INBOX INSIGHTS, June 23, 2021: Data Quality, Natural Language Generation, Instagram Brand Data

Data Quality, Natural Language Generation, Instagram Brand Data

Inbox Insights from Trust Insights

Want to know what works on Instagram? Watch the replay of Instagram Data-Driven Best Practices here »

Data Quality Requires Subject Matter Expertise

As I was preparing this week’s Data Diaries, I looked at the latest batch of brands that Facebook provides in our Crowdtangle software. I noticed something concerning:

Personal brand mixed in with corporate brands, and yes, there really is a list called Catfluencers

What we see in the data are personal brands mixed in with corporate brands. The intent of looking at brands on Instagram is to look primarily at corporate brands, brands where the entity is a corporation, a company, an organization as opposed to an individual human being. Individual people we bucket under influencers. While we could argue semantics about the power of a personal brand – Celine Dion, for example, is both a human being and a brand – for the purposes of understanding how brands are posting content on social media, I prefer to put personal brands under influencers.

The exception would be where a personal brand isn’t really the person at all. Steve Madden, for example, is a fashion brand that manufactures footwear. The person, Steve Madden, isn’t much involved with Steve Madden the brand. The same is true of Estee Lauder. The real Estee Lauder is deceased, but the corporation maintained her name as the official brand.

So I took an hour to prune through the 4,000+ brands in our collection and removed about 500 personal brands. Now, did Facebook do something wrong? No. They lumped personal brands in with corporate brands because from their point of view, they’re functionally identical. Their classification system is different than ours because they have different intent.

But this speaks to the vital importance of subject matter expertise when it comes to data quality. If we want our data to serve the purposes we intend, we must ensure that it meets our standards. In this case, the data did not meet our standards – but the average person might not disambiguate between a personal brand and a corporate brand. It’s not something I’d want to outsource per se, and definitely something that’s not easily automated. Why? Because this kind of classification requires a lot of judgement, human judgement that requires more nuance than the average classification model would have with such a small dataset.

So what’s the point? Don’t blindly trust third party data, even when it comes from credible sources. Take the time to inspect it, to see what’s inside the box, and determine how well it aligns with your intended use. This applies to any kind of marketing data from a third party, from your Google Analytics instance to social media data to your direct mail list. You might be surprised what level of data quality you’re getting – and how much work it will take to clean up.

Share With A Colleague

Do you have a colleague or friend who needs this newsletter? Send them this link to help them get their own copy:

https://www.trustinsights.ai/newsletter

Binge Watch and Listen

In this week’s In-Ear Insights, Katie and Chris talk about the newest advances in natural language generation and walk through an example of what’s available now for creating content with the assistance of AI. Watch the demonstration, listen to the implications for marketers, and start formulating your AI-based content marketing strategy. Tune in to find out how!

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 audit your Google Tag Manager account.

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

This Thursday at 1 PM Eastern, we’ll be walking through how analyze content marketing to see what’s working and what’s not.

Are you subscribed to our YouTube channel? If not, click/tap here to subscribe!

Need a reminder?

Data Diaries - Interesting Data We Found

In this week’s Data Diaries, we look at our newly-revised and appended Brands list on Instagram to see how unpaid brand content has performed in terms of engagement, year to date.

Instagram brand performance of unpaid content

We see after a relatively stable springtime, where brand performance remained relatively static (around 0.275% engagement) performance has begun to decline again in May, dipping below 0.25% engagement. Performance was highest in January; peak brand performance averaged 0.371% in the first few days of the new year. Performance slipped the most in June, when it dipped as low as 0.222%. For context, 0.222% is engagement of about 1 in every 450 followers, while 0.371% is engagement of about 1 in every 270 followers. That’s a change of -40%.

One interesting tidbit that is in no way conclusive but merely coincidental for now: brand performance began to decline again right after the iOS 14.5 release on April 26. Since this is all unpaid content, there’s no reason to believe the ad targeting changes impacted unpaid content performance, but it’s possible that the negative press (and in-your-face popup when users launched Instagram, begging people to permit ad tracking) had a minor negative effect.

What’s the key takeaway? Unpaid Instagram performance for brands continues to slip, so if Instagram is key to your marketing strategy, you’ll likely need to add more paid efforts to maintain performance and keep attention on the service.

Methodology: Trust Insights used data Facebook’s Crowdtangle software to extract 1,190,519 Instagram posts from 4,715 brands. Brands were provided by Facebook, then cleaned and augmented by Trust Insights. Brands are defined as corporate Instagram accounts and excludes personal brands. The timeframe of the data is January 1, 2021 – June 20, 2021. The date of study is June 23, 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.

Additional disclosure: You’ll note that even after our removal of the personal brands, the charts above didn’t change substantially; overall, personal brands boosted the aggregate brand engagement by about 0.1% – not a huge amount.

In Case You Missed It
Free Training Classes

Get skilled up with an assortment of our free, on-demand classes.

Weekly Wrapup

This 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 Slack Group

Are you a member of our free Slack group, Analytics for Marketers? Join 1700+ like-minded marketers who care about data and measuring their success. Membership is free – join today. We also post hundreds of job openings sourced from around the Internet every Wednesday, so if you’re looking for work, join the Slack group!

Blatant Advertisement

Is AI still a mystery shrouded in an aura of mystique?

Have you read report after report, article after article proclaiming its magical powers and wondered what exactly the big deal is?

With every software vendor and services provider proclaiming that they too are an AI-powered company, it’s more difficult to demystify artificial intelligence and its applications for marketers. What is AI? Why should you care? How does it apply to your business?

In the newly revised Third Edition of AI for Marketers book, you’ll get the answers you’ve been looking for. With all-new practical examples, you’ll learn:

  • Key marketing problems AI solves, such as:

    • Attribution modeling
    • Forecasting
    • Natural language processing for SEO and social media
    • Influencer identification
  • Detailed explanations of what it will take to successfully adopt AI for your marketing

  • How to prepare your career for AI’s impact

  • Ways your AI efforts will go wrong

  • Prerequisites needed to help your AI efforts to succeed

Buy your copy now in the version that best suits you:

» AI for Marketers, Digital Edition comes in Kindle, ePub, and PDF formats »

» AI for Marketers, Print Edition »

Interested in sponsoring INBOX INSIGHTS? Contact us for sponsorship options to reach over 16,000 analytically-minded marketers and business professionals every week.

Featured Partners and Affiliates

Our Featured Partners are companies we work with and promote because we love their stuff. If you’ve ever wondered how we do what we do behind the scenes, chances are we use the tools and skills of one of our partners to do it.

Read our disclosures statement for more details, but we’re also compensated by our partners if you buy something through us.

Upcoming Events

Where can you find us in person?

  • Agorapulse Agency Summit, June 2021, virtual
  • Women in Analytics, July 2021, virtual
  • MAICON, September 2021, virtual
  • Content Marketing World, September 2021, Cleveland, OH
  • MarketingProfs B2B Forum, October 2021, virtual

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

Want some private training at your company? Ask us!

Stay In Touch, Okay?

First and most obvious – if you want to talk to us about something specific, especially something we can help with, hit up our contact form.

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?

Legal Disclosures And Such

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 - Thanks for Reading

Thanks for subscribing and supporting us. Let us know if you want to see something different or have any feedback for us!

One thought on “INBOX INSIGHTS, June 23, 2021: Data Quality, Natural Language Generation, Instagram Brand Data

Leave a Reply

Your email address will not be published. Required fields are marked *

Pin It on Pinterest

Share This