YouTube has announced the introduction of a new tool in Creator Studio that requires creators to disclose when their videos contain realistic content generated or altered by AI.
As stated in YouTube’s announcement:
“Viewers increasingly want more transparency about whether the content they’re seeing is altered or synthetic.”
To address this growing demand, YouTube will now mandate that creators inform their audience when a video features content that could easily be mistaken for a real person, place, or event but has been created or modified using generative AI or other synthetic media.
Disclosure Labels & Requirements
Disclosures will appear as labels in the expanded description or directly on the video player.
Screenshot from: blog.youtube/news-and-events/disclosing-ai-generated-content/, March 2024.
Screenshot from: blog.youtube/news-and-events/disclosing-ai-generated-content/, March 2024.
YouTube believes this new label will “strengthen transparency with viewers and build trust between creators and their audience.”
Examples of content that will require disclosure include:
Digitally altering a video to replace one person’s face with another’s.
Synthetically generating a person’s voice for narration.
Altering footage of actual events or places to make them appear different from reality.
YouTube acknowledges that creators use generative AI in various ways throughout the creative process and will not require disclosure when AI is used for productivity purposes, such as generating scripts, content ideas, or automatic captions.
Additionally, disclosure will not be necessary for unrealistic or inconsequential changes, such as color adjustments, lighting filters, special effects, or beauty filters.
Rollout & Enforcement
The labels will be rolled out across all YouTube surfaces and formats in the coming weeks, starting with the YouTube app on mobile devices and eventually expanding to desktop and TV.
While creators will be given time to adjust to the new process, YouTube may consider enforcement measures in the future for those who consistently fail to disclose the use of AI-generated content.
In some cases, particularly when the altered or synthetic content has the potential to confuse or mislead people, YouTube may add a label even if the creator has not disclosed it themselves.
YouTube is working on updating its privacy process to allow individuals to request the removal of AI-generated or synthetic content that simulates an identifiable person, including their face or voice.
In Summary
As viewers demand more transparency, marketers must be upfront about using AI-generated content to remain in good standing on YouTube.
While AI can be a powerful tool for content creation, marketers should strive to balance leveraging AI’s capabilities and maintaining a human touch.
FAQ
How does YouTube’s new policy on AI-generated content disclosure impact content creators?
The policy mandates content creators to disclose if their videos include AI-generated or significantly altered content that mimics real-life scenarios.
Disclosure labels will be added in video descriptions or directly on the player.
Failure to comply with disclosure requirements could result in YouTube taking enforcement measures.
What are the exceptions to YouTube’s mandatory AI content disclosure requirements?
AI used to produce unrealistic or animated content, including special effects and production assistance, is exempt from disclosure.
This also applies to minor adjustments like color correction, lighting filters, or beautification enhancements.
What actions will YouTube take if creators do not disclose AI-generated content?
In cases where AI-generated content could mislead viewers, YouTube may add a disclosure label if the creator hasn’t.
Creators will have a grace period to adjust to the new policy, but persistent non-compliance may lead to enforcement measures.
YouTube is refining its privacy guidelines to allow individuals to request the removal of AI-generated content that uses their likeness without consent.
OpenAI’s Sam Altman answered questions about challenging Google’s search monopoly and reveals that he’d rather entirely change the paradigm of how people get information rather than copy what Google has been doing it for the past twenty+ years. His observations were made in the context of a podcast interview by Lex Fridman.
What Altman proposed is that the best way to challenge Google is to completely replace its entire business category, including the advertising.
1. Is OpenAI Building A Challenge Google Search?
The discussion began with a question from Fridman asking if it’s true that OpenAI is going to challenge Google.
Lex Fridman asked:
“So is OpenAI going to really take on this thing that Google started 20 years ago, which is how do we get-“
Sam Altman responded that the whole idea of building a better search engine limits what the future of information retrieval can be, calling the current conception of search boring.
Altman answered:
“I find that boring. I mean, if the question is if we can build a better search engine than Google or whatever, then sure, we should go, people should use the better product, but I think that would so understate what this can be. Google shows you 10 blue links, well, 13 ads and then 10 blue links, and that’s one way to find information.
But the thing that’s exciting to me is not that we can go build a better copy of Google search, but that maybe there’s just some much better way to help people find and act on and synthesize information. Actually, I think ChatGPT is that for some use cases, and hopefully we’ll make it be like that for a lot more use cases.”
2. The World Doesn’t Need Another Google
Altman expanded on his thoughts by saying that the idea of creating another Google in order to challenge Google is not interesting. He said that the more interesting path to follow is completely change not just how people get information but to do it in a way that fits into how people are using information.
Altman continued:
“But I don’t think it’s that interesting to say, “How do we go do a better job of giving you 10 ranked webpages to look at than what Google does?”
Maybe it’s really interesting to go say, “How do we help you get the answer or the information you need? How do we help create that in some cases, synthesize that in others, or point you to it in yet others?’
But a lot of people have tried to just make a better search engine than Google and it is a hard technical problem, it is a hard branding problem, it is a hard ecosystem problem. I don’t think the world needs another copy of Google.”
3. AI Search Hasn’t Been Cracked
The part where the conversation seemed fall off the rails is when Fridman steered the discussion over to integrating a chatbot with a search engine, which itself is already done to death and boring. Bing created the chat on top of search experience over a year ago and now there are at least six AI search engines.that integrate a chatbot on top of a traditional search engine.
Fridman’s direction of the discussion threw cold water on what Altman was talking about.
Altman said that nobody has “cracked the code yet,” which implied that repeating what Bing did was not what Sam Altman had in mind. He called it an “example of a cool thing.”
Fridman and Altman continued:
“And integrating a chat client, like a ChatGPT, with a search engine-
Sam Altman As you might guess, we are interested in how to do that well. That would be an example of a cool thing.
…The intersection of LLMs plus search, I don’t think anyone has cracked the code on yet. I would love to go do that. I think that would be cool.”
4. Advertisement Supported AI Search Is Dystopian
Altman used the word “dystopic” to characterize a world in which AI search was based on an advertising model. Dystopic means dystopian, which means a dehumanizing existence that lacks justice and is characterized by distrust.
He noted that ChatGPT as a subscription-based model can be perceived as more trustworthy as an advertising-based search engine. He raised the idea of an AI suggesting that users try a specific product and questioning whether the recommendation was influenced by advertising or what was best for the user.
That makes sense because there’s a high level of trust involved with AI that doesn’t exist with traditional search. Many consumers don’t trust Google search because, rightly or wrongly, it’s perceived as influenced by advertising and spammy SEO.
Fridman steered the conversation to advertising:
“Lex Fridman …What about the ad side? Have you ever considered monetization of-
Sam Altman I kind of hate ads just as an aesthetic choice. I think ads needed to happen on the internet for a bunch of reasons, to get it going, but it’s a momentary industry. The world is richer now.
I like that people pay for ChatGPT and know that the answers they’re getting are not influenced by advertisers.
I’m sure there’s an ad unit that makes sense for LLMs, and I’m sure there’s a way to participate in the transaction stream in an unbiased way that is okay to do, but it’s also easy to think about the dystopic visions of the future where you ask ChatGPT something and it says, “Oh, you should think about buying this product,” or, “You should think about going here for your vacation,” or whatever.”
5. A Search Experience Where The Consumer Is Not The Product
Altman next commented that he didn’t like how consumers are the product when they used social media or search engines. What he means is that user interactions are sold to advertisers who then turn around to target the users based on their interests.
Altman continued:
“And I don’t know, we have a very simple business model and I like it, and I know that I’m not the product. I know I’m paying and that’s how the business model works.
And when I go use Twitter or Facebook or Google or any other great product but ad-supported great product, I don’t love that, and I think it gets worse, not better, in a world with AI.”
6. Altman Is Biased Against Advertising
Sam Altman explicitly said that he was biased against search and expressed confidence that there is a path toward an AI-based information retrieval system that is profitable without having to serve advertising. His statement that he was biased against advertising was made in the context of the interviewer raising the idea of “completely” throwing out ads, which Altman refused to confirm.
“Lex Fridman …I could imagine AI would be better at showing the best kind of version of ads, not in a dystopic future, but where the ads are for things you actually need. But then does that system always result in the ads driving the kind of stuff that’s shown?
….I think it was a really bold move of Wikipedia not to do advertisements, but then it makes it very challenging as a business model. So you’re saying the current thing with OpenAI is sustainable, from a business perspective?
Sam Altman Well, we have to figure out how to grow, but looks like we’re going to figure that out.
If the question is do I think we can have a great business that pays for our compute needs without ads, …I think the answer is yes.
Lex Fridman Hm. Well, that’s promising. I also just don’t want to completely throw out ads as a…
Sam Altman I’m not saying that. I guess I’m saying I have a bias against them.”
Is OpenAI Building A Challenge To Google?
Sam Altman did not directly say that OpenAI was building a challenge to Google. He did imply that a proper challenge to Google that uses AI doesn’t yet exist, saying that nobody has “cracked the code” on that yet.
What Altman offered was a general vision of an AI search that didn’t commoditize and sell the users to advertisers and thereby be more trustworthy and useful. He said that a proper challenge to Google would be something that was completely different than what Google has been doing.
TikTok has launched its new Creator Rewards Program and introduced a Search Insights tool.
The program, which was previously in beta, rewards creators based on four key metrics:
Originality
Play duration
Search value
Audience engagement
The new Creator Search Insights tool provides data on trending search topics, helping you to create content that meets TikTok’s requirements for “search value.”
Here are the details about the new monetization program and keyword research tool.
Emphasis On Search Value
One of the most notable aspects of the Creator Rewards Program is its emphasis on search value.
In an announcement, TikTok defines search value as:
“Search value is a metric assigned to content based on popular search terms. Content that aligns with in-demand search topics increases its value for searchers.”
To help people create more content with search value, TikTok launched the Creator Search Insights tool, which identifies trending search topics on the platform.
Creator Search Insights Tool
The Creator Search Insights tool, available in select regions, allows you to explore topics that are frequently searched for on TikTok.
By typing “Creator Search Insights” in the search bar, you can access a wealth of information to inspire your content creation process.
The tool surfaces popular search topics sorted by category or personalized based on your content niche. Additionally, you can filter for content gap topics, which are popular terms with limited video content available on the platform.
“With these insights, creators can source inspiration for their content, tailor their creative strategies to meet audience interests and create content that people want to see more of. Our hope is that Creator Search Insights empowers creators to make content that’s relevant to searchers and positioned to perform well on TikTok.”
Additional Program Metrics & Eligibility
The Creator Rewards Program also prioritizes originality, encouraging creators to showcase their unique perspectives and creative processes in a way that resonates with their audience.
Additionally, the program considers play duration, which accounts for watch time and finish rate, and audience engagement, including likes, comments, and shares.
To be eligible for the program, creators must be at least 18 years old, have a minimum of 10,000 followers, and have generated at least 100,000 views in the past 30 days. Their accounts must also be in good standing and located in a region where the program is available.
Enhanced Dashboard & Creator Academy
Alongside the Creator Rewards Program launch and the Creator Search Insights tool, TikTok has introduced an enhanced dashboard that provides creators with detailed analytics, insights, and customization options to help them analyze their content performance and estimated rewards.
The dashboard also includes direct access to the Creator Academy, a comprehensive education hub offering resources, courses, and insights to support creators at all levels.
TikTok has also improved its Monetization module within the in-app Creator tools. It provides a centralized hub for creators to access all monetization-related operations, including revenue analysis and personalized recommendations.
In Summary
The Creator Rewards Program and Search Insights tool are the latest examples of how TikTok enables creators to make money on its platform.
As the platform continues to evolve and prioritize search, marketers who adapt their strategies accordingly may find new opportunities to earn revenue.
FAQ
How do the new TikTok Creator Rewards Program and Search Insights tool influence content strategy?
Marketers focusing on TikTok must adjust their content strategies in light of the platform’s recent updates. The Creator Rewards Program incentivizes content that aligns with specific criteria, emphasizing:
Originality – Offering a fresh and unique perspective in the content.
Play duration – Creating content that encourages viewers to watch until the end.
Search value – Crafting content that corresponds with in-demand search terms and topics.
Audience engagement – Generating content that fosters likes, comments, and shares.
Content creators and marketers should leverage the Creator Search Insights tool to capitalize on these metrics. By focusing on trending searches and identifying content gaps, they can tailor their content to meet user interests and improve its potential for visibility and monetization on the platform.
To be eligible for TikTok’s Creator Rewards Program, what criteria must creators meet?
For creators to take advantage of TikTok’s monetization opportunities through the Creator Rewards Program, they must meet the following eligibility criteria:
Age – Must be at least 18 years old.
Followers – Must have a minimum of 10,000 followers.
View count – Must have garnered at least 100,000 views in the past 30 days.
Account standing – Must have an account in good standing and based in a region where the program is available.
These prerequisites ensure that active, influential, and engaged creators are rewarded, incentivizing high-quality and engaging content creation on TikTok.
What resources does TikTok provide to creators to help them succeed on the platform beyond the Creator Rewards Program?
TikTok offers resources to support creators in honing their craft and optimizing their content. These resources include:
An enhanced dashboard that delivers in-depth analytics, insights, and customization options, thus enabling creators to analyze content performance and projected rewards.
Direct access to the Creator Academy presents an extensive array of educational material, courses, and insights aimed at aiding creators of varying experience levels.
Improvements to the in-app Monetization module, featuring a centralized hub where creators can manage all monetization aspects, including revenue analysis and tailored recommendations.
These tools empower creators with the knowledge and data to create compelling content and maximize their earning potential on TikTok.
In today’s digital landscape, a healthy, technically sound website is the key to SEO success.
However, ensuring your site is optimized for maximum performance is no easy feat, as SEOs, developers, UX pros, content leaders, marketing, and C-suite members must all be in alignment.
Maintaining your website’s technical health isn’t just about ranking well in search engines – it’s also crucial to driving more user engagement, conversions, and ultimately, revenue.
On March 27, we’re delving into the critical areas and key site metrics you need to focus on in 2024, including SEO, site speed, and accessibility.
Join us as we provide actionable tips and insights to help you improve your website’s technical health and drive tangible results.
And of course, we’ll go beyond just finding issues on your domains – we’ll also walk you through ways to actually fix them.
Our expert guests, Richard Barrett and Matt Ford of Lumar, will show you how to build new connected site health workflows that enable faster fixes and less stress for everyone involved in the website optimization process.
In this live session, we’ll cover the following topics:
Expanding Your View: Beyond Content and Keywords –Learn why SEO professionals and website managers need to broaden their perspective beyond content & keywords for maximum business results.
Improving Technical Health: Tips and Strategies – Discover practical tips for enhancing key aspects of your website’s technical health, including crawlability, indexability, site speed, accessibility, and more.
Building Streamlined Workflows: Aligning Your Team for Success – Explore strategies for building connected website health workflows that facilitate faster issue resolution and reduced stress for your team.
SEO has undergone many transitions and disruptions in a short time.
Enterprise SEO has been at the center of some fundamental transformations over the past year.
Adapting to the ever-changing needs and demands of consumers, integrating AI into search engines, and the influx of new generative AI SEO and content tools have forced organizations to adapt and evolve their marketing strategies.
In this article, I will delve deeper into five key enterprise SEO trends for 2024 with tips to help you keep pace with change and prepare for future success accordingly.
What Is Enterprise SEO?
Enterprise SEO is typically associated with implementing SEO strategies within large-scale organizations.
It predominantly applies to sizable brands with multiple departments and complex infrastructures. This can include large – and multiple – websites that offer a diverse array of products and services.
One of the key differences between standard SEO and enterprise SEO is the need for the workflow management of stakeholders, strategic planning, and ensuring strategies align with an organization’s broader – and, in many cases, multiple – objectives.
How Enterprise SEO Has Changed
In 2024, enterprise SEO trends will be shaped by technological advancements, changing user behaviors, and the evolving search landscape.
It’s no secret that the way search engines utilize generative AI to create new user experiences is changing how enterprises look at, and understand, what is happening in the search engine results pages (SERPs).
This includes shifting from pure keyword research leveraging data-led insights to understanding conversational intent that triggers search results.
Whether you are searching via traditional results or in Google SGE labs, results now contain more sources and multiple content formats. As a result, enterprises must become more innovative and proactive in their SEO and content marketing approaches.
The great thing to see is that the role of SEO is growing and expanding in this new AI era.
Image from author, February 2024
5 Essential Enterprise SEO Trends To Watch In 2024
1. Understanding Market Shift And Ever-Evolving Consumer Preferences
SEO is such a dynamic and intense discipline that, for the majority, it can be a ‘heads down,’ laser-focused, task-by-task approach.
However, especially when we look at enterprise SEO and large-scale projects, it is essential to take a step back and ensure you have a pulse on what is happening at a macro level.
For enterprise SEO experts, it is crucial to stay on top of the latest trends and developments in consumer behavior, especially during economic shifts. These shifts can significantly impact how businesses align their more extensive SEO and content strategies to match business objectives.
For example, the pandemic saw rapid shifts in shopping preferences for products related to staying at home.
In any era-changing economic conditions, the importance of SEO reaches an all-time high due to its cost efficiencies and compounding returns, such as branding and data-driven insights into products and all major digital strategies such as paid search, email, and social.
Market conditions can force organizations to prioritize specific competitor strategies.
Search algorithm updates may prioritize credibility and authoritative sources, which means content should be optimized accordingly. I will share more on this later in this article.
Economic changes can also accelerate the use of new technologies, requiring businesses to be flexible and adaptable, and exercise caution in adoption.
Enterprise SEO pros must liaise with key management stakeholders monthly to ensure their strategies align with key business priorities to avoid going down unproductive pathways.
You must use data analytics effectively to understand target audiences and what is changing.
As enterprise SEO is a multi-stakeholder discipline, insights must be fed into organizational strategies to create more holistic, not just channel-agnostic, individualized experiences.
These can range from lead magnets that take the form of tailored marketing communications to customized product content and campaigns.
2. Using Generative AI For SEO And Content: Managing Risk Vs. Reward
According to Bloomberg Intelligence, by 2032, generative AI will be worth $1.3 trillion. Additionally, Gartner research shows that SEO and content marketing are two of the highest areas of increased investment.
Numbers vary depending on the source, but if you drill down, well over 2,000 generative content AI tools are flooding the market. No doubt you hear about a new one in the news every week!
The challenge for enterprise SEO pros who want to boost content productivity and performance lies in balancing the risk versus reward of using these tools.
Risk: Some of the content generative tools focus on velocity over quality. This is challenging for the consumer and search engines and limits the chance of your brand being discovered in a sea of nonsense.
This is because they are based on single-source, low-quality data sources that are not trained to understand your audience’s needs and wants. They have no understanding of what works in content & SEO.
For brands, this means the content can get buried below irrelevant, low-quality spam-like articles. Over time, I expect Google to solve this.
In addition, as a result, we are seeing more and more government and organization institutions building ethical AI and content creation guidelines and standards related to data use, regulation, and governance.
Always remember the risks.
Generative AI has severe limitations and liabilities, including the tendency to “hallucinate” by fabricating information when it doesn’t have an answer.
It can state misinformation so convincingly a reader new to the topic may believe it to be fact.
It lacks creativity and produces output that tends to be generic and formulaic.
The content produced is only as good as the input (prompts) and oversight (editorial process) –garbage in, garbage out.
Reward: On the flip side, if correctly used, generative AI tools can help improve content productivity and scale content for SEO campaigns.
Help give valuable insights and inspiration: The cornerstone of successful campaign development is the strategic generation of ideas. Marketers can create compelling content by using generative AI to uncover popular search terms, monitor social media trends, and discover unique angles and ideas.
Accelerate content production creation efficiency: Generative AI can also help segment audiences based on demographics, preferences, and behaviors, enabling you to tailor personalization strategies and unique experiences. It can also assist in timely (short-from) email marketing and crafting specific messages for each key target audience.
Scale productivity and performance: For enterprise SEO pros who use platforms rather than multiple tools with disparate data sources, AI-generated content can be created in one platform that also helps you streamline workflows. Due to built-in privacy considerations and guardrails, platform-specific generative AI tools are likely safer to use. They can create content based on your existing assets and utilize high-fidelity and secure data based on search and content patterns. These are helpful for efficient content discovery and distribution, allowing you to focus on strategy and creation.
Recommendations from all-in-one platforms also act as a content and SEO best practice assistant.
3. Preparing For Search Generative Experiences: Your Content And Your Brand
The transition to Search Generative Experiences (SGE) marks the most substantial transformation in the history of search engines – and a seismic shift that will impact all industries, affecting every company and marketer globally.
SGE represents a paradigm shift in SEO, moving beyond traditional keyword-based tactics to embrace the power of generative AI.
As AI emerges and becomes almost a “mediator” between a company’s content and its users, one search can produce results that would have previously taken five separate searches.
Take retail shopping as an instance: AI will start to recommend a complete shopping experience that gives consumers an experience that contains many channels and sources and multiple forms of media.
For consumers, this promises deeper and more interactive experiences, leading to increased engagement and time spent on Google.
For brands, it means higher value clicks once a consumer is ready to visit your website.
I have been monitoring this (at BrightEdge) for a long time. I see experiments in critical areas that you should keep an eye on! For example:
Testing of over 22 new content formats in SGE results.
There are many warnings in the healthcare and YMVL industries, as Google is exercising caution.
New visual content formats are used in industries such as e-commerce.
More reviews are being added to results in areas like entertainment.
There is a big focus on places (local) being integrated into results.
To help SEJ readers and the whole community, you can view for free (ungated) the data behind all these findings and a step-by-step guide to understanding this Ultimate Guide to SGE.
Note: This is still in Google Labs and has not been rolled yet. However, from the above, I firmly predict this is a matter of when, where, and how it will proceed.
4. Understanding And Adapting To New Search Behaviours: Data And Conversational Intent
Utilizing data to grasp user behavior and the underlying intent in conversations will be crucial for SEO success in both traditional and AI-driven search results.
Search is becoming conversational, and marketers must focus on user intent, advancing their understanding of their audience from simple keyword optimization to grasping conversational intent and extended phrases.
For users, this translates into more captivating and immersive experiences, leading to increased time spent on Google. This optimizes their search, guiding them swiftly to the most pertinent websites that cater to their unique needs.
For marketers, navigating your search presence becomes more intricate yet more fruitful. Anticipate reduced but higher-quality web traffic. Identifying key searches that activate various types of results is essential.
Clicks will carry greater monetary value due to enhanced conversion rates. This is because consumers are more ready to act after being informed and influenced by prior interactions and data from Google.
Marketers need to guarantee that their content strategy not only answers the specific query but also considers the broader context in which the query is made. This will help ensure targeted and effective engagement with users.
However, the core fundamentals of technical and website SEO remain the same. They will become more critical as marketers shift to optimizing their sites for higher-value traffic and clicks.
Ensure your site is fast and responsive, it is structured, and the content is optimized for human readers. It should be structured to answer their questions in the most engaging and user-friendly way.
Ensure your content assets are primed for conversion with clear CTAs.
Focusing on contextual signals will be vital for content marketers who want to maximize performance.
For example, schema markup,E-E-A-T, and HCU (even though not regarded as ranking factors) are vital, so search engines and users send signals so they can understand the context behind your site and content.
Leverage data to decode user behavior and the intent behind conversations, using this insight as a catalyst for generative AI outcomes.
Develop and refine various content types, such as videos and images, to enhance engagement.
Coordinate marketing efforts across paid media, social platforms, and public relations to create a unified content campaign strategy.
Concentrate on tracking metrics like traffic and converting high-quality down-funnel traffic as consumers spend more time on Google before making informed decisions and visiting your website.
And, as I know, you are now thinking. Yes, SGE could mean slightly less but more qualified traffic.
5. Managing Omnichannel Marketing: Managing SEO And Multiple Marketing Disinclines
SEO has long shifted from being a siloed channel, but enterprises must make changes now as consumers and search engine demands drive the need for even closer collaboration.
Given that the SERPs and AI-generated SGE results encompass a variety of media types and formats – including social media, reviews, and news sources – content marketers will need to get closer than ever to their SEO, digital branding, design, social media, and PR teams.
Screenshot for search for [food delivery near me], Google, February 2024
Consumers are no longer consuming media in silos, and that means marketers cannot operate SEO and digital marketing in silos. More than managing PPC and SEO campaigns with a bit of social media will be required in 2024.
This is especially true as AI-powered results contain multiple formats and sources. Whether you are a big brand or not, whoever provides the best experience will win in 2024 – so expect some curveballs from your competition.
This means the relationships between people, processes, and technology must change.
Make sure you are aligning your teams and managing workflows across:
Design – Images and video.
Branding and PR – Messaging and company reputation.
Content – From text to design to social.
SEO – PPC and Website teams.
Customer Service teams – For reviews.
Sales teams for advice on down-funnel CTAs on your site.
For enterprise SEO pros, platforms are the only way you can do this.
Key Takeaways For Enterprise SEO Success In 2024
SEO today is going to be different than SEO tomorrow. SEO tomorrow will be different than the search in March.
Image from author, February 2024
Change is the core constant we all share in this industry. Time has shown us that those who keep up with trends and adapt quickly survive and thrive.
Never forget many of the core principles of SEO still apply, but be ready to help your organization become more agile so your success in enterprise SEO and AI is guaranteed.
In 2024, regardless of the search source, once a consumer clicks, brands that give them the best experience win.
More resources:
Featured Image: Sutthiphong Chandaeng/Shutterstock
Gone are the days when AI was merely a distant concept.
Today, AI has already been integrated into our daily lives through various applications and services, transforming how we interact with digital platforms.
A few years ago, AI operated silently behind the scenes, facilitating data processing and optimization for large services.
However, starting in 2023, its presence has become ubiquitous, manifesting in the features and functionalities of the apps and tools we use regularly.
What’s particularly fascinating is the bold strides made in the integration of AI into the very tools we use to create and work.
Consider the emergence of AI-powered image creation tools that generate visuals from textual descriptions or transform sketches into intricate 3D models in real time.
Video creation, once labor-intensive, is now more accessible and creative, thanks to AI-driven algorithms that handle background/object detection and stylization.
My background in design has compelled me to explore how these advancements will reshape our interactions with devices and software.
We are witnessing a shift from the traditional keyboard and mouse interaction towards more natural forms of communication with AI-integrated tools.
This transition from manual inputs to intuitive conversations and descriptions empowers users to become orchestrators of technological capabilities.
Does AI Enhance Or Compromise The Authenticity Of User Interactions?
The ongoing discourse surrounding AI’s role in UX design centers on whether it enhances or compromises the authenticity of user interactions.
Advocates view AI as a transformative force, empowering designers to personalize experiences, predict user behavior, and streamline processes.
Yet, skeptics raise concerns about the potential erosion of genuine human interaction, urging caution against the over-reliance on algorithmic intervention.
The rapid pace of AI innovation necessitates a delicate balance between harnessing its potential and preserving authenticity.
While AI offers unprecedented opportunities, its integration poses ethical dilemmas and challenges UX professionals to navigate complex terrain.
The need for responsible AI adoption underscores the importance of prioritizing user-centric design principles, maintaining transparency, and fostering open dialogue.
Ultimately, the future of UX lies in striking a balanced approach: leveraging AI’s capabilities while preserving the authenticity of user interactions. We must forge a path where technology enhances – rather than compromises – the human experience.
Expanding AI Applications And Their Impact On User Experience
AI is reshaping our interactions with cameras, transcending their traditional role as image-capturing devices.
Equipped with AI algorithms, cameras extend beyond mere photography to recognize QR codes, translate texts, and facilitate visual searches. This evolution transforms the camera into a dynamic input tool, effectively bridging the physical and digital realms.
Consider the Dot-go app, which leverages smartphone cameras to initiate automation processes.
Originally designed to aid visually impaired individuals, this innovative application demonstrates the broader potential of AI-powered cameras to enhance daily experiences for everyone.
From identifying bus routes to calculating calorie intake, AI-powered camera applications offer boundless possibilities for seamless integration into everyday life.
As AI progresses, it will further enrich user experiences through natural interactions such as facial recognition and gesture control. This highlights the importance of striking a balance between automation and human touch.
A Firsthand Look At How AI Empowers Developers
GitHub Copilot exemplifies the fusion of AI and developer collaboration, transcending its role as a mere tool to become a meeting point between developers and AI. (Disclaimer: I worked for GitHub.)
GitHub’s machine learning experts dedicated themselves to enhancing Copilot’s contextual understanding, recognizing effective communication as the linchpin of seamless collaboration.
During my time as GitHub’s SEO manager, I witnessed firsthand the remarkable fusion of AI and developer collaboration during the development phase of Copilot.
More than just a tool, Copilot represents a convergence of minds between developers and their AI pair programming counterparts.
Machine learning experts from GitHub tirelessly researched, developed, and tested new capabilities to enhance Copilot’s contextual understanding.
They recognized that effective communication is essential to pair programming, emphasizing the significance of inferring context to facilitate seamless collaboration.
As a marketing team member, I played a pivotal role in ensuring complete visibility from search to all communications surrounding the project. It was a project that genuinely excited me.
The evolution of Copilot from its inception to its widespread availability represented a paradigm shift in AI-driven coding tools. Leveraging OpenAI’s Codex model, GitHub Copilot emerged as the world’s first generative AI coding tool at scale.
The journey wasn’t just about developing a tool; it aimed to empower developers to focus on meaningful work.
Through meticulous experimentation and iteration, GitHub’s team honed Copilot into a resource that accelerates tasks like code completion and fosters creativity and efficiency.
The collaborative efforts behind Copilot underscored the significance of good user experience and the seamless integration of AI technologies into the developer workflow.
As a result, Copilot continues to revolutionize the way developers work, offering tailored suggestions and insights that amplify productivity and innovation in coding endeavors.
Optimizing The User Journey With Human-AI Collaboration
AI is a pivotal catalyst for personalization, intelligent automation, and predictive analytics in UX design.
By analyzing user data and behavior, AI empowers designers to create bespoke experiences that deeply resonate with individual preferences.
This AI-driven approach fosters engagement, efficiency, and data-driven decision-making, leading to significant improvements in SEO rankings.
Thus, integrating AI-driven UX design not only optimizes user satisfaction, but also boosts a website’s visibility and authority in the competitive digital landscape.
However, as with any technological advancement, ethical considerations loom large.
Designers must navigate data privacy, bias, and transparency issues to ensure AI algorithms uphold moral standards and minimize negative impacts on users.
Key Takeaway
AI’s transformative impact on user experience design is undeniable.
By embracing AI’s capabilities and collaborating with skilled experts, designers can harness its potential to deliver exceptional experiences that meet or exceed user expectations in the digital era.
As we continue to innovate and adapt, the synergy between human creativity and AI technology will profoundly shape the future of interaction design.
An “ideal customer profile” describes a company’s most valuable prospects, those who find a product or service seemingly perfect for their needs.
Ideal customer profiles help merchants:
Select marketing channels,
Create ad copy and design,
Narrow outreach,
Build email sequences,
Produce how-to, problem-solving videos.
AI platforms have vast databases of businesses and their audiences, helpful for defining an ideal customer. I tested three platforms for this article.
Custom GPT: ICP Generator
“ICP – Ideal Customer Profile Generator,” a custom GPT (available for ChatGPT Plus subscribers), creates profiles based on a URL. I tested it on Smarty Marketing, the site I launched last year. The results were useful, although lacking specifics. My company’s ideal customers per the custom GPT are:
In the growth phase: Companies aiming to expand their online presence, increase website traffic, and enhance brand visibility.
Digital forward: Businesses that understand and value digital marketing’s impact on growth and are ready to invest in innovative SEO strategies.
In competitive markets: Enterprises in industries where online competition is fierce, making them more likely to benefit from unique and effective SEO and link-building strategies.
Content creators: Organizations that produce valuable content and can leverage infographic marketing and social media to engage and expand their audience.
Seeking long-term results: Businesses focused on building lasting brand awareness and not just short-term gains, aligning with Smarty Marketing’s emphasis on long-term outcomes.
I could continue prompting the custom GPT for the best keywords in organic and paid search campaigns, the best social media platforms, helpful Facebook audience targeting, and so on.
Lemlist
Lemlist builds free ideal customer profiles based on a URL. The profiles are personas with names, demographic details, goals and objectives, and their potential outreach strategies. The reports are useful for ideas and brainstorming. The most helpful sections are:
An ideal customer’s responsibilities and pain points,
The ideal customer’s most effective marketing channels (“touchpoints”),
Risks to ideal customers of not achieving goals.
Lemlist builds free ideal customer profiles based on a URL — with names, demographic details, goals and objectives, and potential outreach strategies. Click image to enlarge.
For example, Lemlist identified my company’s ideal customer as a marketing director (spot-on) with these pain points:
Struggling with understanding organic search strategies, underperforming marketing campaigns, and lack of unique digital content.
And the risks to my ideal customers of not solving problems are:
Continued decrease in online visibility, inability to compete with competitors’ online presence, loss of potential leads and sales.
M1-Project
M1 Project offers various AI-powered marketing tools, including generators for an ideal customer profile and a marketing strategy. Input your URL and M1 Project will:
Create a product description,
List the problems your products solve,
Segment your target audience.
Edit the descriptions, problems, and segments to your business. Then choose your preferred segment, and the tool will create an ideal customer profile. The downloadable document costs $99 and includes the ideal customer’s:
Position, income, and pain points,
Tools or platforms (potential partners for your business),
Screenshot from: blog.youtube/news-and-events/disclosing-ai-generated-content/, March 2024.
Screenshot from: blog.youtube/news-and-events/disclosing-ai-generated-content/, March 2024.
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