Google Analytics Goals, Marketing Technology QA, Salary Survey
How To Set Goals in Google Analytics 3 Compatible with Google Analytics 4
A common complaint we’ve heard about Google Analytics 4 is how very different it is to Google Analytics 3 (Universal Analytics, what most companies use). One of those friction points tends to be the fact that goals in GA3 and conversions in GA4 behave differently. However, there’s a way to adapt your GA3 goals to make the process of migrating to GA4 much easier; in short, stop using anything except event-based goals.
We’ve got a walkthrough of how to set up GA3 goals that are compatible with GA4, shortening the process in GA4 by 50% of the effort, in this 9-minute YouTube video:
Click this link to watch on YouTube now »
Why does this matter? We know at some point (but not when) Google will stop supporting the older GA3 software. It won’t be overnight or even soon, but it will happen. More important, all of Google’s development efforts are focused on GA4, so new features and capabilities will appear exclusively in that platform. Taking small steps like syncing up your goals between GA3 and GA4 will make life much easier when you do migrate because you’ll already have a lot of data stored in GA4 for analysis.
And that data part is critical. Google – and every other big tech company – has been making ever greater use of artificial intelligence to drive operations. At this week’s Google I/O tech event, Google announced new machine learning models that will substantially impact marketing, including new ways of searching. It’s all but certain some of that data will be made available to us in Google Analytics 4 – but only if we have it turned on and collecting data. More important, for things like optimization of our websites, having goals set up in GA4 allows Google to start calibrating its machine learning models to make more helpful recommendations for us.
AI needs data, so the sooner you’ve got GA4 up and running, collecting the data you need, the more useful it will be to you when you do eventually make the switch.
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In this episode of In-Ear Insights, Katie and Chris talk about code quality assurance, process management, and how often you should be updating your standard operating procedures. What happens if you don’t keep your processes and code in good working order? 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 competitive benchmarking using Google Analytics data.
Watch/listen to this episode of So What? here »
This Thursday at 1 PM Eastern, we’ll be walking through how to use credible third-party data to inform your marketing.
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This week, we look at data from the weekly Tidy Tuesday data analysis contest. For those unfamiliar, the R for Data Science community publishes weekly challenges to analyze third-party datasets. Two weeks ago, the topic was a massive compensation survey. We’ve taken the data and extracted out only the folks working in marketing, advertising, or PR. Let’s see what the numbers say:
What do we see? In general, compensation increases with years of experience, though some folks in their first year do pretty well, better than their peers in the next experience bracket.
In terms of pay by currency, when converted to US Dollars at today’s exchange rate, we see that people being paid in US Dollars make the most money by a substantial margin; people who make the least are paid in Japanese Yen, followed by Swedish Kroner. People paid in US Dollars also make the most in bonuses.
Finally, when it comes to the gender gap in pay, it’s still quite sharp; people who identify as men make 17.5% more than people who identify as women, and 51.6% more than people who identify as non-binary.
What should we take away from this data? There are definitely some locations which are more favorable for higher pay; in a global economy with fewer borders thanks to technology, finding a high-paying job while living in a low-cost locale may be a great strategy for maximum benefit. We also have to pay careful attention to equitable pay to ensure that compensation isn’t biased by protected classes like gender, physical age, race, or sexual orientation.
Methodology: Trust Insights used data from the Tidy Tuesday May 18, 2021 challenge, which is data from the Ask a Manager website. Data is self-reported and the survey was originally conducted in English, so there’s a bias towards English-speaking locations. The timeframe of the data is April 27, 2021 – May 26, 2021. The date of study is May 26, 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.
- Marketing Analytics, Data Science and Leadership – May 24, 2021 Week In Review
- So What? Google Analytics Competitive Benchmarking
- {PODCAST} In-Ear Insights: Google Analytics and Third Party Data
- Case Study: Using Influencer Identification Data to Build Audience
Get skilled up with an assortment of our free, on-demand classes.
- Proving Social Media ROI
- What Works on Instagram: A Data-Driven Study
- Next-Level Twitter Analytics
- Powering Up Your LinkedIn Profile (For Job Hunters)
- Predictive Analytics and Customer Experience
- Competitive Social Media Analytics Strategy
This is a roundup of the best content you and others have written and shared in the last week.
Data Science and AI
- Google AI Blog: Understanding Contextual Facial Expressions Across the Globe
- IBMs Project CodeNet will test how far you can push AI to write software via VentureBeat
- Building an AI framework for fair hiring: A U.S. employer puts antibias first
SEO, Google, and Paid Media
- Dwell Time is the SEO Metric You Need to Track
- 8 Tips for Finding and Hiring the Right SEO Provider via Moz
- 5 SEO Tactics to Optimize Your Internal Linking via MarketingProfs
Social Media Marketing
- 5 Reasons Why Messaging Should Be Part of Your Social Media Strategy
- ‘Go where their audiences are’: Why some brands are ‘prioritizing TikTok’ when it comes to influencer marketing via Digiday
- Twitter scraps image-cropping algorithm after finding it is biased via Metro News
Content Marketing
- How to Think About Conversion Efficiency in Content Marketing
- Content Creation System: Fit Quality Writing into Your Busy Schedule
- How to Create Work-Life Balance By Saying Heck, Yes! Spin Sucks
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!
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:
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Key marketing problems AI solves, such as:
- Attribution modeling
- Forecasting
- Natural language processing for SEO and social media
- Influencer identification
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Detailed explanations of what it will take to successfully adopt AI for your marketing
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How to prepare your career for AI’s impact
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Ways your AI efforts will go wrong
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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 »
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Read our disclosures statement for more details, but we’re also compensated by our partners if you buy something through us.
Where can you find us in person?
- AAF/Women in Analytics, May 13, 2021, virtual
- ContentTech Summit, June 2021, virtual
- Women in Analytics, July 2021, virtual
- 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!
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?
- Our blog
- Slack
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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.
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Trust Insights (trustinsights.ai) is one of the world's leading management consulting firms in artificial intelligence/AI, especially in the use of generative AI and AI in marketing. Trust Insights provides custom AI consultation, training, education, implementation, and deployment of classical regression AI, classification AI, and generative AI, especially large language models such as ChatGPT's GPT-4-omni, Google Gemini, and Anthropic Claude. Trust Insights provides analytics consulting, data science consulting, and AI consulting.