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Google Analytics 4 Should Trigger Reorganizations & Agency Reviews

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By now, you may already know that GA4 operates across platforms, uses an event-based data model to deliver user-centric measurement, and does not rely exclusively on cookies.

And you recognize that GA4 uses machine learning to generate sophisticated predictive insights about user behavior and conversions, create new audiences of users likely to purchase or churn, and automatically surface critical insights to improve your marketing.

Heck, you may have already started to move to GA4 as soon as possible to build the necessary historical data before Universal Analytics (UA) stops processing new hits on July 1, 2023, and UA 360 stops new hit processing on Oct. 1, 2023.

Many people may mistakenly think they have a good bead on things.

Well, I was at Pubcon Las Vegas on Nov. 14, 2005, when Google announced that Urchin Software, which it had acquired in April of that year, was being renamed Google Analytics. Yep, I was in the room where it happened.

I was standing next to one of my clients, John Marshall, the CEO of ClickTracks Analytics, which offered a range of competing solutions that cost $495, $1,195, or $3,495.

That’s when we both heard that the basic version of Google Analytics was free for the first time.

So, I know a little something about the impact of new versions of Google’s web analytics service.

And, I’ve learned that you don’t need to wait for machine learning to generate sophisticated predictive insights about a couple of “events” that the adoption of GA4 is likely to trigger for your organization or clients in the next 14 months.

One is a reorganization. The other is an agency review.

The Reorg

The “web analytics” team still sits in the IT department in far too many organizations.

Why?

Because the team was originally created back in 1995 when web analytics meant servers, log files, and complex handwritten code to parse the log files and pump out reports.

So, putting them in the IT department made perfect sense back then.

But, data collection, storage, and processing have all moved into the cloud (hosted by your application service provider rather than in-house).

This eliminated the need to maintain IT teams for web analytics, except perhaps to update measurement codes and related code fragments collectively known as “tags” on your website or mobile app.

In addition, your website itself has transformed from being “brochure-ware” back in the early days into an increasingly integral part of your business – both online and offline.

Nothing highlights this change more than the fact that we no longer count the number of client requests (or hits) made to the web server like they did a generation ago.

Because of these trends, the “digital analytics” team doesn’t belong in IT anymore.

Where does it belong?

Well, ask yourself three questions:

Who uses analytics?

Marketing (not IT) needs to see unified customer journeys across their websites and apps.

Marketing (not IT) needs to use Google’s machine learning technology to the surface and predict new insights.

And marketing (not IT) needs to keep up with evolving customer needs and expectations.

Who directs implementation?

Marketing (not IT) needs to decide which recommended events to add, which suggested audiences to use, and which events to mark as conversions.

Marketing (not IT) needs to decide what associate monetary values to use for micro-conversions, custom insights to create, and anomalies to act on.

And marketing (not IT) should decide which other platforms, such as Google Ads, Search Console, and Salesforce Marketing Cloud, to integrate with GA4.

Who owns reporting?

Marketing (not IT) needs to drive sales or app installs, generate leads, or connect online and offline customer engagement.

So, marketing (not IT) needs to use data-driven attribution to analyze the full impact of their latest campaigns and ongoing programs across the customer journey.

And marketing (not IT) needs to export that analysis to Google Ads and the Google Marketing Platform’s media tools to optimize those campaigns and programs.

This is why digital analytics belongs in marketing – and it has belonged there for more than 10 years.

But, inertia is a powerful force – and most people hate reorgs – which explains why far too many organizations are loath to move their analytics team out of IT and into marketing.

So, why do I think that GA4 will be the irresistible force to overcome this immovable object?

Well, one of the features that you’ve already heard about is Analytics Intelligence, which uses machine learning and conditions that you need to configure to help you understand and act on your GA4 data.

And one of the statistical techniques that Analytics Intelligence uses is Anomaly detection.

Using historical data, Analytics Intelligence “learns” to predict the value of metrics for the current time period and flags any data points as anomalies if their actual value falls outside a “credible” interval.

For detection of weekly anomalies, the training period for GA4’s machine learning is 32 weeks.

For detection of daily anomalies, the training period is 90 days. And for the detection of hourly anomalies, the training period is two weeks.

In other words, somewhere between 2 and 32 weeks after GA4 is set up and starts collecting data, Analytics Intelligence’s machine learning will be sufficiently trained to analyze your data and predict future actions that your end-users may take.

That’s when marketers will begin seeing “Insights” appear on their GA4 Home page.

These Insights will show unusual changes, emerging trends, and other anomalies about your site or app.

Seeing specific Insights can help you quickly identify data changes that warrant further analysis and action.

That’s when the marketing department will start “freaking out” if the IT department doesn’t respond to urgent requests for “help” within a week, a day, or even an hour.

And that’s when the business case for moving the analytics team from IT to Marketing will suddenly become data-driven.

Why is this scenario likely to ripple across organizations worldwide over the next 14 months?

Well, early adopters of GA4 have already reported the benefits of getting a complete view of their customer lifecycle with an event-based measurement model that isn’t fragmented by platform or organized into independent sessions.

And I’d argue that the same benefits are available to an organization that isn’t fragmented by department or organized into independent silos.

For example, Gymshark, a fitness apparel and accessories brand based in the UK, used GA4 to understand its customers across touchpoints on its website and app.

This enabled the Gymshark team to see how users moved through the purchase funnel. As a result, they reduced their user drop off by 9%, increased their product page clickthroughs by 5%, and reduced their time spent on user journey analysis by 30%.

Oh, and non-profits can benefit from seeing the user journey from end to end, too.

For example, 412 Food Rescue, a non-profit organization based in Pittsburgh, needed to recruit more volunteers to deliver food from retailers to people experiencing food insecurity.

Automated Insights in GA4 showed their team that weekends tended to be a little bit slower in terms of volunteers and engagement, so they adjusted the social media campaigns that were driving traffic to their website.

And they’ve cut their reporting time by 50%, which has freed up their already limited staff to grow their impact throughout the community and expand to new cities.

Watch “Google Analytics: 412 Food Rescue Case Study”, which was uploaded to YouTube on Mar. 24, 2021, to hear the team tell their story in their own words.

This brings us to the second “event” that GA4 is likely to trigger for your organization or clients: An agency review.

Agency Review

Now, some big ad agencies were using Google Analytics with DoubleClick’s advertising services, which Google Acquired in March 2008, even before the Google Marketing Platform was launched on July 24, 2018.

So, they should weather the storm created by the move to GA4 without too much difficulty.

But, many other ad agencies will need to hold an “all hands on deck” meeting to figure out how to hang on to a client that’s just configured their GA4 property and started recording YouTube Web Engaged View Conversion (EVC) events.

To do that, the client:

  • Linked their property to Google Ads to make YouTube Web EVCs available in their GA4 reports.
  • Activated Google signals to see conversions from users who are signed in to their Google accounts.

Now, they expect their agency to help them do what Harmoney did.

Who is Harmoney?

They’re an online personal loan platform based in New Zealand.

What did they do? They used YouTube to build brand awareness of its target audience in Australia.

How does Harmoney know that they did that?

Well, they used GA4 to measure EVCs after their target audience watched their YouTube ads.

This enabled them to directly correlate the uplift in brand impressions to their investment by measuring the engaged-view conversions from their YouTube ads, which often occur in mobile apps.

Or, what if a client asks your agency for new ads that target one of their “Predictive audiences.”

For example, let’s say your client has built an audience of “likely 7-day purchasers,” which includes users likely to purchase in the next seven days.

Now, they assume that your agency can help them do what McDonald’s Hong Kong did.

Umm, what was that?

Well, McDonald’s Hong Kong met its goal of growing mobile orders using a predictive audience of “likely” 7-day purchasers.” They exported it to Google Ads – and increased their app orders more than six times.

They also saw a 2.3 times stronger ROI, a 5.6 times increase in revenue, and a 63% reduction in cost per action.

Or, another client may want your agency to create a remarketing campaign to re-engage users based on their behavior on their site or their app.

What will your agency do when it’s handed a remarketing list of “Suggested audiences,” which can include:

  • Achievers (e.g., users reach key milestones like reading a certain number of articles).
  • Billable users.
  • Cart abandoners.
  • Checkout starters.
  • Item searchers.
  • Item viewers.
  • Leads.
  • Registered users.
  • Searchers.
  • Streamers.
  • Top players.
  • Top scorers.
  • Tutorial abandoners.
  • Tutorial finishers.
  • Video completers.
  • Video starters.
  • Wishlist users.

Hey, you can’t make this stuff up.

So, what will you do?

Well, my scientific wild-ass guess is your agency will act like a swan, gracefully gliding across a lake – while furiously paddling beneath the water’s surface.

But, if you don’t convince everyone at your agency that GA4 will fundamentally change client expectations of what ad agencies should be able to do, then you’re likely to lose those clients.

I don’t suppose you know what clients will expect your ad agency should be able to do, do you?

Aw, wait. That was on Final Jeopardy! last night.

Mayim Bialik said…clients now expect their ad agencies to be able to use the front end of the Google Marketing Platform to leverage what the back end of the platform (the part formerly known as Google Analytics) can provide…which now includes measuring YouTube Web EVC events, generating Predictive audiences, and creating Suggested audiences.

So, don’t be surprised when your client announces an agency review.

And even if your agency is invited to compete, don’t expect to hang on to this account – unless you’ve figured out how to defeat some of the big ad agencies using the Google Marketing Platform since March 2008.

So, for the inevitable agency review that will be triggered by GA4, I’d recommend that you organize your presentation to address the five best practices that DoubleClick once called “programmatic advertising” and Google now calls “the latest advances in machine learning for data-driven creative.”

In case you haven’t learned these five best practices yet, they are:

  • Organize audience insights: Aggregate your data sources – including GA4 data, offline data, CRM data, survey data, or third-party data – to get a comprehensive view of your audience.
  • Design compelling creative: Google encourages marketers to “establish a general campaign plan and align your creative, analytics, and media teams as early as possible. This allows the creative team to tailor messages appropriately for different channels and devices; it will also make it easier to ensure creative assets can work across them.”
  • Execute with integrated technology: Identify a capable partner for programmatic buying. For example, you’ll find 2,424 potential partners in the Google Partners Directory.
  • Reach audiences across screens: According to eMarketer, U.S. advertisers are expected to spend $62.96 billion on programmatic digital video in 2022, up from $52.17 billion in 2021. And mobile represents two-thirds of programmatic video advertising, but its share is declining as connected TV (CTV) earns more ad dollars.
  • Measure the impact: Use GA4 to measure EVCs after your target audience watches your YouTube ads, grow mobile orders using a Predictive audience of “likely 7-day purchasers,” and lastly, remarket to “Suggested audiences.”

Now, some of the big ad agencies have more experience executing with integrated technology and reaching audiences across screens.

That’s why you may need to identify a capable partner for programmatic buying before the agency review.

But, even the big ad agencies are still learning about GA4 just like you are.

So, I’d argue that you should be able to hold your ground when organizing audience insights and measuring the impact.

And, the one area where you may have an advantage over even some of the big ad agencies is designing compelling creative.

So, here’s what you need to emphasize at the beginning of the agency review: Creative accounts for 56% of advertising effectiveness, and media 30%, according to Nielsen Catalina.

Okay, how do you design compelling creative for programmatic digital video?

First, I recommend that you watch “Understanding the ABCD guidelines for effective YouTube ads.”

It explains that successful ads on YouTube grab Attention, incorporate strong Branding, build a Connection, and have a strong Direction.

A second approach uses emotional AI to correlate creative attributes with video performance data.

How do you do that?

Well, read my article, “What’s the Alternative to Spending $7 Million on a Super Bowl Ad?

The first digital marketing expert to respond to my request for alternatives was Ian Forrester, the founder and CEO of DAIVID. He used his video testing tool, which uses Emotional AI to automatically predict video performance without the need to show creative to respondents.

A third option is to use YouTube Director Mix to create customized videos at scale, swapping out different elements to tailor content to specific audiences.

For example, Mondelez India designed “The Not Just a Cadbury Ad,” employing YouTube Pin Code Targeting, YouTube Director’s Mix, and Google Maps API.

This enabled them to produce thousands of customized AI-generated ads to 270 pin codes across eight cities.

This hyper-localized campaign helped nearly 1,800 local retailers grab business during Diwali during the pandemic.

It delivered incredible business results, including over 32% more business growth against what was forecasted and 2x sales for the retailers featured in the ads.

The fourth way is to create a video experiment to determine which of your video ads is more effective on YouTube.

With a video experiment, you can test different video ads with the same audience and then use the experiment results to determine which ad resonates more with your audience.

For example, Grammarly used Video Experiments to test ad sequences.

To see their results, watch “Grammarly | Success Story | YouTube Advertisers.”

And now for something completely different.

Instead of letting GA4 prompt an agency review, preemptively urge your clients to conduct a digital analytics review.

Matt Bailey, who teaches people how to turn marketing data into action, says:

“I’ve been talking with Adobe, and they’ve seen an incredible surge in inquiries and changeovers. With the privacy issues and Google being the world’s biggest data vacuum, I’ve decided it’s time to make a change as well. I’m loving that the analytics landscape is once again becoming a financially competitive environment!”

He adds, “I’ve been testing Matomo, Woopra, Heap, and Piwik Pro. They all have similar features as G4. The problem is that G4 still isn’t finished. They keep adding measurements and changing labels. Just two weeks ago, they added a new measurement that trashed any historical data associated with it.”

So, which of these options should you use?

Well, before David went to fight Goliath, he stopped by a brook to select five smooth stones.

And, all David needed to slay Goliath was one smooth stone.

So, here’s what you should emphasize at the end of the agency review: If an agency uses integrated technology to reach audiences across screens with creative that isn’t compelling, then the only thing you will measure is the lack of impact.

My colleagues at Search Engine Journal have already done a great job preparing you to be successful with Google Analytics 4 (GA4). Check out these resources if you haven’t yet:


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Twitter Will Share Ad Revenue With Twitter Blue Verified Creators

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Twitter Will Share Ad Revenue With Twitter Blue Verified Creators

Elon Musk, owner and CEO of Twitter, announced that starting today, Twitter will share ad revenue with creators. The new policy applies only to ads that appear in a creator’s reply threads.

The move comes on the heels of YouTube launching ad revenue sharing for creators through the YouTube Partner Program in a bid to become the most rewarding social platform for creators.

Social networks like Instagram, TikTok, and Snapchat have similar monetization options for creators who publish reels and video content. For example, Instagram’s Reels Play Bonus Program offers eligible creators up to $1,200 for Reel views.

The catch? Unlike other social platforms, creators on Twitter must have an active subscription to Twitter Blue and meet the eligibility requirements for the Blue Verified checkmark.

The following is an example of a Twitter ad in a reply thread (Promoted by @ASUBootcamps). It should generate revenue for the Twitter Blue Verified creator (@rowancheung), who created the thread.

Screenshot from Twitter, January 2023

To receive the ad revenue share, creators would have to pay $8 per month (or more) to maintain an active Twitter Blue subscription. Twitter Blue pricing varies based on location and is available in the United States, Canada, Australia, New Zealand, Japan, the United Kingdom, Saudi Arabia, France, Germany, Italy, Portugal, and Spain.

Eligibility for the Twitter Blue Verified checkmark includes having an active Twitter Blue subscription and meeting the following criteria.

  • Your account must have a display name, profile photo, and confirmed phone number.
  • Your account has to be older than 90 days and active within the last 30 days.
  • Recent changes to your account’s username, display name, or profile photo can affect eligibility. Modifications to those after verification can also result in a temporary loss of the blue checkmark until Twitter reviews your updated information.
  • Your account cannot appear to mislead or deceive.
  • Your account cannot spam or otherwise try to manipulate the platform for engagement or follows.

Did you receive a Blue Verified checkmark before the Twitter Blue subscription? That will not help creators who want a share of the ad revenue. The legacy Blue Verified checkmark does not make a creator account eligible for ad revenue sharing.

When asked about accounts with a legacy and Twitter Blue Verified checkmark, Musk tweeted that the legacy Blue Verified is “deeply corrupted” and will sunset in just a few months.

Regardless of how you gained your checkmark, it’s important to note that Twitter can remove a checkmark without notice.

In addition to ad revenue sharing for Twitter Blue Verified creators, Twitter Dev announced that the Twitter API would no longer be free in an ongoing effort to reduce the number of bots on the platform.

While speculation looms about a loss in Twitter ad revenue, the Wall Street Journal reported a “fire-sale” Super Bowl offer from Musk to win back advertisers.

The latest data from DataReportal shows a positive trend for Twitter advertisers. Ad reach has increased from 436.4 million users in January 2022 to 556 million in January 2023.

Twitter is also the third most popular social network based on monthly unique visitors and page views globally, according to SimilarWeb data through December 2022.


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AI Content Detection Software: Can They Detect ChatGPT?

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AI Content Detection Software: Can They Detect ChatGPT?

We live in an age when AI technologies are booming, and the world has been taken by storm with the introduction of ChatGPT.

ChatGPT is capable of accomplishing a wide range of tasks, but one that it does particularly well is writing articles. And while there are many obvious benefits to this, it also presents a number of challenges.

In my opinion, the biggest hurdle that AI-generated written content poses for the publishing industry is the spread of misinformation.

ChatGPT, or any other AI tool, may generate articles that may contain factual errors or are just flat-out incorrect.

Imagine someone who has no expertise in medicine starting a medical blog and using ChatGPT to write content for their articles.

Their content may contain errors that can only be identified by professional doctors. And if that blog content starts spreading over social media, or maybe even ranks in Search, it could cause harm to people who read it and take erroneous medical advice.

Another potential challenge ChatGPT poses is how students might leverage it within their written work.

If one can write an essay just by running a prompt (and without having to do any actual work), that greatly diminishes the quality of education – as learning about a subject and expressing your own ideas is key to essay writing.

Even before the introduction of ChatGPT, many publishers were already generating content using AI. And while some honestly disclose it, others may not.

Also, Google recently changed its wording regarding AI-generated content, so that it is not necessarily against the company’s guidelines.

Image from Twitter, November 2022

This is why I decided to try out existing tools to understand where the tech industry is when it comes to detecting content generated by ChatGPT, or AI generally.

I ran the following prompts in ChatGPT to generate written content and then ran those answers through different detection tools.

  • “What is local SEO? Why it is important? Best practices of Local SEO.”
  • “Write an essay about Napoleon Bonaparte invasion of Egypt.”
  • “What are the main differences between iPhone and Samsung galaxy?”

Here is how each tool performed.

1. Writer.com

For the first prompt’s answer, Writer.com fails, identifying ChatGPT’s content as 94% human-generated.

Writer.com resultsScreenshot from writer.com, January 2023

For the second prompt, it worked and detected it as AI-written content.

Writer.com test resultScreenshot from writer.com, January 2023

For the third prompt, it failed again.

Sample ResultScreenshot from writer.com, January 2023

However, when I tested real human-written text, Writer.com did identify it as 100% human-generated very accurately.

2. Copyleaks

Copyleaks did a great job in detecting all three prompts as AI-written.

Sample ResultScreenshot from Copyleaks, January 2023

3. Contentatscale.ai

Contentatscale.ai did a great job in detecting all three prompts as AI-written, even though the first prompt, it gave a 21% human score.

Contentscale.aiScreenshot from Contentscale.ai, January 2023

4. Originality.ai

Originality.ai did a great job on all three prompts, accurately detecting them as AI-written.

Also, when I checked with real human-written text, it did identify it as 100% human-generated, which is essential.

Originality.aiScreenshot from Originality.ai, January 2023

You will notice that Originality.ai doesn’t detect any plagiarism issues. This may change in the future.

Over time, people will use the same prompts to generate AI-written content, likely resulting in a number of very similar answers. When these articles are published, they will then be detected by plagiarism tools.

5. GPTZero

This non-commercial tool was built by Edward Tian, and specifically designed to detect ChatGPT-generated articles. And it did just that for all three prompts, recognizing them as AI-generated.

GPTZeroScreenshot from GPTZero, January 2023

Unlike other tools, it gives a more detailed analysis of detected issues, such as sentence-by-sentence analyses.

sentence by sentence text perplexityScreenshot from GPTZero, January 2023

OpenAI’s AI Text Classifier

And finally, let’s see how OpenAi detects its own generated answers.

For the 1st and 3rd prompts, it detected that there is an AI involved by classifying it as “possibly-AI generated”.

AI Text Classifier. Likely AI-generatedAI Text Classifier. Likely AI-generated

But surprisingly, it failed for the 2nd prompt and classified that as “unlikely AI-generated.” I did play with different prompts and found that, as of the moment, when checking it, few of the above tools detect AI content with higher accuracy than OpenAi’s own tool.

AI Text Classifier. Unlikely AI-generatedAI Text Classifier. Unlikely AI-generated

As of the time of this check, they had released it a day before. I think in the future, they will fine tune it, and it will work much better.

Conclusion

Current AI content generation tools are in good shape and are able to detect ChatGPT-generated content (with varying degrees of success).

It is still possible for someone to generate copy via ChatGPT and then paraphrase that to make it undetectable, but that might require almost as much work as writing from scratch – so the benefits aren’t as immediate.

If you think about ranking an article in Google written by ChatGPT, consider for a moment: If the tools we looked at above were able to recognize them as AI-generated, then for Google, detecting them should be a piece of cake.

On top of that, Google has quality raters who will train their system to recognize AI-written articles even better by manually marking them as they find them.

So, my advice would be not to build your content strategy on ChatGPT-generated content, but use it merely as an assistant tool.

More resources: 


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Five things you need to know about content optimization in 2023

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5 Things You Need To Know About Optimizing Content in 2023

30-second summary:

  • As the content battleground goes through tremendous upheaval, SEO insights will continue to grow in importance
  • ChatGPT can help content marketers get an edge over their competition by efficiently creating and editing high-quality content
  • Making sure your content rank high enough to engage the target audience requires strategic planning and implementation

Google is constantly testing and updating its algorithms in pursuit of the best possible searcher experience. As the search giant explains in its ‘How Search Works’ documentation, that means understanding the intent behind the query and bringing back results that are relevant, high-quality, and accessible for consumers.

As if the constantly shifting search landscape weren’t difficult enough to navigate, content marketers are also contending with an increasingly technology-charged environment. Competitors are upping the stakes with tools and platforms that generate smarter, real-time insights and even make content optimization and personalization on the fly based on audience behavior, location, and data points.

Set-it-and-forget-it content optimization is a thing of the past. Here’s what you need to know to help your content get found, engage your target audience, and convert searchers to customers in 2023.

AI automation going to be integral for content optimization

Technologies-B2B-organizations-use-to-optimize-content

As the content battleground heats up, SEO insights will continue to grow in importance as a key source of intelligence. We’re optimizing content for humans, not search engines, after all – we had better have a solid understanding of what those people need and want.

While I do not advocate automation for full content creation, I believe next year – as resources become stretched automation will have a bigger impact on helping with content optimization of existing content.

CHATGPT

ChatGPT, developed by OpenAI, is a powerful language generation model that leverages the Generative Pre-trained Transformer (GPT) architecture to produce realistic human-like text. With Chat GPT’s wide range of capabilities – from completing sentences and answering questions to generating content ideas or powering research initiatives – it can be an invaluable asset for any Natural Language Processing project.

ChatGPT-for-content

The introduction on ChatGPT has caused considerable debate and explosive amounts of content on the web. With ChatGPT, content marketers can achieve an extra edge over their competition by efficiently creating and editing high-quality content. It offers assistance with generating titles for blog posts, summaries of topics or articles, as well as comprehensive campaigns when targeting a specific audience.

However, it is important to remember that this technology should be used to enhance human creativity rather than completely replacing it.

For many years now AI-powered technology has been helping content marketers and SEOs automate repetitive tasks such as data analysis, scanning for technical issues, and reporting, but that’s just the tip of the iceberg. AI also enables real-time analysis of a greater volume of consumer touchpoints and behavioral data points for smarter, more precise predictive analysis, opportunity forecasting, real-time content recommendations, and more.

With so much data in play and recession concerns already impacting 2023 budgets in many organizations, content marketers will have to do more with less this coming year. You’ll need to carefully balance human creative resources with AI assists where they make sense to stay flexible, agile, and ready to respond to the market.

It’s time to look at your body of content as a whole

Google’s Helpful Content update, which rolled out in August, is a sitewide signal targeting a high proportion of thin, unhelpful, low-quality content. That means the exceptional content on your site won’t rank to their greatest potential if they’re lost in a sea of mediocre, outdated assets.

It might be time for a content reboot – but don’t get carried away. Before you start unpublishing and redirecting blog posts, lean on technology for automated site auditing and see what you can fix up first. AI-assisted technology can help sniff out on-page elements, including page titles and H1 tags, and off-page factors like page speed, redirects, and 404 errors that can support your content refreshing strategy.

Focus on your highest trafficked and most visible pages first, i.e.: those linked from the homepage or main menu. Google’s John Mueller confirmed recently that if the important pages on your website are low quality, it’s bad news for the entire site. There’s no percentage by which this is measured, he said, urging content marketers and SEOs to instead think of what the average user would think when they visit your website.

Take advantage of location-based content optimization opportunities

Consumers crave personalized experiences, and location is your low-hanging fruit. Seasonal weather trends, local events, and holidays all impact your search traffic in various ways and present opportunities for location-based optimization.

AI-assisted technology can help you discover these opportunities and evaluate topical keywords at scale so you can plan content campaigns and promotions that tap into this increased demand when it’s happening.

Make the best possible use of content created for locally relevant campaigns by repurposing and promoting it across your website, local landing pages, social media profiles, and Google Business Profiles for each location. Google Posts, for example, are a fantastic and underutilized tool for enhancing your content’s visibility and interactivity right on the search results page.

Optimize content with conversational & high-volume keywords

Look for conversational and trending terms in your keyword research, too. Top-of-funnel keywords that help generate awareness of the topic and spur conversations in social channels offer great opportunities for promotion. Use hashtags organically and target them in paid content promotion campaigns to dramatically expand your audience.

Conversational keywords are a good opportunity for enhancing that content’s visibility in search, too. Check out the ‘People Also Ask’ results and other featured snippets available on the search results page (SERP) for your keyword terms. Incorporate questions and answers in your content to naturally optimize for these and voice search queries.

SEO-and-creating-content-in-2023

It’s important that you utilize SEO insights and real-time data correctly; you don’t want to be targeting what was trending last month and is already over. AI is a great assist here, as well, as an intelligent tool can be scanning and analyzing constantly, sending recommendations for new content opportunities as they arise.

Consider how you optimize content based on intent and experience

The best content comes from a deep, meaningful understanding of the searcher’s intent. What problem were they experiencing or what need did they have that caused them to seek out your content in the first place? And how does your blog post, ebook, or landing page copy enhance their experience?

Look at the search results page as a doorway to your “home”. How’s your curb appeal? What do potential customers see when they encounter one of your pages in search results? What kind of experience do you offer when they step over the threshold and click through to your website?

The best content meets visitors where they are at with relevant, high-quality information presented in a way that is accessible, fast loading, and easy to digest. This is the case for both short and long form SEO content. Ensure your content contains calls to action designed to give people options and help them discover the next step in their journey versus attempting to sell them on something they may not be ready for yet.

2023, the year of SEO: why brands are leaning in and how to prepare

Conclusion

The audience is king, queen, and the entire court as we head into 2023. SEO and content marketing give you countless opportunities to connect with these people but remember they are a means to an end. Keep searcher intent and audience needs at the heart of every piece of content you create and campaign you plan for the coming year.

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