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The Most Engaged YouTube Fans For NCAA Basketball Teams

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The Most Engaged YouTube Fans For NCAA Basketball Teams

Imagine that you head up digital marketing at Turner Sports or CBS Sports, which have the exclusive rights to license NCAA marks, tickets, and taglines in commercial promotions.

Or suppose that your social video agency was just invited to pitch AT&T, Capital One, or Coca-Cola, which are official NCAA corporate champions.

And you have an assignment to identify the most engaged YouTube fans for the NCAA Division 1 Men’s and Women’s basketball teams.

I realize that you probably don’t work at one of those sports media and entertainment companies and it’s highly unlikely that you’ll be asked to pitch one of those brands in the foreseeable future.

So, why should you care about what makes engaged NCAA fans on YouTube?

Keep reading, there is method in the madness.

Cognitive, Emotional, And Behavioral Metrics

As mentioned previously, the Interactive Advertising Bureau (IAB) has identified 30 metrics – 7 cognitive, 4 emotional, and 19 behavioral – that brands or agencies can use to measure the “engagement continuum.”

Image from IAB, March 2024

But fan engagement can fluctuate depending on whether a college basketball team is on the bubble, makes it to the Big Dance, or goes deep into the Sweet 16, Elite Eight, and Final Four.

Fan engagement can also vary depending on the number of logo 3s, buzzer beaters, or overtime wins.

That’s why this hypothetical assignment is so hard.

Nevertheless, exploring various video engagement metrics from several video intelligence sources can help you better understand the most engaged YouTube fans for NCAA basketball teams and how to apply what you’ve learned to your brands or clients.

Here are three cognitive metrics that you should explore when measuring engagement:

  • Change in Brand Awareness/Familiarity: You can use surveys to measure the extent your brand is recognized by potential customers before and after this year’s NCAA tournaments.
  • Change in Brand Consideration: You can also use pre- and post-March Madness surveys to measure your brand’s inclusion in a set customers would select from.
  • Change in Purchase Intent: You can also use Brand Lift surveys to measure the delta in customers’ plans or willingness to purchase your brand in the future.

Here are three emotional metrics that you should look at using to measure engagement:

  • Change in Baseline Brand Perception: Surveys enable you to measure the pre-post delta in what potential customers think and feel about your brand.
  • Change in Baseline Brand Favorability: Surveys also enable you to measure what potential customers like and value about your brand before and after the Big Dance.
  • Change in Baseline Brand Loyalty: Surveys enable you to measure customer loyalty in terms of weight and frequency of usage – as well as likelihood to switch – from Selection Sunday, March 17, to the women’s NCAA championship game on Sunday, April 7, and the men’s NCAA championship game on Monday, April 8, 2024.

Here are six behavioral metrics worth exploring to measure engagement:

  • Watch Time: The total amount of time viewers spend watching a video, including any replays or rewatches, should be a key metric. Since it’s only available if you have access to your brand or client’s YouTube Analytics, digital marketers and social video agencies use “views” as a metric to compare videos across other YouTube channels.
  • Applause Rate: The number of likes a YouTube video gets.
  • Amplification Rate: The number of shares a YouTube video gets.
  • Conversation Rate: The number of comments a YouTube video gets.
  • Engaged-View Conversions (EVCs): In Google Analytics 4 (GA4), an engaged-view conversion (EVC) indicates that someone watched a YouTube video for at least 10 seconds and then converted on your website or app within 3 days of viewing the video.
  • Economic Value: This is the monetary value of visitors from YouTube to your site who go on to complete micro conversions like subscribing to a newsletter or initiating a chat with your business, as well as macro conversions like purchasing a product or registering for a service.

In addition, here are some of the video intelligence sources you should evaluate:

  • Official Team and Conference Channels: Many NCAA Division 1 teams and major conferences, like the ACC, Big 10, and SEC, have their own YouTube channels. These channels feature highlights, interviews, and behind-the-scenes content. Comparing their metrics can provide you with insights.
  • Media and NCAA Basketball Channels: YouTube channels like CBS Sports and March Madness upload video content about various college basketball teams, allowing you to compare fan engagement based on comments and viewership.
  • Third-Party Tools: Tubular Labs, a social video intelligence company that provides data on social video audiences, and Pixability, a company that helps brands monitor their YouTube and CTV campaigns, can provide deeper insights into engagement, but they require paid subscriptions.

For this article, I contacted Matt Duffy, the company’s CMO, and Sean Alie, the head of its insights team, to see if they had any critical data or strategic insights worth sharing.

They did – and it appears below.

There are four sections: men’s team views, women’s team views, year-over-year (YoY) data for men’s and women’s teams + men’s vs. women’s teams, and lastly, views by popular players (such as Caitlin Clark, the NCAA Division I all-time leading scorer of the Iowa Hawkeyes in the Big Ten Conference).

Here’s what the men’s NCAA basketball views look like.

They are filtered to sports videos only, and each video includes the keywords “*team name*,” “basketball,” and “men” somewhere in the metadata.

The timeline is February only.

Men’s Basketball

Houston, the #1 ranked team, earned 7.5% more views than the next leading team, Kansas (21M vs 19.6M). Kansas did rank first in engagements, though, earning 13% more engagements than Houston (442K vs 391K).

Duke ranked 3rd in views (16M) and engagements (389K). One thing to note is Houston is the #1 ranked team and the most viewed team on YouTube.

However, Kansas was ranked 14th and Duke 9th, yet they were able to rank 2nd and 3rd in views. This is a testament to the brand awareness these programs hold.

Men's basketball engagement dataImage from Pixability, March 2024

Women’s Basketball

This data uses the same methodology as the men’s data except with “women” as a keyword instead of “men.”

Iowa, home of star Caitlin Clark, earned 51% more views than the next leading program, LSU (12.4M vs 8.2M). This makes sense as Angel Reece plays for LSU and is widely considered the second most popular player in women’s college basketball, after Caitlin.

The individual stars may influence views for women’s programs more than the team’s fan base. Iowa earned 9.5% more engagements than LSU (178.5K vs 162.9K). Indiana ranked 3rd in views, followed by UConn.

Women's basketball engagement dataImage from Pixability, March 2024

Men’s Vs. Women’s Teams And YoY Stats

  • The top 16 men’s teams earned a combined 130.8M views in February 2024, which is 157% more than the top 16 women’s teams have earned (50.8M). Men’s teams earned 247% more engagements (2.4M) than women’s teams (690K).
  • YoY, the top 16 ranked men’s teams earned 61% more views this year compared to the top 16 ranked teams last year in February (130.8M vs 81.2M).
  • YoY, the top 16 ranked women’s teams earned 147% more views this year compared to the top 16 ranked teams last year in February (50.8M vs 20.5M). This means that views for women’s college basketball are growing faster than the men’s. A large part of this was due to the rise of Caitlin Clark.

Views By Popular Basketball Players

The stats below are based on players participating in the tournament: Caitlin Clark earned 17.5M player mention views in February, which is more than any other player in the men’s and women’s tournaments.

Caitlin earned 10.6x more views in February than the highest male player (Kyle Filipowski) views polled in February (17.5M vs 1.6M).

The second most viewed player was also a woman, Angel Reese, who plays for the LSU Tigers in the Southeastern Conference. Angel earned 3.9x more views than Kyle Filipowski, who plays for the Duke Blue Devils in the Atlantic Coast Conference (6.4M vs 1.6M).

The rivalry between these two women stars has fueled incredible engagement on YouTube.

Again, men’s teams are more popular than women’s teams, but at the individual level, women players are outperforming men by a large margin.

Although the USC Trojans of the Pac-12 Conference won’t make the tournament this year, LeBron Raymone “Bronny” James earned 32M views, which is 87% higher than Caitlin Clark’s views.

This is still incredibly impressive for Caitlin as she is putting up numbers that compete with someone as well-known as Bronny James.

Engagement Data for PlayersImage from Pixability, March 2024

Of course, you could figure out who are the most engaged YouTube fans for NCAA basketball teams without using third-party tools.

But that might take so much time that you’d miss some of the games that make March Madness worth watching and create highlights worth sharing on YouTube.

Hey, you make the call.

How Marketers Can Use Insights Into The Most Engaged Fans

So, how can digital marketers use these insights about NCAA basketball’s most engaged fans?

Well, I can think of three key ways to apply what we’ve just learned.

First, as I mentioned in “39 Emotions Digital Marketers Can Use In Advertising,” people share videos that elicit “high-arousal” or intense emotions twice as much as ones that elicit “low-arousal” or moderate emotions. And March Madness elicits several intense emotions.

For example, the Big Dance triggers nostalgia, a sentimental longing or wistful affection for some past period or irrecoverable condition. How do you make use of this insight?

Watch Continental Tire’s “Grant Hill, Christian Laettner, and the Smart Choice!” Basketball legends Grant Hill and Christian Laettner of Duke not only tell us about the importance of making smart choices but also remind us of “The Shot” during the 1992 NCAA tournament.

During a game between East Region #1 seed Duke and #2 seed Kentucky in the East Regional Final to determine a spot in the Final Four, defending national champion Duke trailed 103–102 with 2.1 seconds remaining in overtime.

That’s when Hill threw a pass three-quarters of the length of the court to Laettner, who faked right, dribbled once, turned, and hit a jumper as time expired for the 104–103 win. In 2004, Sports Illustrated called it the greatest college basketball game of all time.

Second, college athletes can now make money from their name, image, and likeness (NIL). So, brands like State Farm Insurance can now feature players like Caitlin Clark in YouTube videos like “Shoot! (feat. Caitlin Clark, Jimmy Butler, Reggie Miller) :30 | State Farm Commercial.”

It’s worth noting that State Farm uploaded this video on Nov. 21, 2023, almost three months before Clark broke “Pistol” Pete Maravich’s NCAA Division I scoring record on Feb. 15, 2024. Kudos to the brand and their agency for being ahead of the curve.

Third, the line between creators and their audiences is blurring.

At last year’s Brandcast, YouTube CEO Neal Mohan told advertisers, “The universe of ‘creators’ is growing every day as more people make videos on their phones.

This limitless access means the world of creation is changing. Fans used to engage with a like or subscribe. But now, you can see a trend and easily jump in with your own video.”

For an example, check out “Meet the New Face of March Madness – Robbie Avila #collegebasketball #indianastate #sports #funny.” BenchwarmerBran, the online alias of Brandon Carney, a sports content creator who makes jokes about teams, players, and fantasy leagues, uploaded this video on March 7, 2024. And it currently has 405,000 views and 63,500 engagements.

If you use Tubular Intelligence, then you will see that 1,536 accounts in the U.S. uploaded 3,208 videos about “March Madness” to YouTube in the last 90 days.

And influencers uploaded 2,359 of these videos (73.5%), while media and entertainment companies uploaded 602 (18.8%), and brands uploaded only 224 (7.0%).

Now, these 3,208 YouTube videos about March Madness got a total of 11.6 million views and 455,000 engagements.

So, targeting affinity segments, people who already have a strong interest in relevant topics, may be a much smarter option than targeting placements, specific YouTube channels or websites and apps on the Google Display Network.

How SEO Pros Can Use This Information, Too

So, how could an SEO specialist use this information to make actionable decisions?

Well, I’m sad to say that some won’t.

Why? As Captain Spock (Leonard Nimoy) said in “Star Trek II: The Wrath of Kahn”,

“He is intelligent, but not experienced. His pattern indicates two-dimensional thinking.”

In other words, some intelligent SEO specialists think their job is to work with text, not videos. And they also think that the content that their optimizing is to help people make rational decisions, not emotional ones.

But YouTube videos have been appearing in Google’s search results since May 2007. And as I mentioned in “Customer Personas Can Transform SEO, PPC and Content Marketing,” Google has talked about emotions driving search intent since May 2019.

As Justin De Graaf, Head of Ads Research and Insights at Google, observed back then,

“The truth is, decision-making is not a rational process, but one driven mainly by how people feel. The rational brain layers on reasons for our choices only after they’re made.”

So, if SEO specialists continue to focus on optimizing text to help people make rational decisions, then their pattern indicates two-dimensional thinking.

Now, they may continue to be somewhat successful, especially if they can answer “yes” when asked: “After reading your content, will someone leave feeling they’ve learned enough about a topic to help achieve their goal?”

But, as Google has said,

“The helpful content update aims to better reward content where visitors feel they’ve had a satisfying experience, while content that doesn’t meet a visitor’s expectations won’t perform as well.”

So, SEO specialists who can’t create (and optimize) video content that tells a good story and makes a visitor feel something emotionally may struggle to provide a satisfying experience.

In conclusion, this is why it’s worth dreaming about getting a starring role in a Cinderella story.

I realize that you probably won’t get a job at one of those media and entertainment companies and it’s highly unlikely that you’ll be asked to pitch one of those brands in the foreseeable future.

But, if and when your opportunity presents itself, then you will be ready to take your best shot at the buzzer.

More resources:


Featured Image: adriaticfoto/Shutterstock

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How to Combine SEO and Content Marketing (The Ahrefs’ Way)

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How to Combine SEO and Content Marketing (The Ahrefs’ Way)

SEO and content marketing are different marketing channels. But you don’t have to choose between them. They’re complementary.

In fact, you should combine them for greater effectiveness in your marketing.

Two main reasons:

1. Content marketing and SEO are like peanut butter and jelly—they work well together

Content marketing is the process of creating and distributing content to attract and retain customers.

Here’s how SEO helps content marketing:

The web's largest traffic referrersThe web's largest traffic referrers

SEO is the process of improving a website’s visibility in search engines to get more traffic.

Here’s how content marketing helps SEO:

  • It helps you get more search traffic — If you want more search traffic, you need to rank for more keywords, which requires you to make more content.
  • It makes SEO more effective — Thought leadership content acquires backlinks, gated content generates leads, and sales enablement converts traffic into sales.

2. The same amount of investment in effort, money, and time can generate results for both content marketing and SEO

We’re the perfect example. Our content ranks high on Google and generates hundreds of thousands of monthly search visitors:

Ahrefs blog trafficAhrefs blog traffic

It also attracts links and shares on social media because we make sure each piece is unique and not just regurgitation or “AI content”.

LinkedIn comment on how we blended an SEO-friendly term with a contrarian point of viewLinkedIn comment on how we blended an SEO-friendly term with a contrarian point of view

Finally, each piece of content introduces visitors to our product and educates them on how to use it to solve their problems. (Keep on reading and you’ll see it in action too!)

Example of how we introduce our product in our contentExample of how we introduce our product in our content

It hits all content marketing and SEO goals at once:

  • Acquires search traffic ✅
  • Builds thought leadership ✅
  • Attracts links ✅
  • Generates sales (over the long-term) ✅

How do we do what we do? Believe it or not, there’s a method to the madness. Here’s one line that summarizes our entire SEO content marketing strategy:

We create and maintain high-quality, product-led, search-focused content about topics with business potential and search traffic potential.

Let me break down how we combine SEO and content marketing:

If you want to acquire search traffic, you need to target topics that your potential customers are searching for.

The easiest way to find these keywords is to use a keyword tool like Ahrefs’ Keywords Explorer:

  1. Go to Keywords Explorer
  2. Enter a few broad keywords related to your site or niche
  3. Go to the Matching terms report
  4. Filter for keywords with traffic potential (TP)
Matching terms report in Keywords ExplorerMatching terms report in Keywords Explorer

Sidenote.

Traffic Potential is the estimated monthly organic search traffic to the top-ranking page for a keyword. Since pages tend to rank for many keywords, Traffic Potential is a more reliable estimate than search volume.

Go through the report and pick out the keywords that are relevant to your site. For example, if I were an ecommerce store selling coffee equipment, this could be a potential keyword to target:

The keyword "best coffee grinder"The keyword "best coffee grinder"

A keyword’s business potential is how easy it will be to pitch your product while covering a certain topic. It’s our ‘trade secret’—it’s why we can easily introduce our product and its features in every piece of content we create.

Here’s how to score a topic’s business potential:

Business potential scoring chartBusiness potential scoring chart

So, taking the above example, the topic “best coffee grinder” would score a “3” (provided we sell coffee grinders) whereas a topic like “does decaf coffee have caffeine” would score a “1” or even a “0”.

You should prioritize topics that score high on business potential, i.e. a “2” or a “3”.

What does all of the jargon mean? Let’s break it down.

Search-focused

Part one of being ‘search-focused’ is finding keywords that people are searching for. Part two is to figure out why they’re searching for those particular keywords. This ‘why’ is known as search intent.

Given that Google’s goal is to always rank the most relevant content, we can look at the search engine results (SERPs) to uncover search intent. Take your target keyword, enter it into Keywords Explorer, scroll down to SERP Overview, and click Identify intents:

Identify intents feature in Keywords ExplorerIdentify intents feature in Keywords Explorer

So, we can see that searchers looking for the keyword “best coffee grinders” want detailed reviews and expert recommendations on the best coffee grinders. Not only that, we can also see that searchers want a list that is fresh.

Identified search intent for "best coffee grinder"Identified search intent for "best coffee grinder"

If we’re targeting this topic, making it search-focused means matching this search intent—we’ll need to create a list of the best coffee grinders for the current year.

Product-led

Product-led means ensuring you’re not just creating content for the sake of it; you’re also ‘selling’ your product. You want to be aware of which use case, feature, or service you want to weave into the narrative. Naturally, of course.

Scoring a topic’s business potential would have done 90% of the work here. If you’re creating content about a topic that scored a “3”, then your product pitch would be natural. For example, we could easily add links back to our coffee equipment store after covering the best coffee grinders. Or, if we make our coffee grinders, we could pitch them as one of the best. (That’s why I say the business potential score is our secret ingredient.)

The challenge comes when you’re covering topics that score a “1” or “0”. It’s not impossible, but you’ll need to be creative.

For example, I recently covered the topic “SEO specialist”. It had a business potential of “1” and was tough to include a product pitch. Fortunately, I noticed that some job listings asked for experience with different SEO toolsets (including us.) It was the perfect segue to introduce our product and certification course.

An example of how I managed to pitch Ahrefs in a post with a business potential of 1An example of how I managed to pitch Ahrefs in a post with a business potential of 1

High-quality

This is subjective. Everyone’s standards are different. But here’s how we think of quality:

  • Accurate — No hype, no lying. Every statement we make should be as accurate as possible.
  • Clear — No fluff—delete all unnecessary words and sentences. Use jargon only when needed. When necessary, create illustrations to expand on ideas and concepts.
  • Helpful — Being product-led is important but the content should not just be aimed at pitching. The content should be focused primarily on helping visitors solve their problems, while creatively weaving our product into the context.
  • Unique — One way to make your content unique is to have skin in the game—conduct experiments, run data studies, and write from personal experience. If having skin is difficult, then interview practitioners. Focus on did, not could.

The deterioration of your content is inevitable:

  • Search-focused — Your rankings may drop because of competitors. Or you didn’t even rank the first time round. Or your target topic’s search intent changed (e.g., the word corona’s search intent changed during the void years of 2020-2022.)
  • Product-led — You may have new features, services, or use cases to introduce. Or your team has depreciated certain features or abandoned some services.
  • High-quality — Statements may become inaccurate over time. Or your unique idea was so successful that everyone else copied you (and outranked you.) Or you might have better ways to reword sentences and paragraphs. Or just simply the ideas, screenshots, and content has become outdated.

That’s why you don’t build a train track and disappear. You have to actively maintain it to keep it working. (I’m looking at you London tube.) Same goes for your content.

The way to maintain your content is to conduct regular content audits. We do this every quarter—Each writer on our blog team goes through their portfolio of articles and selects at least three pieces to update. Each writer may also choose a couple to do a full rewrite.

I highly recommend going through our content audit template so you can see what went wrong with your content and what to do with it next.

Final thoughts

SEO and content marketing may be different marketing types, but that doesn’t mean you need to do one to the exclusion of the other.

Both channels are highly compatible and as you see above, can be designed as an entire strategy that hits all important marketing objectives.



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Trending Content Output Compared in ChatGPT, Gemini & Claude

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Trending Content Output Compared in ChatGPT, Gemini & Claude

“Should we use ChatGPT, Gemini, or Claude to create trending content?”

That’s a good question – and one that I’m frequently asked when teaching a live class about engaging audiences through content.

You might mistakenly assume that instructors are supposed to answer questions like that. But my colleagues and I do something different.

We give our students relevant assignments that provide them with the opportunity to discover the answers to good questions for themselves.

This test-and-learn approach is something that you can also apply within your own company, agency, or team. Want to know which generative AI model to use to create trending content?

Well, conduct a test and compare the output.

Write Concise Descriptions Of The Most Emotionally Engaging Video Ads Of Euros 2024

You already know how to use Google Trends to identify search terms or topics that are trending now. In fact, many journalists use this free tool to get story ideas.

Over the long Fourth of July weekend, I used Google Trends and saw that the topic “Euros 2024” ranked No. 1 in Trending Searches with more than 1 million queries.

Next, I decided to avoid using OpenAI’s ChatGPT 3.5 for my tests. Why? Because it’s the most popular generative AI model, which means that your competitors are probably using it, too.

That means the content that this tool creates is less likely “to provide substantial value when compared to other pages in search results,” as Google’s long-standing advice recommends.

ChatGPT Output

So, I explored the custom versions of ChatGPT and selected Write For Me by puzzle.today.

Why? Because it ranked No. 1 in the Writing category. The tool also claimed it would help me “write tailored, engaging content with a focus on quality, relevance and precise word count.”

I want to create better content, not just content that is different from what everyone else is creating. So, I asked Write For Me to “write concise descriptions of the most emotionally engaging video ads of Euros 2024.”

Here’s what this generative AI tool produced:

1. Unity Through Football

 “A diverse group of children from different European countries come together on a pristine football pitch. As they play, the camera captures their joy and camaraderie, transcending language and cultural barriers. The ad concludes with a montage of professional players joining the children, emphasizing football's power to unite nations and foster friendship.”

2. Legacy of Legends

 “The ad begins with black-and-white footage of iconic moments from past Euros, highlighting legendary players. It transitions to vibrant, modern clips of current stars recreating these moments, symbolizing the passing of the torch. A heartfelt narration speaks to the continuity of dreams and the legacy carried by each generation.”

3. Homecoming

 “A montage of fans traveling from various parts of Europe to the host country, capturing their excitement and anticipation. Emotional reunions with fellow fans, old friends, and family members create a sense of belonging and community. The ad closes with a panoramic shot of a stadium filled with cheering supporters, underscoring the tournament's role in bringing people together.”

4. The Dream Begins

 “The ad follows a young aspiring footballer practicing tirelessly, inspired by their favorite Euros moments. Interspersed with clips of professional matches, it shows the child's journey from local games to a stadium filled with fans. The message is clear: dreams start small but can lead to greatness, encouraging viewers to pursue their passions.”

5. Heartbeat of the Game

 “This ad features a rhythmic sequence of football-related sounds: the thud of a ball, cheers from the crowd, and the whistle of the referee. These sounds build into a symphony, interspersed with clips of players’ intense focus and emotional celebrations. The heartbeat sound underscores the passion and excitement of the Euros, resonating with fans’ own emotions.”

6. From Streets to Stadiums

 “Children playing football in urban alleys, rural fields, and makeshift pitches across Europe are showcased. Their raw passion and joy are mirrored by professional players in grand stadiums, blurring the lines between dreams and reality. The ad concludes with a powerful message: football belongs to everyone, from the streets to the grandest arenas.

Now, it’s perfectly clear why video ads with these descriptions would be emotionally engaging, but it is frustratingly unclear which brands are running these ads during Euros 2024.

So, I’d have to do some double-checking to make sure that ChatGPT isn’t hallucinating.

Gemini Output

Next, I gave Google’s Gemini (formerly Bard) the same prompt. Here’s what this generative AI model produced:

1. Adidas: "Hey Jude" (Most Engaging)

 “This ad features rising England star Jude Bellingham alongside football legends like David Beckham and Frank Lampard. It taps into positive emotions by showcasing the passing of the torch and the enduring spirit of the game.”

2. Irn-Bru: "Get to Germany"

 “This ad, likely using humor, aims to create positive feelings and excitement around the Euros being held in Germany.”

3. Budweiser: "Bring it Home"

“This ad uses a patriotic theme, likely aiming to inspire viewers and evoke a sense of national pride for their team's chance to win the Euros.”

It’s perfectly clear which brands are running the most emotionally engaging video ads of Euros 2024, but it’s still unclear which methodology Gemini is using to make this selection.

So, I’d still have to do more due diligence to discover that it’s probably recent articles and posts about new research from DAIVID.

Claude Output

I asked Anthropic’s Claude 3.5 Sonnet to “write concise descriptions of the most emotionally engaging video ads of Euros 2024.” Here’s what this generative AI tool replied:

“I apologize, but I don't have access to specific information about video ads from Euro 2024, as my knowledge cutoff is in April 2024, and I can't browse the internet for current information.”

 “I can, however, offer some general thoughts on what makes emotionally engaging soccer/football ads:”

“Underdog stories of players or teams overcoming adversity.”
“Nostalgic montages showcasing historic Euro moments.”
“Depictions of passionate fans and their connection to the sport.”
“Inspirational messages about unity and international cooperation.”
“Cinematic recreations of iconic goals or plays.”

 “If you'd like me to expand on any of these concepts or discuss emotionally engaging sports ads in general, I'd be happy to do so. For accurate information about Euro 2024 ads, I'd recommend checking official UEFA sources or recent sports media coverage.”

Well, Claude’s honesty is admirable. But its knowledge cutoff means that I shouldn’t use this generative AI model for content about fairly recent trends.

Write Short Captions For The Funniest Photos From The 2024 Nathan’s Hot Dog Eating Contest

For my second test, I used the Google autocomplete feature to confirm that the phrase, [Nathan’s hot dog eating contest], was a trending search term.

Then, I asked each of the three generative AI tools to “write short captions for the funniest photos from the 2024 Nathan’s Hot Dog Eating Contest.”

ChatGPT Output

Here’s what Write For Me generated:

“Captions for Funniest Photos from the 2024 Nathan’s Hot Dog Eating Contest:”

"When you realize you're only halfway through your 50 hot dogs."
"Eyes on the prize: the ketchup bottle!"
"Training for this by swallowing my pride daily."
"When the bun hits you harder than the hot dog."
"Mustard not? I mustered up the courage!"
"New strategy: inhale, don’t chew."
"Hot dogs: 10, Dignity: 0."
"When you think it’s the last dog but it’s not."
"The face you make when you beat your personal best... by 1 dog."
"Calories don’t count if you don’t chew, right?"

Okay, I admit that many of these captions are funny. But it’s difficult to tell if they belong to actual photos or if this custom version of ChatGPT hallucinated the entire list.

And don’t get me started on getting permission to use any photos that exist. Of course, I could always use DALL-E 3 to turn the text above into images.

Gemini Output

Next, I gave Gemini the same assignment. Here’s what it generated:

1. Mustard Mishap: "Someone's about to be redecorated in yellow!" (Photo of a competitor with mustard splattered all over their face).

2. Relish the Moment: "This is what pure competitive joy looks like." (Photo of a competitor mid-devour with a look of intense concentration and relish dripping down their chin).

3. Bun Bungee: "Is that a hot dog or a bungee jumper? Defying the laws of physics, one frankfurter at a time." (Photo of a competitor with a hot dog halfway down their esophagus).

4. Fountain of Fury: "Looks like someone forgot their manners! (But they're probably winning.)" (Photo of a competitor with a spray of water and ketchup erupting from their mouth).

5. Doggy Downtime: "Even champions gotta rest sometimes. (Just don't let Joey Chestnut see this.)" (Photo of a competitor slumped back in their chair with a belly full of hot dogs).”

Um, okay. These are also funny captions.

But it’s hard to know if they go with actual photos that were posted on July 4, 2024, without using Google Images to conduct a series of relevant searches. And that still doesn’t give me permission to use them even if they do exist.

[Note, these responses were generated a few days before Google announced their support for labelling AI-generated images.]

Claude Output

Then, I asked Claude 3.5 Sonnet to “write short captions for the funniest photos from the 2024 Nathan’s Hot Dog Eating Contest.” Here’s what it replied:

“I apologize, but I don't have access to specific photos from the 2024 Nathan's Hot Dog Eating Contest, as my knowledge cutoff is in April 2024. Additionally, I can't generate, produce, edit, manipulate or create images.”

 “However, I can suggest some hypothetical humorous captions that might be appropriate for funny moments at a hot dog eating contest:”

"When the hot dogs fight back"
"Regretting that 50th hot dog"
"Mid-contest nap: Expert level achieved"
"Ketchup everywhere... except on the hot dogs"
"When you realize it's only been 2 minutes"
"The face of a champion... or indigestion"
"Spectators' faces: Equal parts horror and awe"
"When the bun-to-dog ratio is all wrong"
"Competitive eating: Where table manners go to die"
"That moment you question all your life choices"

 
“Remember, these are fictional captions for imaginary photos. For accurate information about the 2024 contest, you'd need to check official sources or news reports from after the event.”

Once again, Claude gets high marks for being honest about its limitations.

But unless I want to select some of these hypothetical humorous captions and use them as prompts in Adobe Firefly, then I need to use one of the other options.

Write A 400-Word Blog Post About The Top Omni Channel Retailing Trends Of 2024

For my third test, I used SparkToro to research the audience of 5,000 to 6,000 people who search for the keyword [customer retention] each month.

I used SparkToro’s trending keywords feature to analyze the search terms that have risen in popularity among searchers for “customer retention” over the last quarter.

Then, I selected the trending keyword, “omni channel retailing trends,” for this test.

ChatGPT Output

When I asked Write For Me to “write a 400-word blog post about the top omni channel retailing trends of 2024,” here’s what this generative AI tool produced:

Top Omnichannel Retailing Trends of 2024

 “As we move into 2024, the landscape of retail continues to evolve rapidly, driven by technological advancements and changing consumer expectations. Omnichannel retailing, which integrates various shopping channels into a seamless customer experience, remains at the forefront of this evolution. Here are the top omnichannel retailing trends to watch out for in 2024.”
 
1. Enhanced Personalization Through AI and Data Analytics
“In 2024, personalization goes beyond just using the customer’s name in emails. Retailers are leveraging advanced AI and data analytics to offer hyper-personalized shopping experiences. By analyzing consumer behavior, preferences, and purchase history, retailers can tailor recommendations, promotions, and content to individual customers. This level of personalization enhances customer satisfaction and increases conversion rates.”
 
2. Seamless Integration of Physical and Digital Channels 
“The line between online and offline shopping continues to blur. In 2024, more retailers are perfecting the integration of physical and digital channels. Innovations like in-store augmented reality (AR) mirrors, smart fitting rooms, and mobile app functionalities that enhance in-store experiences are becoming standard. Additionally, services like click-and-collect and in-store returns for online purchases are expected to become more streamlined and widespread.”
 
3. Expansion of Mobile Commerce (M-Commerce) 
“Mobile commerce continues to grow as consumers increasingly use their smartphones for shopping. Retailers are optimizing their mobile websites and apps to provide faster, more intuitive, and secure shopping experiences. Features like one-click purchasing, mobile wallets, and personalized push notifications are becoming essential components of mobile strategies.”

 4. Social Commerce Revolution 
“Social media platforms are transforming into powerful retail channels. In 2024, social commerce, where shopping experiences are embedded within social media, is set to explode. Platforms like Instagram, Facebook, and TikTok are enhancing their shopping functionalities, allowing users to discover, browse, and purchase products without leaving the app. Influencer marketing and user-generated content continue to drive this trend, making social media a critical part of omnichannel strategies.”
 
5. Sustainable and Ethical Retailing
“Consumers are increasingly demanding sustainability and transparency from the brands they support. In response, retailers are incorporating sustainable practices and ethical sourcing into their omnichannel strategies. This includes offering eco-friendly products, reducing packaging waste, and providing transparency about product origins and manufacturing processes. Brands that can effectively communicate their sustainability efforts through all channels will gain a competitive edge.”
 
6. Voice Commerce and Conversational AI 
“Voice-activated shopping and conversational AI are becoming more prevalent. With the rise of smart speakers and virtual assistants, consumers are using voice commands to search for products, place orders, and track deliveries. Retailers are integrating voice commerce capabilities into their omnichannel strategies to enhance convenience and improve customer engagement.”
 
Conclusion 
“In 2024, the retail industry is embracing these omnichannel trends to create more cohesive and engaging shopping experiences. By focusing on personalization, integrating physical and digital channels, leveraging mobile and social commerce, prioritizing sustainability, and adopting voice commerce, retailers can stay ahead in a competitive market. These trends highlight the importance of flexibility and innovation in meeting the evolving needs of modern consumers.”

Um, okay. This is 498 words long. This content seems designed for publication at the beginning of the year.

The blog post is missing citations from reliable sources, credible quotes, and relevant statistics, as Roger Montti’s article, “Researchers Discover How To SEO For AI Search,” noted back on Dec. 18, 2023.

So, it’s not as bad as a first draft. But I would hope that writers would learn by using this custom version of ChatGPT that they need to craft something a little bit better.

Gemini Output

Next, I asked Gemini to tackle the same assignment. Here’s what this generative AI tool produced:

The Future of Shopping: Top Omnichannel Retail Trends in 2024
 
“The retail landscape is ever-evolving, and 2024 is no exception. Consumers today expect a seamless shopping experience, regardless of whether they're browsing online, visiting a physical store, or interacting with a brand on social media. This is where omnichannel retail thrives. By creating a unified experience across all touchpoints, retailers can build stronger customer loyalty and drive sales.”
 
“Let's delve into the top omnichannel retail trends shaping the industry in 2024:”

 1. The Rise of the Data-Driven Experience:
 “With the demise of third-party cookies, retailers are focusing on collecting and utilizing first-party customer data. This data allows for real-time personalization across all channels. Imagine receiving targeted email promotions based on your recent in-store purchases, or seeing personalized product recommendations on a brand's app. Advanced analytics will not only personalize marketing efforts but also optimize search functionalities and product merchandising on e-commerce platforms.”

 2. AI Takes Center Stage: 
“Artificial intelligence (AI) is rapidly transforming the retail experience. AI-powered chatbots can answer customer queries 24/7, recommend products based on browsing history, and even assist with in-store tasks. Generative AI can create personalized marketing content at scale, while AI-driven sales automation streamlines processes for both retailers and customers.”
 
3. The Blur Between Physical and Digital: 
“The lines between online and offline shopping are continuing to blur. We're seeing a rise in ‘phygital’ experiences, such as augmented reality (AR) apps that allow customers to virtually try on clothes or visualize furniture in their homes. In-store kiosks can facilitate online purchases and allow for easy returns or exchanges. Additionally, ‘showrooming,’ where customers browse in-store and then purchase online, necessitates seamless product availability and pricing across channels.”
 
4. Social Commerce Takes Off: 
“Social media platforms are no longer just for browsing; they're becoming powerful shopping destinations. ‘Live shopping’ experiences with influencers showcasing products are gaining traction, while social media platforms are integrating smoother buying functionalities within their apps. User-generated content and social proof will continue to influence purchasing decisions, making social media a crucial touchpoint in the omnichannel journey.”

 5. Personalization Beyond Products: 
“The future of omnichannel retail goes beyond just product recommendations. Retailers are focusing on creating personalized experiences that cater to individual customer preferences. This could involve offering flexible delivery options, loyalty programs with tiered benefits, or the ability to curate in-store shopping experiences through appointments or personalized product selections.”

Conclusion: 
“In today's competitive retail environment, omnichannel isn't just a trend; it's a necessity. By embracing these trends and prioritizing a data-driven, personalized approach, retailers can not only survive but thrive in the ever-evolving landscape of commerce.”

Well, the headline is better and it’s 433 words long, which is closer to what I’d asked for. But this blog post is also missing citations from reliable sources, credible quotes, and relevant statistics.

So, I hope writers would learn the same lesson by using Gemini that they learned using a custom version of ChatGPT: It’s not bad, but a human with experience and expertise can do better.

Claude Output

Finally, I asked Claude 3.5 Sonnet to “write a 400-word blog post about the top omni channel retailing trends of 2024.” Here’s what this generative AI tool produced:

Top Omnichannel Retailing Trends Shaping 2024
 
“As we navigate through 2024, the retail landscape continues to evolve rapidly. Omnichannel strategies have become more crucial than ever, with consumers expecting seamless experiences across all touchpoints. Let's explore the key trends defining omnichannel retailing this year.”
 
1. AI-Powered Personalization: “Artificial intelligence is revolutionizing how retailers understand and cater to individual customer preferences. In 2024, we're seeing more sophisticated AI algorithms that analyze customer data across channels to deliver hyper-personalized recommendations, offers, and experiences.”
 
2. Augmented Reality Integration: “AR is bridging the gap between online and offline shopping. Retailers are leveraging AR technology to allow customers to virtually try on clothes, visualize furniture in their homes, or explore products in detail before making a purchase decision.”
 
3. Social Commerce Acceleration: “Social media platforms are increasingly becoming direct sales channels. Retailers are optimizing their presence on platforms like Instagram, TikTok, and Pinterest, enabling in-app purchases and creating shoppable content that seamlessly integrates with users' social experiences.”
 
4. Sustainable and Ethical Omnichannel Practices: “Consumers are more environmentally conscious than ever. Retailers are responding by implementing sustainable practices across their omnichannel operations, from eco-friendly packaging to transparent supply chains and ethical sourcing information available across all channels.”
 
5. Voice Commerce Integration: “With the growing adoption of smart speakers and voice assistants, retailers are optimizing their digital presence for voice search and enabling voice-activated purchases, adding another dimension to the omnichannel experience.”
 
6. Phygital Experiences: “The blend of physical and digital experiences, or ‘phygital,’ is gaining traction. Retailers are creating innovative in-store digital touchpoints and bringing elements of the physical store experience to online platforms.”
 
7. Unified Customer Data Platforms: “Retailers are investing in advanced customer data platforms that consolidate information from all channels, providing a single view of the customer and enabling more cohesive marketing and service strategies.”

8. Flexible Fulfillment Options: “The line between online and offline continues to blur with the expansion of services like buy online, pick up in-store (BOPIS), curbside pickup, and same-day delivery. Retailers are optimizing their logistics to offer customers maximum flexibility.”

9. Subscription-Based Models: “More retailers are incorporating subscription services into their omnichannel strategies, providing regular product deliveries or exclusive access to content and experiences across multiple platforms.”
 
10. Advanced Analytics for Real-Time Insights: “Retailers are leveraging advanced analytics tools to gain real-time insights into customer behavior across channels, allowing for quick adjustments to inventory, pricing, and marketing strategies.”
 
“As these trends show, the future of retail lies in creating cohesive, customer-centric experiences that seamlessly blend online and offline touchpoints. Retailers who successfully adapt to these omnichannel trends will be well-positioned to thrive in the dynamic retail environment of 2024 and beyond.”

Claude’s content is 443 words long, which is longer than Gemini’s, but shorter than the custom version of ChatGPT. And Claude generated 10 trends, while ChatGPT generated six, and Gemini generated five.

But just like the other generative AI tools, Claude’s blog post is missing citations from reliable sources, credible quotes, and relevant statistics.

So, Claude is also good at creating a rough draft. But I’d hope that writers would learn by using ChatGPT, Gemini, and Claude that they shouldn’t become a tool of their tools.

AI Is Not Going To Take Your Job

A year ago, Jensen Huang, the founder, president, and CEO of Nvidia, said,

“AI is not going to take your job. The person who uses AI is going to take your job.”

Well, a year later, we’ve learned by comparing the content output generated by ChatGPT, Gemini, and Claude that it’s still smarter to use generative AI tools to brainstorm or create a good first draft.

Then, use your experience, expertise, authoritativeness, and trustworthiness (E-E-A-T) to add emotionally engaging videos, eye-catching photos, citations from reliable sources, credible quotes, and relevant statistics to your content.

Why? Because this is the best way to provide substantial value when compared to other pages in search results.

More resources:  


Featured Image: jomel alos/Shutterstock

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Can You Spot Google Updates with XmR Charts?

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Can You Spot Google Updates with XmR Charts?

Website traffic data normally looks like this:

Ups and downs, peaks and troughs.

If we’re doing our job properly, we generally expect traffic to trend upwards over time, but in any given month, it’s difficult to say whether a peak or a trough is worth paying attention to.

Did we do something great and trigger a new phase of growth? Did we benefit from a new Google update? Or is it just normal variation, part of the natural ebb and flow of people finding our website?

Or suppose you make a change to your content process—you pruned and redirected a bunch of old content—and then traffic dropped the next month. Was that drop caused by the change, or was it just a coincidence?

I’ve been experimenting with a simple statistical tool designed to help answer these questions: XmR charts, also known as process control charts.

Here’s an XmR chart:

Can You Spot Google Updates with XmR ChartsCan You Spot Google Updates with XmR Charts

XmR charts are designed to tell you whether any single data point from a time series is likely to be caused by normal fluctuation (“routine variation”) or a sign that something happened and needs to be investigated (“exceptional variation”).

XmR charts consist of an X plot (named after the x-value, the “thing” we care about—like widgets produced or sales closed)…

1721658366 562 Can You Spot Google Updates with XmR Charts1721658366 562 Can You Spot Google Updates with XmR Charts

…and an MR plot (named after the moving range, basically the “gap” between each data point):

1721658366 191 Can You Spot Google Updates with XmR Charts1721658366 191 Can You Spot Google Updates with XmR Charts

In its simplest use, if you plot your data on the chart and it wiggles up and down around the central line, without crossing the upper and lower bounds—no problem! These ups and downs likely represent normal variation.

But any points that appear outside the upper or lower bounds (shown in red) should be treated as anomalies that need to be investigated.

In the X plot above, the time series seems to show routine variation until January 16th, when the first red out-of-bounds point appears.

1721658366 804 Can You Spot Google Updates with XmR Charts1721658366 804 Can You Spot Google Updates with XmR Charts

The XmR chart suggests that something happened on the 16th to mess with our production process (for better or for worse). Our job is to investigate why.

Sidenote.

The line in the middle is the average value of the dataset; the upper and lower bounds represent 3-standard deviations away from the average (known as three-sigma). Any point that falls outside of these upper and lower bounds is very likely to be an anomaly, and not part of the original probability distribution.

There are other “signals” that the XmR chart can show you (like eight consecutive points on one side of the average line representing another type of exceptional variation)—but I will leave you to investigate those on your own time.

When I started reading about XmR charts, one obvious use came to mind: identifying the impact of Google algorithm updates.

If a site’s traffic tanks to zero, it’s easy to say “we were hit by a manual penalty.” But for smaller changes, like a few months’ consecutive traffic decline, it’s harder to work out the cause. Did we get caught out by a Google update? Is it seasonality? Or is it just a coincidence, with traffic likely to return to normal in the future?

Here’s two years of monthly organic traffic data for the Ahrefs blog, pulled from Site Explorer and plotted on an XmR chart:

1721658366 298 Can You Spot Google Updates with XmR Charts1721658366 298 Can You Spot Google Updates with XmR Charts

Now… this is not particularly useful.

There are tons of data points outside the expected range (red), with very few sitting nearer the center line than the quartile limits (orange).

The XmR chart is supposed to show exceptional variation in a consistent process—but in this image, almost all of the data points suggest exceptional variation. What gives?

Process charts were designed around simple manufacturing processes, and they work very well when the expected output of a process is constant.

If your goal is manufacturing 10,000 widgets each and every week, an XmR chart will help you work out if that 5,600-widget month was a normal “blip” in routine operation, or caused by a real problem that needs to be investigated.

Website traffic is more complicated. There are tons of variables that impact traffic:

  • the fluctuating search volume of each topic,
  • individual ranking positions,
  • new competing articles,
  • search features,
  • seasonality,
  • publishing frequency,
  • Google algorithm updates

That means that running an XmR analysis on a long series of traffic data probably won’t be very helpful. Your “blogging process” is not likely to remain stable for very long.

In my case, this particular two-year snapshot of data probably doesn’t come from a single, stable process—there may be multiple probability distributions hidden in there.

But we can make the analysis more useful.

The best practice for XmR charts is to limit the analysis to a period of time when you know the process was relatively static, and recalculate it when you suspect something has changed.

Looking at the Moving Range chart for this data below, large amounts of traffic variance happened in November and December. We should investigate possible causes. 1721658366 887 Can You Spot Google Updates with XmR Charts1721658366 887 Can You Spot Google Updates with XmR Charts

I know that our publishing frequency was fairly static (we definitely didn’t double our content output). Seasonality would cause a traffic drop, not a spike (we’re writing about SEO, not holiday gift guides).

But there was a big Google update at the start of December:

1721658366 313 Can You Spot Google Updates with XmR Charts1721658366 313 Can You Spot Google Updates with XmR Charts
Source

If we work on the assumption that something happened to our blog process around this time—likely a change to traffic caused by the Google update—we can add a divider to our XmR chart.

Instead of trying to analyze our traffic as a single process, we can treat it as two processes, and calculate XmR charts separately:

1721658366 499 Can You Spot Google Updates with XmR Charts1721658366 499 Can You Spot Google Updates with XmR Charts

Now the first process looks stable (all black dots). The second process shows less extreme variation (red) too, but there’s still too much moderate variation (orange) to look stable. There may be another process lurking within.

And per a rule of thumb for analyzing XmR charts: “the duration of an XmR chart needs to be revisited when a ‘long-run’ of data remains above or below the Average line.” This trend begins in late summer (which is also around the time that Google announced another core update):

1721658366 566 Can You Spot Google Updates with XmR Charts1721658366 566 Can You Spot Google Updates with XmR Charts

We can add another divider at the start of this “long-run” of data to create three separate XmR analyses:

1721658366 941 Can You Spot Google Updates with XmR Charts1721658366 941 Can You Spot Google Updates with XmR Charts

In doing so, all three analyses seem stable, with no points of extreme variance. In other words, we seem to have done a good job at capturing three distinct processes happening within our traffic data.

From this analysis, there seems to be a good chance that our traffic was impacted by external factors around the time of two major Google updates.

Now… this is basically a post-hoc data torturing exercise. We can’t infer any causation from this analysis, and it’s entirely possible that other arbitrary divisions would yield similar results.

But that’s okay. These charts can’t give you definitive, concrete reasons why your traffic changed, but they can tell you where to look, and help you work out whether troubleshooting a traffic dip or spike is a good use of your time.

The ultimate measure of a model’s usefulness is its ability to help you predict things. Will XmR charts help me do a better job running the Ahrefs blog in the future?

I think yes.

Assuming my “blog process” remains relatively stable—I publish at the same frequency, target the same topics, compete with the same competitors—I now have a set of “stable” data that I can use to provide extra context for future traffic numbers:

1721658366 754 Can You Spot Google Updates with XmR Charts1721658366 754 Can You Spot Google Updates with XmR Charts

In the months that follow, I can work out whether dips or spikes in our traffic are likely the result of normal variance, or whether something has changed that requires my attention—like a Google update.

If, for example, my traffic does this next month… 1721658366 36 Can You Spot Google Updates with XmR Charts1721658366 36 Can You Spot Google Updates with XmR Charts

…I know that—given this distribution—that traffic drop could well be normal, unexciting variance.

But if it does this…

1721658367 676 Can You Spot Google Updates with XmR Charts1721658367 676 Can You Spot Google Updates with XmR Charts

…there’s probably something else at work.

With extreme traffic changes you can usually “eyeball” traffic charts and guess what happened. But XmR charts are useful for more subtle variations, and there’s a chance I will be able to identify and act on just a single month’s worth of data. That’s pretty cool.

Final thoughts

Troubleshooting traffic changes is a big challenge for SEOs and content marketers (and we’re working on a few ways to help you identify the signal amongst the noise of your traffic data).

In the meantime, I have found XmR charts an interesting tool in my toolkit, useful for contextualizing my monthly reporting numbers and justifying when I should (or shouldn’t) spend my energy troubleshooting a down month.

(At the very least, XmR charts might just give you the confidence necessary to say “get off my back” when that VP sends you a brusque 3AM email complaining about last month’s 8% traffic dip.)

Sidenote.

Thanks to Benyamin Elias, VP of Marketing at Podia, for introducing me to XmR charts.

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