons learned after three years of being in business. What things went well? What things surprised us? What would we do differently? What’s on the horizon? For entrepreneurs and the curious, lots of takeaways about building a company from scratch.:

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

This week, tune into So What? The Marketing Analytics and Insights Live Show on Thursday at 1 PM Eastern as we discuss off-the-shelf attribution models in software like Google Analytics. You’ll learn what the most common types are, when they apply, and what to do about attribution in the new Google Analytics 4. Catch us live on our YouTube channel.

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Rear View Mirror Data

In this week’s Rear View Mirror, we dig into the latest metrics on content republishing. How much content are we republishing, and does republishing work? In past issues, we’ve examined the art of republishing content and previously concluded that it does generate results, but not as well as original content. Let’s see what 2021 holds thus far. First, the overall content publishing trends:

Content republishing chart

What we see here is a fairly consistent amount of content republising until about the end of February, after which original content – content never published previously – drops off dramatically, from a high in February of almost 600,000 pieces of content in a day to less than 50,000 pieces of content a day in mid-March. Meanwhile, republished content rises from around 50,000 pieces a day to over 100,000 pieces of content a day in mid-March.

Why is this the case? We don’t know; there doesn’t appear to be an obvious explanation for the overall dramatic decline in content.

When we look at the content performance for the top 5,000 articles per week over the same time period, we see some interesting performance:

top 5,000 articles per week table

What we see is republished content outperforms its original content peers, in some cases by considerable amounts. The average republished piece of content earns 1,000 more visits within the same time period as new content, and has larger numbers of shares in the same time period.

So, what’s the key takeaway here? Two things.

First, the unusual deficit of original content could be an opportunity; check using your SEO tool of choice to determine if your industry/niche is experiencing an original content lull, and if so, fill it while you can.

Second, republishing content is now delivering stronger results, so don’t be afraid to improve and republish content over time to supplement your original content.

Methodology: Trust Insights used AHREFS data about content with the most individual page traffic, published in the English language, for the query terms “a OR and OR the”, excluding homepages and explicit results. The timeframe of the data is January 1, 2021 – March 20, 2021. The date of study is March 22, 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.

In Case You Missed It
Partner Spotlight

Do you want to understand data science better as a marketer? Would you like to learn whether it’s the right choice for your career? Do you need to know how to manage data science employees and vendors? Take the Data Science 101 workshop from Trust Insights.

In this 90-minute on-demand workshop, learn what data science is, why it matters to marketers, and how to embark on your marketing data science journey. You’ll learn:

  • How to build a KPI map
  • How to analyze and explore Google Analytics data
  • How to construct a valid hypothesis
  • Basics of centrality, distribution, regression, and clustering
  • Essential soft skills
  • How to hire data science professionals or agencies

The course comes with the video, audio recording, PDF of the slides, automated transcript, example KPI map, and sample workbook with data.

Get your copy by clicking here or visiting TrustInsights.ai/datascience101 »

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Shiny Objects

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

Data Science and AI

SEO, Google, and Paid Media

Social Media Marketing

Content Marketing

Join the Club

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Get Back To Work

We’ve changed things up in Get Back To Work, and we’re looking at the top 310 metro areas in the United States by population. This will give you a much better sense of what the overall market looks like, and will cover companies hiring in multiple locations. Get all the data in our Slack group!

Upcoming Events

Where can you find us in person?

  • MarketingProfs B2B Forum, April 2021, virtual
  • HighEdWeb Analytics Summit, April 2021, virtual
  • ContentTech Summit, April 2021, virtual

Going to a conference we should know about? Reach out!

Want some private training at your company? Ask us!

Stay In Touch

Where do you spend your time online? Chances are, we’re there too, and would enjoy sharing with you. Here’s where we are – see you there?

FTC Disclosure

Some events and partners have purchased sponsorships in this newsletter and as a result, Trust Insights receives financial compensation for promoting them. Read our full disclosures statement on our website.

Conclusion

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