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What’s New & Important for GA4? [2023]

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What’s New & Important for GA4? [2023]

Google Analytics 4 (GA4) marks a major shift in thinking about how web and app properties are tracked. Formerly called “App + Web properties” in beta, Google Analytics 4—announced in October 2020—builds upon the foundation of cross-device unified measurement introduced in July 2019.

GA4 is a new Google product that allows for Web and App data to be collected separately, or in one continuous property. GA4 is designed to replace both Universal Analytics (UA) and GA360, which will be deprecated in 2023. UA accounts will stop collecting data effective July 1, 2023, while GA360 accounts will stop collecting data effective July 1, 2024. At that time, GA4 will become Google’s sole analytics platform.

Acknowledging the increasing overlap between web and mobile app development and content—as well as answering marketers’ needs for unified data—Google Analytics 4 seeks to eliminate the need for manual stitching and workarounds between platforms.

Although Universal Analytics (UA) tracking is available until July 1, 2023 with historical data available for an additional 6 months later, it’s important to recognize GA4 as “the new Google Analytics.”
 

What is Google Analytics 4?

 
GA4 is not simply a redesign of Universal Analytics (UA); it’s an entirely new product that can be installed in addition to your existing UA profile. That said, if you’re setting up GA for the first time, GA4 is the “latest version” that superseded UA as the default analytics platforms in October 2020. UA can still be installed, but GA4 is to be considered a Google Analytics update.

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Previously, Analytics was divided between web properties (traditional Google Analytics) and Analytics for Firebase (to specifically cater to app needs). Perhaps most importantly, Google Analytics 4 seeks to set property owners up with flexible, yet powerful analytics tools within the bounds of cookieless tracking and consent management.

In other words: Google Analytics 4 is ready for the future, and the future is now.

 

Universal Analytics vs. Google Analytics 4

 

Q. Should Businesses Use Both Universal Analytics & GA4?

 
 Absolutely—assuming you already have an existing Universal Analytics profile. GA4 implementation does not necessitate removing your existing GA setup. You’ll want to keep that in place for all that valuable historical data, with the insights you garner from GA4 working in complement with it.

If you are setting up Google Analytics for the first time, you can get started right away with GA4; there is no need to create a new, separate Universal Analytics profile, as those will sunset in July 2023.

A number of important changes have taken place in the evolution of GA4 and the growing restrictions around data privacy. A few key items that have changed—and not just for GA4, in some cases—include:
 

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IP Address logging

 
IP logging has been deprecated as a whole, and all processing for locations will happen and be passed through to GA. This meets GDPR requirements and ensures no compliance issues arise in the form of transferring PII (personally identifiable information)
 

EU Data

 
Previously, EU data was being moved to the States to be processed. This practice has been deprecated, and all EU data is processed within the EU, which also ensures GDPR compliance
 

Google Signals Regionality 

 
Launched in 2018, Google Signals is a product that collects data for users who have opted into Ad Personalization. This data is anonymized and made available to integrate into reporting, audience building, and more. Google Signals can be disabled for specific regions (Countries, specifically), while included for others. There are a number of reasons this control is important; while not necessarily a GDPR requirement, it allows entire regions to not be a part of intake. Reasons for this are typically socioeconomic and/or political
 

Granular Location and Device Data Collection

 
A number of data points including city, device information, browser versioning, and more were previously default. Some may prefer not to collect certain data points for the sake of being tighter on compliance risk. These previously default data points can now be specified regionally if they will be collected
 

New Features & Capabilities of GA4

 
Our GA language is changing. While the reasons we use GA data largely remain the same, the available data—and the best ways to answer the questions at hand—have evolved.

A number of metrics that we’ve grown accustomed to in Universal Analytics have either changed or deprecated and been replaced with something new. Let’s explore a few of the most important updates…

 

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New metrics to track

 
 
Old user behavioral measurements are on the way out. Metrics including bounce rate and average session duration will no longer be available in GA4, requiring that we start using new metrics to understand behavior. These metrics include engagement rates and engaged sessions, which are more impactful in what they describe than previously available metrics.
 

Goals are out, Conversions are in

 
While largely a change in name, the taxonomy changes slightly due to the deprecation of the category/action/label hierarchy of previous events.

It’s important to note that GA4 will count every instance of a conversion event—even if it’s occurred multiple times in one session. For instance, if the same user fills out a form 3 times in one session, that conversion will be counted 3 times. Previously, Goals could only occur once per session.
 

Pageviews are out, Views are in

 
‘Views’ is used over ‘pageviews’ in GA4 due to the combined nature of web & app properties; ‘Views’ accounts for both screenviews and pageviews.

Repeated views of the same content are all counted, as always.
 

Session is out, Session Start is in

 
The definition of what creates a session has slightly changed; a session is now determined when a specific event ‘session start’ is triggered, which generates a session ID that is appended to each event that occurs within the session.

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Sessions end after 30 minutes or the defined timeout period. Additionally, sessions no longer restart at midnight, or when new campaign parameters are encountered.
 

Bounce Rate (while still available) is out, Engagement Rate is in

 
Bounce Rate was always based on whether someone’s session duration was 0. Engagement Rate measures in the opposite direction, communicating what we were always truly looking to learn from Bounce Rate: What percentage of people are actually interacting with the site?
 

Average Session Duration is out, Average Engagement Time is in

 
While the two metrics are calculated differently, Average Engagement Time reports on what Average Session Duration was trying to touch on, but never quite got there: user focus on web or screenpages.
 

A different way to display data

 
Universal Analytics’ data model is hit-based, characterized by sessions and pageviews. Pageviews are essentially the key to the ignition, being the starting point of data collection for Universal Analytics. In GA4, this proverbial key is instead made up of events.
 

Uncovering user information with Identity Spaces

 
GA4 is equipped with four different identity methods to help in creating a unified view of cross-device user journeys:

 

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  • User – ID
  • Google signals
  • Device ID
  • Modeling

 

All data associated with the same user—or identity—is assigned to the same identity space. These identity spaces are used across all GA4 reporting, allowing brands and advertisers to de-duplicate their users list, and gain a richer understanding of their relationship and interaction with your business.
 

Multi-purpose audience lists

 
When you create Audiences in Google Analytics 4, they are automatically imported and become available for remarketing in Google Ads on the Google Search Network, Google Display Network, and YouTube. In Universal Analytics, advertisers had to recreate the audiences in Google Ads that had been created in Google Analytics.
 

Key Business Benefits of Google Analytics 4

 
 
GA4 is a step in the right direction when it comes to providing businesses with the insights that matter—and can be acted on—today, leveraging machine learning and AI components built for the nearing cookieless future.

GA4 opens the pathway to describe and collect data in the way that is most meaningful to each business. Limitations are far fewer, and strong-arming interaction into the constraints of old events becomes obsolete. Collect what you need, and analyze it at the level that is most meaningful.

It’s also notable that the free version of GA4 allows for free product linking. Previously, a GA360 license was required to link DV360, SA360, Campaign Manager 360, and BigQuery.
 

1. Unified Metric and Dimension Scopes

 
The single biggest advantage of Google Analytics 4 is the unified view between app and web.

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Collection methodology is united to “events” with traditional pageviews on a more even scope with behavioral events. Prior versions of Google Analytics required separate tagging and separate properties, with inconsistent (by default) metrics and dimensions.

 

 

Keep in mind there won’t be historical or 24h+ data when you first get into the new GA 4, but you’ll start to see data populate over time

 

2. Simplified & Organized Reporting

 
Perhaps more importantly to marketers and web analysts, with the re-scope of methodology, GA4 has brought several new reporting tools. The existing web and app reports have also been reorganized in the platform UI. Of course, the biggest benefit is the unified user view between app and website, but Google has also revamped their custom reporting tool to an “analysis hub”, which offers a bit more flexibility with custom and ad hoc reporting.
 
User interface for Google Analytics with page-by-page engagement
 

3. New Privacy-Conscious Data Controls

 
 
Unified user journey and reporting across platforms has been a difficulty since the dawn of app and web development. Google has answered (finally!), and seems to understand that these needs will continue to increase, especially with the challenges of data collection.

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As 3rd-party data collection is criticized by privacy advocates (and we observe certain platforms implement tracking restrictions), Google is prepared to shift towards using anonymized first-party data, along with consented tracking. By unifying properties, collection scopes, and announcing significant server-side capabilities, Google is shifting away from client-side dependencies.
  

A Brief Overview of What to Expect with GA4

 
Over the last few years, we have seen Users and Sessions physically change places in GA. This subtle shift was a nod to the future, encouraging marketers to begin tracking towards users over session by session data.

This shift is fully realized in GA4. Event-based tracking over hit-based tracking allows for flexibility and granularity of data not previously possible. Old required categories, like Category/Action/Label, are deprecated, and all interactions with a website are ingested at the same level of granularity.

A pageview happens at the same level of detail as a link click—as scroll depth is tracked, as conversions are recorded. This level-setting allows for flexibility that would have been more limited, making the question less about what happened in a session, and more about the behavior of a user, and the translation of data points into human actions.
  

How to Track Important Marketing Data & Create Reports in GA4

 
Within the Property Settings, a default attribution model can be set for reporting needs. A lookback window can also be specified, leveraging 30-day as the default. This is a stark difference from UA, where Last Non-Direct Click was default, and could not be changed across the account; different models were previously only comparable in a specific tab.

Google has released important notes on attribution models:

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  • Direct visits are excluded from receiving attribution credit on all attribution models unless the conversion path was only direct visits
  • Attribution models have been, and will be, introduced at different dates, with data for those models only available from their start dates forward. If you select data outside of the available date, only partial data will be seen

 
Attribution reporting previously focused on how a website acquired a user’s session, however GA4’s attribution reporting will focus on both how the user was first acquired and how a user’s subsequent sessions were acquired. Below, you’ll see reference to a number of metrics that factor in not just current sessions, but also the original method of acquisition.

You will see a number of old dimensions and metrics that utilize language like ‘First user source’ and ‘Session source’. This is used in a number of dimensions, including channel grouping and medium, to differentiate between information specific to the user’s initial acquisition as well as subsequent sessions.

New in GA4:

  • Active Users — Number of users that have been active in a 28 day period
  • Engaged Sessions — Number of sessions that lasted longer than 10 seconds, had a conversion event, or had at least 2 views
  • Engagement Rate — Percentage of total sessions that were engaged sessions
  • Average Engagement Time — Calculated summation of user engagement durations per active user
  • Event Count — Count of triggered events or hits

 

Current GA Attribution Models

 
Data-driven models — Data-driven attribution distributes credit for the conversion based on channel data for each conversion event. It differs from other models because it uses your account’s data to calculate the actual contribution of each click interaction.

Cross-channel rules-based models —These come in a number of formats, dependent on specifics:

  • Last-click gives full credit to the last channel with a click or engagement via YouTube
  • First-click gives full credit to the first channel with a click or engagement via YouTube
  • Linear gives even credit to all channels before conversion
  • Position-based gives 40% credit to each first and last, splitting the remaining 20% across all middle channels
  • Time delay gives more credit the closer the channel is to conversion, using a 7-day half life
  • Ads-preferred model gives 100% credit to the last Google Ads channel clicked through prior to converting

 

How to Migrate to Google Analytics 4 from UA & GA360

 
Because GA4 is an entirely new product, you can’t simply hit an ‘update’ button on your existing Universal Analytics or GA360 property; a new property needs to be created for GA4, and your site will need the appropriate tagging to begin collecting data.

While Google is providing a mirroring service that translates UA tags to GA4, both our and Google’s recommendation is to not rely on this solely.  Due to the inherent differences in data structure, this will likely lead to messy setups; with any errors or issues from the old setup being carried to GA4.  With the introduction of GA4, there’s the opportunity to set yourself up for success in this new age of analytics.

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Some strategic questions you’ll need to answer before implementation include:

  • Should you migrate to server-side tracking?
  • Is your existing Tag Manager or gtag integration collecting all of the data it should?
  • Is your app running the latest version of the Firebase SDK?

 
If you want to have year over year data available in GA4 before the UA and/or GA360 deprecation, a full implementation is required before the respective date for this year (July 1, 2023 for GA360). If not completed by then, GA4 will have gaps that complicate 2023 year-over-year reviews.
 

Web Properties

 
A separate tracking code needs to be added to properties. This can be done within existing Google Tag Manager integrations, with no immediate need for code development on sites that are already successfully running Tag Manager.

Sites without Tag Manager will need to upgrade their site from analytics.js to gtag.js. We recommend considering Tag Manager if this is the case, for ease of implementation for all site tags (not just Analytics).
 

Mobile Applications

 
Existing Firebase SDK integrations will need to be updated to the latest version for Google Analytics 4, and apps without Firebase will need to be implemented.

If you already have the Firebase SDK on your site, make sure you have the latest version and link the app. If your app doesn’t yet have the Firebase SDK, get started in Google Analytics.
 

Best Practices to Make the Most of GA4

 
Data is forward-facing from the date of install, so the sooner you add GA4, the more historical data you’ll have. Adding GA4 to your site now—even if you don’t yet have the time to learn the layout, or decide how you’ll use the insights—is so important because it will start capturing data immediately. GA4 will keep running in the background so that when you are ready to explore its capabilities, you’ll have some statistically significant information to work with.
 

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Take Time to Familiarize Yourself with Newly Available Insights

 
Historically, Google Analytics data has been very pageview-driven, providing information on familiar metrics to include the number of sessions and their average duration, the number of users and new users, bounce rate, and more. The data GA4 provides is more oriented toward understanding the customer lifecycle, to include information regarding acquisition, engagement, monetization, and retention.

In short, GA4 provides an entirely new way of looking at things. And a new way of looking at things can be both wonderful and overwhelming, especially if you’ve been using Google Analytics daily for many years.

Since there are so many changes to the user interface and methodology, the sooner you start planning, the better. Even if basic code is set-up on your site/app in parallel, it will allow users to familiarize themselves with the nuances of the new platform.
 

Have Your Data Cake (and eat it, too)

 
As we mentioned—at least as long as Universal Analytics is still available—you don’t have to choose. For the time being, you can have your data cake and eat it, too.

While you still have 2 profiles—UA or GA360 and GA4—we recommend using them individually and in tandem, understanding which metrics are related, or influence one another. Chances are new connections between dots will present themselves, and those enhanced understandings of how A can impact B can impact C can be invaluable.
 

Should You Make the Switch to GA4?

 
Yes—as soon as possible.

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Once Universal Analytics (UA) is retired, site owners who haven’t yet installed GA4 will be scrambling to get it implemented. We strongly recommend exporting and maintaining hard copies of historical data for your records. Data will not be transferable from UA/GA360 to GA4 properties due to how differently their data models and definitions function and operate. If you need help with this data export, Tinuiti can help!

Avoid the panicked rush by getting your site set-up well ahead of time, especially because GA data is so important. Proper implementation—with time to work out any potential kinks—is crucial; you make a lot of decisions based on GA data, so you need to be sure the information you’re working with is accurate.

With the change of the data model and how data is organized, we’re seeing a shift in how Google Analytics will be best leveraged. GA has historically been among the best ways to view and analyze, while GA4 is far better-positioned to be the nexus point of data, ready to be leveraged, particularly within Tinuiti’s own Mobius ecosystem.
 
Get in touch now to see how Tinuiti can help you assess readiness and migrate to GA4. 
 
Editor’s Note: This post was originally published by Tom Clinton in November 2020 and has been updated for freshness, accuracy, and comprehensiveness.

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Effective Communication in Business as a Crisis Management Strategy

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Effective Communication in Business as a Crisis Management Strategy

Everyday business life is full of challenges. These include data breaches, product recalls, market downturns and public relations conflicts that can erupt at any moment. Such situations pose a significant threat to a company’s financial health, brand image, or even its further existence. However, only 49% of businesses in the US have a crisis communications plan. It is a big mistake, as such a strategy can build trust, minimize damage, and even strengthen the company after it survives the crisis. Let’s discover how communication can transform your crisis and weather the chaos.

The ruining impact of the crisis on business

A crisis can ruin a company. Naturally, it brings losses. But the actual consequences are far worse than lost profits. It is about people behind the business – they feel the weight of uncertainty and fear. Employees start worrying about their jobs, customers might lose faith in the brand they once trusted, and investors could start looking elsewhere. It can affect the brand image and everything you build from the branding, business logo, social media can be ruined. Even after the crisis recovery, the company’s reputation can suffer, and costly efforts might be needed to rebuild trust and regain momentum. So, any sign of a coming crisis should be immediately addressed. Communication is one of the crisis management strategies that can exacerbate the situation.  

The power of effective communication

Even a short-term crisis may have irreversible consequences – a damaged reputation, high employee turnover, and loss of investors. Communication becomes a tool that can efficiently navigate many crisis-caused challenges:

  • Improved trust. Crisis is a synonym for uncertainty. Leaders may communicate trust within the company when the situation gets out of control. Employees feel valued when they get clear responses. The same applies to the customers – they also appreciate transparency and are more likely to continue cooperation when they understand what’s happening. In these times, documenting these moments through event photographers can visually reinforce the company’s messages and enhance trust by showing real, transparent actions.
  • Reputation protection. Crises immediately spiral into gossip and PR nightmares. However, effective communication allows you to proactively address concerns and disseminate true information through the right channels. It minimizes speculation and negative media coverage.
  • Saved business relationships. A crisis can cause unbelievable damage to relationships with employees, customers, and investors. Transparent communication shows the company’s efforts to find solutions and keeps stakeholders informed and engaged, preventing misunderstandings and painful outcomes.
  • Faster recovery. With the help of communication, the company is more likely to receive support and cooperation. This collaborative approach allows you to focus on solutions and resume normal operations as quickly as possible.

It is impossible to predict when a crisis will come. So, a crisis management strategy mitigates potential problems long before they arise.

Tips on crafting an effective crisis communication plan.

To effectively deal with unforeseen critical situations in business, you must have a clear-cut communication action plan. This involves things like messages, FAQs, media posts, and awareness of everyone in the company. This approach saves precious time when the crisis actually hits. It allows you to focus on solving the problem instead of intensifying uncertainty and panic. Here is a step-by-step guide.  

Identify your crisis scenarios.

Being caught off guard is the worst thing. So, do not let it happen. Conduct a risk assessment to pinpoint potential crises specific to your business niche. Consider both internal and external factors that could disrupt normal operations or damage the online reputation of your company. Study industry-specific issues, past incidents, and current trends. How will you communicate in each situation? Knowing your risks helps you prepare targeted communication strategies in advance. Of course, it is impossible to create a perfectly polished strategy, but at least you will build a strong foundation for it.

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Form a crisis response team.

The next step is assembling a core team. It will manage communication during a crisis and should include top executives like the CEO, CFO, and CMO, and representatives from key departments like public relations and marketing. Select a confident spokesperson who will be the face of your company during the crisis. Define roles and responsibilities for each team member and establish communication channels they will work with, such as email, telephone, and live chat. Remember, everyone in your crisis response team must be media-savvy and know how to deliver difficult messages to the stakeholders.

Prepare communication templates.

When a crisis hits, things happen fast. That means communication needs to be quick, too. That’s why it is wise to have ready-to-go messages prepared for different types of crises your company may face. These messages can be adjusted to a particular situation when needed and shared on the company’s social media, website, and other platforms right away. These templates should include frequently asked questions and outline the company’s general responses. Make sure to approve these messages with your legal team for accuracy and compliance.

Establish communication protocols.

A crisis is always chaotic, so clear communication protocols are a must-have. Define trigger points – specific events that would launch the crisis communication plan. Establish a clear hierarchy for messages to avoid conflicting information. Determine the most suitable forms and channels, like press releases or social media, to reach different audiences. Here is an example of how you can structure a communication protocol:

  • Immediate alert. A company crisis response team is notified about a problem.  
  • Internal briefing.  The crisis team discusses the situation and decides on the next steps.  
  • External communication. A spokesperson reaches the media, customers, and suppliers.
  • Social media updates. A trained social media team outlines the situation to the company audience and monitors these channels for misinformation or negative comments.
  • Stakeholder notification. The crisis team reaches out to customers and partners to inform them of the incident and its risks. They also provide details on the company’s response efforts and measures.
  • Ongoing updates. Regular updates guarantee transparency and trust and let stakeholders see the crisis development and its recovery.

Practice and improve.

Do not wait for the real crisis to test your plan. Conduct regular crisis communication drills to allow your team to use theoretical protocols in practice. Simulate different crisis scenarios and see how your people respond to these. It will immediately demonstrate the strong and weak points of your strategy. Remember, your crisis communication plan is not a static document. New technologies and evolving media platforms necessitate regular adjustments. So, you must continuously review and update it to reflect changes in your business and industry.

Wrapping up

The ability to handle communication well during tough times gives companies a chance to really connect with the people who matter most—stakeholders. And that connection is a foundation for long-term success. Trust is key, and it grows when companies speak honestly, openly, and clearly. When customers and investors trust the company, they are more likely to stay with it and even support it. So, when a crisis hits, smart communication not only helps overcome it but also allows you to do it with minimal losses to your reputation and profits.

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Should Your Brand Shout Its AI and Marketing Plan to the World?

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Should Your Brand Shout Its AI and Marketing Plan to the World?

To use AI or not to use AI, that is the question.

Let’s hope things work out better for you than they did for Shakespeare’s mad Danish prince with daddy issues.

But let’s add a twist to that existential question.

CMI’s chief strategy officer, Robert Rose, shares what marketers should really contemplate. Watch the video or read on to discover what he says:

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Should you not use AI and be proud of not using it? Dove Beauty did that last week.

Should you use it but keep it a secret? Sports Illustrated did that last year.

Should you use AI and be vocal about using it? Agency giant Brandtech Group picked up the all-in vibe.

Should you not use it but tell everybody you are? The new term “AI washing” is hitting everywhere.

What’s the best option? Let’s explore.

Dove tells all it won’t use AI

Last week, Dove, the beauty brand celebrating 20 years of its Campaign for Real Beauty, pledged it would NEVER use AI in visual communication to portray real people.

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In the announcement, they said they will create “Real Beauty Prompt Guidelines” that people can use to create images representing all types of physical beauty through popular generative AI programs. The prompt they picked for the launch video? “The most beautiful woman in the world, according to Dove.”

I applaud them for the powerful ad. But I’m perplexed by Dove issuing a statement saying it won’t use AI for images of real beauty and then sharing a branded prompt for doing exactly that. Isn’t it like me saying, “Don’t think of a parrot eating pizza. Don’t think about a parrot eating pizza,” and you can’t help but think about a parrot eating pizza right now?

Brandtech Group says it’s all in on AI

Now, Brandtech Group, a conglomerate ad agency, is going the other way. It’s going all-in on AI and telling everybody.

This week, Ad Age featured a press release — oops, I mean an article (subscription required) — with the details of how Brandtech is leaning into the takeaway from OpenAI’s Sam Altman, who says 95% of marketing work today can be done by AI.

A Brandtech representative talked about how they pitch big brands with two people instead of 20. They boast about how proud they are that its lean 7,000 staffers compete with 100,000-person teams. (To be clear, showing up to a pitch with 20 people has never been a good thing, but I digress.)

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OK, that’s a differentiated approach. They’re all in. Ad Age certainly seemed to like it enough to promote it. Oops, I mean report about it.

False claims of using AI and not using AI

Offshoots of the all-in and never-will approaches also exist.

The term “AI washing” is de rigueur to describe companies claiming to use AI for something that really isn’t AI.  The US Securities and Exchange Commission just fined two companies for using misleading statements about their use of AI in their business model. I know one startup technology organization faced so much pressure from their board and investors to “do something with AI” that they put a simple chatbot on their website — a glorified search engine — while they figured out what they wanted to do.

Lastly and perhaps most interestingly, companies have and will use AI for much of what they create but remain quiet about it or desire to keep it a secret. A recent notable example is the deepfake ad of a woman in a car professing the need for people to use a particular body wipe to get rid of body odor. It was purported to be real, but sharp-eyed viewers suspected the fake and called out the company, which then admitted it. Or was that the brand’s intent all along — the AI-use outrage would bring more attention?

To yell or not to yell about your brand’s AI decision

Should a brand yell from a mountaintop that they use AI to differentiate themselves a la Brandtech? Or should a brand yell they’re never going to use AI to differentiate themselves a la Dove? Or should a brand use it and not yell anything? (I think it’s clear that a brand should not use AI and lie and say it is. That’s the worst of all choices.)

I lean far into not-yelling-from-mountaintop camp.

When I see a CEO proudly exclaim that they laid off 90% of their support workforce because of AI, I’m not surprised a little later when the value of their service is reduced, and the business is failing.

I’m not surprised when I hear “AI made us do it” to rationalize the latest big tech company latest rounds of layoffs. Or when a big consulting firm announces it’s going all-in on using AI to replace its creative and strategic resources.

I see all those things as desperate attempts for short-term attention or a distraction from the real challenge. They may get responses like, “Of course, you had to lay all those people off; AI is so disruptive,” or “Amazing. You’re so out in front of the rest of the pack by leveraging AI to create efficiency, let me cover your story.” Perhaps they get this response, “Your company deserves a bump in stock price because you’re already using this fancy new technology.”

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But what happens if the AI doesn’t deliver as promoted? What happens the next time you need to lay off people? What happens the next time you need to prove your technologically forward-leaning?

Yelling out that you’re all in on a disruptive innovation, especially one the public doesn’t yet trust a lot is (at best) a business sugar high. That short-term burst of attention may or may not foul your long-term brand value.

Interestingly, the same scenarios can manifest when your brand proclaims loudly it is all out of AI, as Dove did. The sugar high may not last and now Dove has itself into a messaging box. One slip could cause distrust among its customers. And what if AI gets good at demonstrating diversity in beauty?

I tried Dove’s instructions and prompted ChatGPT for a picture of “the most beautiful woman in the world according to the Dove Real Beauty ad.”

It gave me this. Then this. And this. And finally, this.

She’s absolutely beautiful, but she doesn’t capture the many facets of diversity Dove has demonstrated in its Real Beauty campaigns. To be clear, Dove doesn’t have any control over generating the image. Maybe the prompt worked well for Dove, but it didn’t for me. Neither Dove nor you can know how the AI tool will behave.

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To use AI or not to use AI?

When brands grab a microphone to answer that question, they work from an existential fear about the disruption’s meaning. They do not exhibit the confidence in their actions to deal with it.

Let’s return to Hamlet’s soliloquy:

Thus conscience doth make cowards of us all;

And thus the native hue of resolution

Is sicklied o’er with the pale cast of thought,

And enterprises of great pith and moment

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With this regard their currents turn awry

And lose the name of action.

In other words, Hamlet says everybody is afraid to take real action because they fear the unknown outcome. You could act to mitigate or solve some challenges, but you don’t because you don’t trust yourself.

If I’m a brand marketer for any business (and I am), I’m going to take action on AI for my business. But until I see how I’m going to generate value with AI, I’m going to be circumspect about yelling or proselytizing how my business’ future is better.

Want more content marketing tips, insights, and examples? Subscribe to workday or weekly emails from CMI.

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Cover image by Joseph Kalinowski/Content Marketing Institute

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How to Use AI For a More Effective Social Media Strategy, According to Ross Simmonds

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How to Use AI For a More Effective Social Media Strategy, According to Ross Simmonds

Welcome to Creator Columns, where we bring expert HubSpot Creator voices to the Blogs that inspire and help you grow better.

It’s the age of AI, and our job as marketers is to keep up.

My team at Foundation Marketing recently conducted an AI Marketing study surveying hundreds of marketers, and more than 84% of all leaders, managers, SEO experts, and specialists confirmed that they used AI in the workplace.

AI in the workplace data graphic, Foundation Labs

If you can overlook the fear-inducing headlines, this technology is making social media marketers more efficient and effective than ever. Translation: AI is good news for social media marketers.

Download Now: The 2024 State of Social Media Trends [Free Report]

In fact, I predict that the marketers not using AI in their workplace will be using it before the end of this year, and that number will move closer and closer to 100%.

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Social media and AI are two of the most revolutionizing technologies of the last few decades. Social media has changed the way we live, and AI is changing the way we work.

So, I’m going to condense and share the data, research, tools, and strategies that the Foundation Marketing Team and I have been working on over the last year to help you better wield the collective power of AI and social media.

Let’s jump into it.

What’s the role of AI in social marketing strategy?

In a recent episode of my podcast, Create Like The Greats, we dove into some fascinating findings about the impact of AI on marketers and social media professionals. Take a listen here:

Let’s dive a bit deeper into the benefits of this technology:

Benefits of AI in Social Media Strategy

AI is to social media what a conductor is to an orchestra — it brings everything together with precision and purpose. The applications of AI in a social media strategy are vast, but the virtuosos are few who can wield its potential to its fullest.

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AI to Conduct Customer Research

Imagine you’re a modern-day Indiana Jones, not dodging boulders or battling snakes, but rather navigating the vast, wild terrain of consumer preferences, trends, and feedback.

This is where AI thrives.

Using social media data, from posts on X to comments and shares, AI can take this information and turn it into insights surrounding your business and industry. Let’s say for example you’re a business that has 2,000 customer reviews on Google, Yelp, or a software review site like Capterra.

Leveraging AI you can now have all 2,000 of these customer reviews analyzed and summarized into an insightful report in a matter of minutes. You simply need to download all of them into a doc and then upload them to your favorite Generative Pre-trained Transformer (GPT) to get the insights and data you need.

But that’s not all.

You can become a Prompt Engineer and write ChatGPT asking it to help you better understand your audience. For example, if you’re trying to come up with a persona for people who enjoy marathons but also love kombucha you could write a prompt like this to ChatGPT:

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ChatGPT prompt example

The response that ChatGPT provided back is quite good:

GPT response example

Below this it went even deeper by including a lot of valuable customer research data:

  • Demographics
  • Psychographics
  • Consumer behaviors
  • Needs and preferences

And best of all…

It also included marketing recommendations.

The power of AI is unbelievable.

Social Media Content Using AI

AI’s helping hand can be unburdening for the creative spirit.

Instead of marketers having to come up with new copy every single month for posts, AI Social Caption generators are making it easier than ever to craft catchy status updates in the matter of seconds.

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Tools like HubSpot make it as easy as clicking a button and telling the AI tool what you’re looking to create a post about:

AI social media caption generator step 1

The best part of these AI tools is that they’re not limited to one channel.

Your AI social media content assistant can help you with LinkedIn content, X content, Facebook content, and even the captions that support your post on Instagram.

It can also help you navigate hashtags:

AI social media hashtags generator example, HubSpot

With AI social media tools that generate content ideas or even write posts, it’s not about robots replacing humans. It’s about making sure that the human creators on your team are focused on what really matters — adding that irreplaceable human touch.

Enhanced Personalization

You know that feeling when a brand gets you, like, really gets you?

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AI makes that possible through targeted content that’s tailored with a level of personalization you’d think was fortune-telling if the data didn’t paint a starker, more rational picture.

What do I mean?

Brands can engage more quickly with AI than ever before. In the early 2000s, a lot of brands spent millions of dollars to create social media listening rooms where they would hire social media managers to find and engage with any conversation happening online.

Thanks to AI, brands now have the ability to do this at scale with much fewer people all while still delivering quality engagement with the recipient.

Analytics and Insights

Tapping into AI to dissect the data gives you a CSI-like precision to figure out what works, what doesn’t, and what makes your audience tick. It’s the difference between guessing and knowing.

The best part about AI is that it can give you almost any expert at your fingertips.

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If you run a report surrounding the results of your social media content strategy directly from a site like LinkedIn, AI can review the top posts you’ve shared and give you clear feedback on what type of content is performing, why you should create more of it, and what days of the week your content is performing best.

This type of insight that would typically take hours to understand.

Now …

Thanks to the power of AI you can upload a spreadsheet filled with rows and columns of data just to be met with a handful of valuable insights a few minutes later.

Improved Customer Service

Want 24/7 support for your customers?

It’s now possible without human touch.

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Chatbots powered by AI are taking the lead on direct messaging experiences for brands on Facebook and other Meta properties to offer round-the-clock assistance.

The fact that AI can be trained on past customer queries and data to inform future queries and problems is a powerful development for social media managers.

Advertising on Social Media with AI

The majority of ad networks have used some variation of AI to manage their bidding system for years. Now, thanks to AI and its ability to be incorporated in more tools, brands are now able to use AI to create better and more interesting ad campaigns than ever before.

Brands can use AI to create images using tools like Midjourney and DALL-E in seconds.

Brands can use AI to create better copy for their social media ads.

Brands can use AI tools to support their bidding strategies.

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The power of AI and social media is continuing to evolve daily and it’s not exclusively found in the organic side of the coin. Paid media on social media is being shaken up due to AI just the same.

How to Implement AI into Your Social Media Strategy

Ready to hit “Go” on your AI-powered social media revolution?

Don’t just start the engine and hope for the best. Remember the importance of building a strategy first. In this video, you can learn some of the most important factors ranging from (but not limited to) SMART goals and leveraging influencers in your day-to-day work:

The following seven steps are crucial to building a social media strategy:

  1. Identify Your AI and Social Media Goals
  2. Validate Your AI-Related Assumptions
  3. Conduct Persona and Audience Research
  4. Select the Right Social Channels
  5. Identify Key Metrics and KPIs
  6. Choose the Right AI Tools
  7. Evaluate and Refine Your Social Media and AI Strategy

Keep reading, roll up your sleeves, and follow this roadmap:

1. Identify Your AI and Social Media Goals

If you’re just dipping your toes into the AI sea, start by defining clear objectives.

Is it to boost engagement? Streamline your content creation? Or simply understand your audience better? It’s important that you spend time understanding what you want to achieve.

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For example, say you’re a content marketing agency like Foundation and you’re trying to increase your presence on LinkedIn. The specificity of this goal will help you understand the initiatives you want to achieve and determine which AI tools could help you make that happen.

Are there AI tools that will help you create content more efficiently? Are there AI tools that will help you optimize LinkedIn Ads? Are there AI tools that can help with content repurposing? All of these things are possible and having a goal clearly identified will help maximize the impact. Learn more in this Foundation Marketing piece on incorporating AI into your content workflow.

Once you have identified your goals, it’s time to get your team on board and assess what tools are available in the market.

Recommended Resources:

2. Validate Your AI-Related Assumptions

Assumptions are dangerous — especially when it comes to implementing new tech.

Don’t assume AI is going to fix all your problems.

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Instead, start with small experiments and track their progress carefully.

3. Conduct Persona and Audience Research

Social media isn’t something that you can just jump into.

You need to understand your audience and ideal customers. AI can help with this, but you’ll need to be familiar with best practices. If you need a primer, this will help:

Once you understand the basics, consider ways in which AI can augment your approach.

4. Select the Right Social Channels

Not every social media channel is the same.

It’s important that you understand what channel is right for you and embrace it.

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The way you use AI for X is going to be different from the way you use AI for LinkedIn. On X, you might use AI to help you develop a long-form thread that is filled with facts and figures. On LinkedIn however, you might use AI to repurpose a blog post and turn it into a carousel PDF. The content that works on X and that AI can facilitate creating is different from the content that you can create and use on LinkedIn.

The audiences are different.

The content formats are different.

So operate and create a plan accordingly.

Recommended Tools and Resources:

5. Identify Key Metrics and KPIs

What metrics are you trying to influence the most?

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Spend time understanding the social media metrics that matter to your business and make sure that they’re prioritized as you think about the ways in which you use AI.

These are a few that matter most:

  • Reach: Post reach signifies the count of unique users who viewed your post. How much of your content truly makes its way to users’ feeds?
  • Clicks: This refers to the number of clicks on your content or account. Monitoring clicks per campaign is crucial for grasping what sparks curiosity or motivates people to make a purchase.
  • Engagement: The total social interactions divided by the number of impressions. This metric reveals how effectively your audience perceives you and their readiness to engage.

Of course, it’s going to depend greatly on your business.

But with this information, you can ensure that your AI social media strategy is rooted in goals.

6. Choose the Right AI Tools

The AI landscape is filled with trash and treasure.

Pick AI tools that are most likely to align with your needs and your level of tech-savviness.

For example, if you’re a blogger creating content about pizza recipes, you can use HubSpot’s AI social caption generator to write the message on your behalf:

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AI social media generator example

The benefit of an AI tool like HubSpot and the caption generator is that what at one point took 30-40 minutes to come up with — you can now have it at your fingertips in seconds. The HubSpot AI caption generator is trained on tons of data around social media content and makes it easy for you to get inspiration or final drafts on what can be used to create great content.

Consider your budget, the learning curve, and what kind of support the tool offers.

7. Evaluate and Refine Your Social Media and AI Strategy

AI isn’t a magic wand; it’s a set of complex tools and technology.

You need to be willing to pivot as things come to fruition.

If you notice that a certain activity is falling flat, consider how AI can support that process.

Did you notice that your engagement isn’t where you want it to be? Consider using an AI tool to assist with crafting more engaging social media posts.

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Make AI Work for You — Now and in the Future

AI has the power to revolutionize your social media strategy in ways you may have never thought possible. With its ability to conduct customer research, create personalized content, and so much more, thinking about the future of social media is fascinating.

We’re going through one of the most interesting times in history.

Stay equipped to ride the way of AI and ensure that you’re embracing the best practices outlined in this piece to get the most out of the technology.

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