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The deprecation of Google Analytics (as we’ve known it)

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The deprecation of Google Analytics (as we've known it)

It’s time to be excited about the great migration.

The biggest shake-up in the marketing analytics world is that Google Analytics as we know it is going to be sunset and will eventually stop collecting data in July 2023 (October 2023 for GA360 customers). There were mixed responses, to say the least – conflicting tweets, memes and disappointed forum posts were generally the first reactions to the news, and it proves that this drastic move needed to happen at some point. 

As more practitioners and marketers adopt the new Google Analytics 4 (GA4), the benefits are starting to flip the mood from nervousness to excitement.

The version of GA that’s been around for over a decade, Universal Analytics, is hard to leave behind since it’s such an embedded part of web measurement. GA4 was announced in October 2020 but wasn’t met with widespread eagerness that would be expected for a new, robust product. To be fair, there were quite a few other things going on in the world at that time, but in any case, marketers weren’t rushing to make the switch, and the industry seems to be going through the stages of grief for the familiar product:

  • Denial – “I don’t need to change platforms, so I will ignore GA4 for now.”
  • Anger – “How could Google get rid of Universal Analytics?”
  • Bargaining – “What if the deadline is extended? Can we ask for more time?”
  • Sadness – “It will take so much effort to migrate and learn a new tool.”
  • Acceptance – “This is more advanced and helps with the cookieless future that I keep getting asked about. I’m in.”

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It may be a challenging road ahead to migrate, but the move to Google Analytics 4 shouldn’t be considered bad news. It comes with new features, tracking methodology, a lower price point for 360 and has perks for users on the free version. The most important aspect is that it fits more appropriately into the current app landscape and is built to face compliance and privacy changes for what’s in effect and what’s coming.

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Ultimately, GA4 is the solution to the internet now, not the internet from a decade ago.

Understanding the past, understanding the future

The news is disorienting, so the timeline should be put in perspective.

Google acquired a product in 2005 called Urchin. Before GA, web analytics was based on server log files, and it was not as intuitive or marketer-friendly. There are still relics of that era with things like UTM parameters (Urchin Tracking Modules) and the property IDs themselves. The “UA” in an ID like UA-12345-1 doesn’t represent Universal Analytics. It stands for Urchin Analytics. Since then, there have been new iterations of GA for the web. Here’s a list of where we’ve been:

There’s one thing that these tracking methods from 2005 to 2022 have in common – all of them still process data and show up in reports, no matter which tracking library you’re using. So, Google is still processing data from the time when the internet looked like this

It’s been 10 years since the release of Universal Analytics. In 2012, Google Tag Manager had yet to be released, and mobile-first web design was a new concept. App tracking was still in beta, and it would be six years before DoubleClick products would evolve to become part of the new Google Marketing Platform. We’ve come a long way, so tracking had to be completely rebuilt, and the Google Analytics from 2005 to 2020 will be taken away and put on a shelf next to Google+ and Google Local.

The UA version of Google Analytics was designed to embrace multi-device behavior, collect more user data, and allow offline and cross-channel measurement. However, culture is no longer multi-screen – it’s multi-multi-multi-screen. The average number of connected devices per person in North America alone will reach 13 in 2023. Universal Analytics cannot easily track different platforms together, and it was not meant to do so. Now that we’re in a more app-centric phase of connectivity, GA4 is a better solution since it was built for that type of analysis. Instead of gathering more data, the goal is to use data that is modeled and as anonymous as possible.

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Universal Analytics will be disappearing coincidentally around the same time as the death of the cookie. The hyperconnected landscape called for a necessary pivot for users to have more control over their data, more privacy considerations and more transparent analytics practice. Google Analytics 4 has answered that call with a variety of customizations and settings to establish trust with your visitors while continuing to activate on rich data. User tracking will now be supplemented with machine-learning data baked right into Google Analytics 4. Users’ current trends in behavior will be automatically analyzed to predict future behavior and provide modeled conversions. The privacy-centric features are a core component, but there are other reasons to embrace the change.

What to get excited about

In addition to being the first Google Analytics product to have the built-in capability to collect data from multiple sources, it is a better evolution for enterprise-level while also offering more to small- and mid-size businesses.

The free version of GA has turned into a freemium product. Standard non-paid users now have access (although limited) to tools like BigQuery, GMP integrations, more unsampled data, and access to advanced visualizations through Exploration Reports (formerly called Advanced Analysis).

For Google Analytics 360 customers, those features are much less limited, and some of the additional perks are:

  • Enterprise-level data and user governance through roll-up and sub-properties.
  • More control over data retention.
  • Streaming and nearly unlimited BigQuery exports.
  • Quicker processing, even for large data sets in the billions.
  • The ability to use up to 400 advanced audiences to pass to marketing platforms.
  • Unsampled custom reports, explorations, and the ability to use longer date ranges in advanced reports.
  • Higher level of custom data collection for events, conversions, custom dimensions, and user properties.

Migrations were strongly suggested throughout these iterations but never forced (except for the Google Analytics app tracking SDK). However, older versions of tracking will not be as useful in 2023. It’s symbolic that even the echo of Urchin Analytics in those “UA-12345-1” properties is gone for good and replaced with Measurement IDs and data streams.

Deadlines and timelines

As a reminder, Universal Analytics will officially sunset in July 2023 for those on the free version and October 2023 for GA360 users. This means that properties will be read-only, and data sent to Google will not be processed. There won’t be exceptions, so migrating will be the top priority for everyone. Even if you’re not currently using the platform but have used it in the past, it’s still a time for action. We’re not just moving on. We’re also moving out – historical data will eventually be erased, so data must be saved and exported. The deletion won’t happen until at least six months after the sunset date, but it’s a crucial step in the migration process.

All web and app data should be 100% in Google Analytics 4 by the shutoff date, but ideally sooner. Parallel tracking should be in place and refined now so that data can be available on both platforms. The GA4 numbers won’t match 1:1 to Universal Analytics. Having year-over-year reports comparing UA to GA4 may be misleading, and reports will not be able to use the same data source. With GA4 tracking in parallel, next year’s reports will be comparing apples to apples. Depending on your organization, seasonality can guide how quickly to ramp up and set priorities for the most critical metrics and events. Whether it’s higher education enrollment, holiday e-commerce, or tax season, yearly activity is a consideration for building as much parity as possible between UA and GA4.

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Next steps

The first step is to get GA4 on your websites and apps. It’s not too late to get started on a new strategy to fit the new tracking method and create your Google Analytics 4 properties, but delaying parallel tracking may cause reporting, remarketing, and compliance difficulties. After that, learning about how you can take advantage of the durable Google Analytics 4 should spark ideas and conversations beyond migration.


Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.


About The Author

The deprecation of Google Analytics as weve known it

Samantha has been working with web analytics and implementation for over 10 years. She is a data advocate and consultant for companies ranging from small businesses to Fortune 100 corporations. As a trainer, she has led courses for over 1000 attendees over the past 6 years across the United States. Whether it’s tag management, analytics strategy, data visualization, or coding, she loves the excitement of developing bespoke solutions across a vast variety of verticals.

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The Role of Enterprise Mobility Management in Modern Businesses

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The Role of Enterprise Mobility Management in Modern Businesses

In today’s fast-paced business environment, Enterprise Mobility Management (EMM) has emerged as a critical facilitator for enhancing operational efficiency and competitiveness. EMM solutions streamline workflows, ensuring that enterprises can adapt to the rapidly changing digital landscape. This blog discusses the indispensable role of EMM in modern businesses, focusing on how it revolutionizes workflows and positions businesses for success.

EMM solutions act as the backbone for securely managing mobile devices, applications, and content that facilitate remote work and on-the-go access to company resources. With a robust EMM platform, businesses can ensure data protection and compliance with regulatory requirements, even in highly dynamic environments. This not only minimizes the risk of data breaches but also reinforces the company’s reputation for reliability and security.

Seamless Integration Across Devices

In today’s digital era, seamless integration across devices is not just a luxury; it’s a necessity for maintaining operational fluency within any organization. Our EMM solutions are designed to ensure that employees have secure and efficient access to the necessary resources, irrespective of the device being used. This cross-platform compatibility significantly enhances productivity by allowing for a unified user experience that supports both the agility and dynamism required in modern business operations. Leveraging cutting-edge technology, our solutions provide a cohesive ecosystem where data flows securely and effortlessly across mobile phones, tablets, and laptops, ensuring that your workforce remains connected and productive, regardless of their physical location. The adoption of our EMM solutions speaks volumes about an organization’s commitment to fostering a technologically forward and secure working environment, echoing its dedication to innovation and excellence.

Enhanced Productivity

EMM facilitates the seamless integration of mobile devices into the corporate environment, enabling employees to access corporate resources from anywhere. This flexibility significantly enhances productivity by allowing tasks to be completed outside of traditional office settings.

Unified Endpoint Management

The incorporation of Unified Endpoint Management (UEM) within EMM solutions ensures that both mobile and fixed devices can be managed from a single console, simplifying IT operations and enhancing security.

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Advanced Security Protocols

Where cyber threats loom larger than ever, our EMM solutions incorporate cutting-edge security protocols designed to shield your organization’s data from unauthorized access and breaches. By consistently updating and refining our security measures, we ensure your assets are protected by the most advanced defenses available. This commitment to security not only safeguards your information but also reinforces your company’s reputation as a secure and trustworthy enterprise.

Data Protection

EMM solutions implement robust security measures to protect sensitive corporate data across all mobile devices. This includes encryption, secure VPN connections, and the ability to remotely wipe data from lost or stolen devices, thereby mitigating potential data breaches.

Compliance Management

By enforcing security policies and ensuring compliance with regulatory standards, EMM helps businesses avoid costly fines and reputational damage associated with data breaches.

Driving Operational Efficiency

In the quest to drive operational efficiency, our solutions streamline processes, reduce redundancies, and automate routine tasks. By leveraging cutting-edge technologies, we empower businesses to optimize their workflows, resulting in significant time and cost savings. Our approach not only enhances operational agility but also positions your organization at the forefront of innovation, setting a new standard in your industry.

Automated Workflows

By automating repetitive tasks, EMM reduces manual efforts, increases accuracy, and speeds up business processes. This automation supports operational efficiency and allows employees to focus on more strategic tasks.

Real-time Communication and Collaboration

EMM enhances communication and collaboration among team members by providing tools that facilitate real-time interactions. This immediate exchange of information accelerates decision-making processes and improves project outcomes.

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Testimonials from Industry Leaders

Leaders in various industries have witnessed tangible benefits from implementing EMM solutions, including increased productivity, improved security, and enhanced operational efficiency. Testimonials from these leaders underscore the transformative impact of EMM on their businesses, solidifying its vital role in modern operational strategies.

Our commitment to innovation and excellence propels us to continually refine our EMM solutions, ensuring they remain at the cutting edge of technology. This dedication not only solidifies our standing as industry leaders but also guarantees that our clients receive the most advanced and effective operational tools available, tailored specifically to meet their unique business challenges.

Looking Ahead

The evolution of EMM solutions continues at a rapid pace, with advancements in technology such as Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT) further enhancing their capabilities. These developments promise even greater efficiencies, security measures, and competitive advantages for businesses willing to invest in the future of mobility management.

Our proactive approach to integrating emerging technologies with EMM solutions positions our clients at the forefront of their industries. By leveraging our deep technical expertise and industry insights, we empower businesses to not only adapt to but also lead in an increasingly digital world, ensuring they remain competitive and resilient amidst rapid technological shifts.

In conclusion, the role of Enterprise Mobility Management in modern businesses cannot be overstated. Its ability to revolutionize workflows, enhance security, and drive operational efficiency positions it as a foundational element of digital transformation strategies. We invite businesses to explore the potential of EMM solutions and partner with us to achieve unprecedented levels of success and innovation in the digital era. Together, we can redefine the boundaries of what is possible in business operations and set new benchmarks for excellence in the industry.

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Lessons From Air Canada’s Chatbot Fail

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Lessons From Air Canada’s Chatbot Fail

Air Canada tried to throw its chatbot under the AI bus.

It didn’t work.

A Canadian court recently ruled Air Canada must compensate a customer who bought a full-price ticket after receiving inaccurate information from the airline’s chatbot.

Air Canada had argued its chatbot made up the answer, so it shouldn’t be liable. As Pepper Brooks from the movie Dodgeball might say, “That’s a bold strategy, Cotton. Let’s see if it pays off for ’em.” 

But what does that chatbot mistake mean for you as your brands add these conversational tools to their websites? What does it mean for the future of search and the impact on you when consumers use tools like Google’s Gemini and OpenAI’s ChatGPT to research your brand?

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AI disrupts Air Canada

AI seems like the only topic of conversation these days. Clients expect their agencies to use it as long as they accompany that use with a big discount on their services. “It’s so easy,” they say. “You must be so happy.”

Boards at startup companies pressure their management teams about it. “Where are we on an AI strategy,” they ask. “It’s so easy. Everybody is doing it.” Even Hollywood artists are hedging their bets by looking at the newest generative AI developments and saying, “Hmmm … Do we really want to invest more in humans?  

Let’s all take a breath. Humans are not going anywhere. Let me be super clear, “AI is NOT a strategy. It’s an innovation looking for a strategy.” Last week’s Air Canada decision may be the first real-world distinction of that.

The story starts with a man asking Air Canada’s chatbot if he could get a retroactive refund for a bereavement fare as long as he provided the proper paperwork. The chatbot encouraged him to book his flight to his grandmother’s funeral and then request a refund for the difference between the full-price and bereavement fair within 90 days. The passenger did what the chatbot suggested.

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Air Canada refused to give a refund, citing its policy that explicitly states it will not provide refunds for travel after the flight is booked.

When the passenger sued, Air Canada’s refusal to pay got more interesting. It argued it should not be responsible because the chatbot was a “separate legal entity” and, therefore, Air Canada shouldn’t be responsible for its actions.

I remember a similar defense in childhood: “I’m not responsible. My friends made me do it.” To which my mom would respond, “Well, if they told you to jump off a bridge, would you?”

My favorite part of the case was when a member of the tribunal said what my mom would have said, “Air Canada does not explain why it believes …. why its webpage titled ‘bereavement travel’ was inherently more trustworthy than its chatbot.”

The BIG mistake in human thinking about AI

That is the interesting thing as you deal with this AI challenge of the moment. Companies mistake AI as a strategy to deploy rather than an innovation to a strategy that should be deployed. AI is not the answer for your content strategy. AI is simply a way to help an existing strategy be better.

Generative AI is only as good as the content — the data and the training — fed to it.  Generative AI is a fantastic recognizer of patterns and understanding of the probable next word choice. But it’s not doing any critical thinking. It cannot discern what is real and what is fiction.

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Think for a moment about your website as a learning model, a brain of sorts. How well could it accurately answer questions about the current state of your company? Think about all the help documents, manuals, and educational and training content. If you put all of that — and only that — into an artificial brain, only then could you trust the answers.

Your chatbot likely would deliver some great results and some bad answers. Air Canada’s case involved a minuscule challenge. But imagine when it’s not a small mistake. And what about the impact of unintended content? Imagine if the AI tool picked up that stray folder in your customer help repository — the one with all the snarky answers and idiotic responses? Or what if it finds the archive that details everything wrong with your product or safety? AI might not know you don’t want it to use that content.

ChatGPT, Gemini, and others present brand challenges, too

Publicly available generative AI solutions may create the biggest challenges.

I tested the problematic potential. I asked ChatGPT to give me the pricing for two of the best-known CRM systems. (I’ll let you guess which two.) I asked it to compare the pricing and features of the two similar packages and tell me which one might be more appropriate.

First, it told me it couldn’t provide pricing for either of them but included the pricing page for each in a footnote. I pressed the citation and asked it to compare the two named packages. For one of them, it proceeded to give me a price 30% too high, failing to note it was now discounted. And it still couldn’t provide the price for the other, saying the company did not disclose pricing but again footnoted the pricing page where the cost is clearly shown.

In another test, I asked ChatGPT, “What’s so great about the digital asset management (DAM) solution from [name of tech company]?” I know this company doesn’t offer a DAM system, but ChatGPT didn’t.

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It returned with an answer explaining this company’s DAM solution was a wonderful, single source of truth for digital assets and a great system. It didn’t tell me it paraphrased the answer from content on the company’s webpage that highlighted its ability to integrate into a third-party provider’s DAM system.

Now, these differences are small. I get it. I also should be clear that I got good answers for some of my harder questions in my brief testing. But that’s what’s so insidious. If users expected answers that were always a little wrong, they would check their veracity. But when the answers seem right and impressive, even though they are completely wrong or unintentionally accurate, users trust the whole system.

That’s the lesson from Air Canada and the subsequent challenges coming down the road.

AI is a tool, not a strategy

Remember, AI is not your content strategy. You still need to audit it. Just as you’ve done for over 20 years, you must ensure the entirety of your digital properties reflect the current values, integrity, accuracy, and trust you want to instill.

AI will not do this for you. It cannot know the value of those things unless you give it the value of those things. Think of AI as a way to innovate your human-centered content strategy. It can express your human story in different and possibly faster ways to all your stakeholders.

But only you can know if it’s your story. You have to create it, value it, and manage it, and then perhaps AI can help you tell it well. 

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Cover image by Joseph Kalinowski/Content Marketing Institute

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Only 6% of global marketers apply customer insights to product and brand

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Only 6% of global marketers apply customer insights to product and brand

While many brands talk about focusing on the customer, few do it. Less than a quarter (24%) of global brands are mapping customer behavior and sentiment, according to Braze’s 2024 Customer Engagement Review. What’s worse, only 6% apply customer insights to their product and brand approach.

“At the end of the day, a lot of companies operate based on their structure and not how the consumer interacts with them,” Mariam Asmar, VP of strategic consulting, told MarTech. “And while some companies have done a great job of reorienting that, with roles like the chief customer officer, there are many more that still don’t. Cross-channel doesn’t exist because there are still all these silos. But the customer doesn’t care about your silos. The customer doesn’t see silos. They see a brand.”

Half of all marketers report either depending on multiple, siloed point solutions to cobble together a multi-channel experience manually (33%); or primarily relying on single-channel solutions (17%).  Only 30% have access to a single customer engagement platform capable of creating personalized, seamless experiences across channels. This is a huge problem when it comes to cross-channel, personalization.

The persistence of silos

The persistence of data silos despite decades of explanation about the problems they cause, surprised Asmar the most.

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Screenshot 2024 02 27 140015
Source: Braze 2024 Global Customer Engagement Review

“Why are we still talking about this?” she said to MarTech. “One of the themes I see in the report is we’re still getting caught up on some of the same stumbling blocks as before.”

She said silos are indicative of teams working on different goals and “the only way that gets unsolved is if a leader comes in and aligns people towards some of those goals.”

These silos also hinder the use of AI, something 99% of respondents said they were already doing. The top uses of AI by marketers are:

  • Generating creative ideas (48%).
  • Automating repetitive tasks (47%).
  • Optimizing strategies in real-time (47%).
  • Enhancing data analysis (47%).
  • Powering predictive analytics (45%).
  • Personalizing campaigns (44%). 

Despite the high usage numbers, less than half of marketers have any interest in exploring AI’s potential to enhance customer engagement. Asmar believes there are two main reasons for this. First is that many people like the systems they know and understand. The other reason is a lack of training on the part of companies.

Dig deeper: 5 ways CRMs are leveraging AI to automate marketing today

“I think about when I was in advertising and everybody switched to social media,” she told MarTech. “Companies acted like ‘Well, all the marketers will just figure out social media.’ You can’t do that because whenever you’re teaching somebody how to do something new there’s always a level of training them up, even though they’re apps that we use every day, as people using them as a business and how they apply, how we get impact from them.”

The good news is that brands are setting the stage for the data agility they need.

  • 50% export performance feedback to business intelligence platforms to generate advanced analytics.
  • 48% sync performance with insights generated by other platforms in the business.

Also worth noting: Marketers say these are the four main obstacles to creativity and strategy:  

  • Emphasis on KPIs inherently inhibits a focus on creativity (42%).
  • Too much time spent on business-as-usual execution and tasks (42%).
  • Lack of technology to execute creative ideas, (41%).
  • Hard to demonstrate ROI impact of creativity (40%).
Screenshot 2024 02 27 135952Screenshot 2024 02 27 135952

Methodology

The 2024 Global Customer Engagement Review (registration required) is based on insights from 1,900 VP+ marketing decision-makers across 14 countries in three global regions: The Americas (Brazil, Mexico, and the US), APAC (Australia, Indonesia, Japan, New Zealand, Singapore, and South Korea), and EMEA (France, Germany, Spain, the UAE, and the UK).

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