Rellify's Blog

By Jayne Schultheis — Marketing has always been about understanding people — their desires, their pain points, their hidden motivations. But what if you could have a digital partner that understands your customers better than they understand themselves? Welcome to the world of agentic AI marketing, where intelligent systems don't just analyze data — they predict, personalize, and propose courses of action.

In this article, we'll dive into how agentic AI is transforming marketing from a game of educated guesswork to a science of pinpoint precision. We'll explore how these intelligent systems are reshaping everything from customer segmentation to personalized content creation.

Ready to build an agentic AI marketing strategy?

What is agentic AI?

Agentic AI refers to artificial intelligence systems that have advanced decision-making capabilities and the ability to act autonomously, without the need for direct human oversight. Agentic AI can analyze complex data, make decisions in real-time, and execute tasks on its own. These systems are designed to solve problems, adapt strategies, and improve outcomes by learning from their environment and adjusting their actions accordingly.

Agentic AI allows for more agile, data-driven marketing strategies that evolve based on continuous learning.

At Rellify, our patent-pending platform automatically creates custom AI models trained on data from your industry and competitors to be a subject matter expert. We leverage agentic AI to analyze content opportunities so you can identify and address relevant topics and trends ahead of your competition. Using that data, our platform can then autonomously select the best keywords and natural language queries for each topic. If you choose, it also can general content automatically.

To learn more about how it could help your business, contact us for a free demo.

Benefits of using agentic AI in marketing

Agentic AI is still in an experimental stage, and lots of companies are still figuring out exactly how to best use natural language processing tools and machine learning within their already-established processes. Marketing automation in any form still needs the helpful, watchful eye of human oversight, especially since predictive modeling can operate on inherent biases

Here are some of the broader ways you can expect to see positive growth when you employ agentic AI in your marketing:

• Efficiency and speed. Automate repetitive tasks and reduce time spent on manual data analysis and decision-making.
• Scalability. Scale campaigns and operations without additional human resources.
• Better customer experience. Improve the customer experience through seamless, personalized engagement and recommendations.
• Data-driven insights. Leverage vast amounts of data for more accurate insights and lead generation.
• Cost-effectiveness. Cut costs by automating processes and optimizing campaigns.

Now, let's take a closer look at how you might develop and implement an  agentic AI marketing strategy.

What makes a great agentic AI marketing strategy?

If you're considering agentic AI, you'll want to know the mechanisms and algorithms in play, just as you would want to know a job candidate's qualifications before you put them to work.

For an effective agentic AI marketing strategy, you'll need several key components come together.

Advanced personalization

In today's market, the name of the game when it comes to consumer engagement is personalization.

Advanced personalization with AI takes this a step further. Agentic AI can analyze vast amounts of customer data and use it to create hyper-targeted, individualized experiences. Unlike traditional methods that rely on broad demographic categories or pre-defined customer segments, agentic AI dives deeper into behavioral data, such as browsing habits, purchase history, social media interactions, and even sentiment analysis from customer feedback.

By continuously learning from this data, agentic AI can understand each customer's unique preferences, needs, and pain points in real time. For example, AI can tailor email subject lines, product recommendations, or even website layouts based on a customer’s previous interactions, interests, and even their stage in the customer journey.

Furthermore, agentic AI can adapt to changes in customer behavior on the fly. If a customer shifts their preferences or starts exploring new products, the AI can automatically update its recommendations and adjust marketing strategies without human intervention. Each person who interacts with your brand could receive a continuously evolving, personalized experience that drives engagement, conversion, and customer retention.

Predictive analytics and forecasting

One of the greatest benefits of this type of technology integration is the elimination of guesswork when it comes to predicting what will work for your brand.

• Data sourcing. Agentic AI uses automation to collect and integrate big data pools from various sources in real time, including customer behaviors, website interactions, social media, CRM systems, and market trends. This allows for a more holistic view of the market and customer behavior.
• Customer insights and market segmentation. Agentic AI can use machine learning algorithms to create highly granular customer segments based on predictive behaviors, such as likelihood to buy and lifetime value. This helps marketers target the right audience with tailored messages. Agentic AI can also help forecast the potential lifetime value of different customers or customer segments. Businesses can then focus resources on retaining and nurturing high-value customers through the sales funnel.
• Behavioral analysis and predictions. It can predict future customer actions such as buying decisions, churn, and engagement, based on historical data and real-time signals. Businesses can optimize campaigns before they even launch.

Streamlining marketing campaigns and ROI optimization

When you're running a small to medium-sized business, every single penny counts. Agentic AI can help cut out wasteful spending and sharpen your focus on paths that have the best chance of success.

• Dynamic pricing models. Agentic AI can help predict demand fluctuations and adjust pricing strategies in real time to maximize revenue and market share. It can analyze historical pricing patterns, competitor pricing, and consumer demand elasticity.
• Efficient budget allocation. Agentic AI can predict which marketing channels, ads, or strategies are likely to bring the highest ROI, helping businesses allocate marketing budgets more efficiently. Dynamic resource allocation minimizes waste and maximizes the impact of every dollar spent.
• Scenario simulation. Agentic AI can model future scenarios and predict outcomes for different marketing strategies, allowing businesses to select the most profitable options. This leads to better decision-making and reduced risk. Think of it like virtual reality meets digital marketing, and you achieve the best outcomes without real-life trial and error.
• Scalable campaign execution. Once predictive models are in place, agentic AI can automatically execute marketing campaigns at scale and adjust variables based on continuous data feedback.
• Competitor analysis. By autonomously tracking competitors’ activities, pricing strategies, and marketing campaigns, agentic AI can predict their next moves and help businesses position themselves effectively in the market. More broadly, agentic AI also can forecast industry trends and competitor actions.

Challenges and considerations with agentic AI

While agentic AI offers tremendous marketing advantages, it also introduces significant ethical considerations. The ability to analyze vast consumer data and predict behaviors raises data privacy concerns. These systems might access and use personal information in ways consumers never intended or consented to.

There's also the challenge of algorithmic bias. If the AI is trained on skewed data, it may perpetuate or even amplify existing prejudices, unfairly targeting certain demographics while excluding others.

Transparency presents another hurdle. When AI automatically decides who sees which marketing messages, both marketers and consumers may lose visibility into how these choices are made.

Companies must balance effective marketing with the ethical responsibility not to manipulate consumers, especially vulnerable populations. Organizations implementing agentic AI must develop clear governance frameworks, establish boundaries for AI autonomy, and regularly audit their systems to ensure they align with both regulatory requirements and broader societal values.

We should also address the elephant in the room: Is agentic AI going to replace real-life employees? We think that AI won't replace human creativity. Instead, it can enhance it by creating hybrid workflows where AI handles the data-heavy tasks and human marketers get more time to focus on strategic planning, creativity, and brand positioning.

Case study: How HubSpot's Breeze uses agentic AI to transform marketing workflows

Before implementing Breeze, HubSpot had noticed that marketing teams faced some very real challenges:

• Lead nurturing sequences required constant manual adjustment.
• Campaign performance analysis consumed hours of specialist time.
• Personalization efforts couldn't scale effectively.
• Despite having access to mountains of customer data, it was difficult to extract actionable insights quickly enough to respond to market changes.

The AI solution

In early 2024, HubSpot rolled out Breeze, an agentic AI system designed specifically for marketing workflow automation. It can observe, learn, and make autonomous decisions within carefully defined parameters.

Breeze integrates with HubSpot's existing marketing platform, analyzing real-time data from multiple sources: website interactions, email engagement, social media activity, and CRM data ability. The system can:

• Enrich company and contact records so you can make data-driven decisions to convert your best opportunities.
• Personalize content at scale by understanding individual contact behaviors, preferences, and buyer intent.
• Optimize lead scoring models by identifying which engagement patterns truly predict conversion
• Create optimized forms that autofill information from the Breeze Intelligence commercial database behind the scenes — and convert better.

Hubspot also offers specific AI "agents" that are specialized for certain functions:

• Breeze Content Agent. Create quality blogs, landing pages, podcasts, and case studies in your brand voice.
• Breeze Social Media Agent. Analyze performance, industry data, and best practices to create compelling social content.
• Breeze Prospecting Agent. Craft and implement tailored outreach for CRM prospects to enhance your sales pipeline.
• Breeze Customer Agent (Beta). Respond quickly to site visitors with AI trained on your website, blog, and knowledge base.

The results

Six months after full deployment, HubSpot customers documented remarkable improvements in their processes, including:

• Higher marketing-qualified lead conversion rates.
• Lower cost-per-acquisition across digital channels.
• Less time spent on routine campaign adjustments.
• Better email engagement metrics like click-through rates.

Perhaps most significantly, the marketing team reported spending more time on creative and strategic initiatives than before Breeze implementation.

Best practices for agentic AI employment in marketing

When any company decides to employ new digital tools, especially one like agentic AI which is still in its infancy, it's important to set some clear parameters for how it will be used within your processes.

1. Start with clear boundaries. Define explicit parameters for the agentic AI's decision-making authority, gradually expanding them as trust developed.
2. Maintain human oversight. While agentic AI operates autonomously, you should establish regular review protocols and approval thresholds for major changes.
3. Focus on transparency. Make sure you can explain the AI's decisions in business terms that marketers could understand and evaluate.
4. Invest in team adaptation. Devote resources to helping marketers develop new skills for collaborating effectively with AI systems.

The Rellify difference

Rellify is no stranger to the realm of agentic AI. Rellify can help you harness AI to transform your content processes for the better. Whether you're looking for content gaps in your niche or need to implement robust marketing campaigns to win better leads, Rellify implements targeted AI content solutions to help you meet your goals.

With a custom Relliverse™, you can have an in-house, customized AI subject-matter expert that shows your team the best content opportunities.  ‍We use it to find niche topics and keywords that will poise your brand as an expert in your industry. And when you're an expert, you're better found online.

If you're ready to see how Rellify can transform the way you do content marketing with cutting-edge AI-powered insights, schedule a brief demo today with one of our experts!

Welcome to the era of agentic AI, where smart systems aren't just following orders but actively solving problems like clever colleagues. What is agentic AI? Agentic AI refers to an artificial intelligence system that  can analyze data, develop solutions and put them into effect autonomously.

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At Rellify, we're leveraging agentic AI workflows for content opportunity analysis so you can spot and speak to the relevant topics and trends ahead of your competition. Our patent-pending platform automatically creates custom AI models trained on relevant market data to be a subject matter expert. Our platform can then autonomously select the right keywords, phrases and natural language queries associated with topics related to the growth opportunities you decide to act on.

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We'll be happy to show you how it works. Just contact us for a free demo.

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Understanding this shift toward autonomous decision making and execution is like discovering electricity while competitors still use candles. Another remarkable AI evolution  has occurred — from digital assistant to digital strategist.

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In this article, we'll explore what's happening now and what's waiting just around the corner. We'll look at specific examples of how these intelligent agents are bringing innovation to fields like healthcare and manufacturing. And we'll examine the possibilities alongside the challenges. Then you'll be set to leverage agentic AI for both competitive advantage and lasting growth.

Types of agentic AI systems: A comprehensive overview

Agentic AI represents a leap in artificial intelligence: autonomous systems that don't merely follow instructions but independently perceive, decide, and act with minimal human oversight. At their heart, these systems use advanced algorithms to learn from and adapt to their environments.

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One example that dramatically brings this home is the way two AI agents can now talk to each other in "Gibberlink Mode," a protocol tailored for machine efficiency that enables AI-to-AI interactions. The fact that they communicate in a language that humans can't understand, however, raises questions involving control, ethics, and security.

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Developers have created different types of agentic AI systems with specific capabilities and purposes in mind. Let's look at the major categories of these AI applications and systems and what makes each distinct.

Reactive agents

Reactive agents, the simplest form of agentic systems, operate based on the current state of their environment without maintaining memory of past states or actions.

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These systems follow a direct stimulus-response model, matching specific situations to specific actions. Think of them as implementing sophisticated "if-then" rules, like a chess-playing program that evaluates the current board state to select a move without explicitly planning multiple steps ahead through internal modeling.

Model-based agents

Model-based agents maintain an internal representation (or model) of their environment, allowing them to understand how their actions affect the world around them. This internal model enables them to predict potential outcomes before acting. These agents excel in complex, dynamic environments where understanding causal relationships is crucial — like controlling an autonomous vehicle.

Goal-based agents

Rather than simply responding to their environment, like model-based agents, goal-based agents continuously evaluate how different actions might help them achieve specific objectives. They can use means-end predictive analytics to consider actions will lead to desired outcomes.

Utility-based agents

Utility-based agents refine the goal-based approach by measuring the desirability of different states. Instead of viewing goals as binary (achieved or not), these systems can evaluate how preferable one outcome is compared to another. A financial trading agent, for example, would go beyond a goal of "make money." A sophisticated utility function could  balance potential returns against risk exposure, liquidity constraints, and diversification principles.

Learning agents

Learning agents incorporate mechanisms to improve their performance over time based on experience. They modify their internal models, decision processes, or evaluation criteria as they interact with their environment.

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A recommendation system is an example of this approach. Initially, it might make suggestions based on general patterns, but as it observes user interactions, it refines its understanding of individual preferences to provide increasingly personalized recommendations.

Multi-agent systems

In multi-agent systems, AI-powered autonomous agents interact within a shared environment. These agents may cooperate toward common goals, compete for resources, or engage in mixed strategies with both cooperative and competitive elements.

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Smart traffic management systems demonstrate this approach, with individual intersection controllers coordinating to optimize overall traffic flow while each manages its local conditions. Coordinated behavior of multiple agents works better than centralized control.

Hybrid architectures

In practice, many sophisticated agentic systems employ hybrid architectures that combine elements from multiple categories. These systems might use different approaches for different aspects of their operation or switch between modes based on context.

Real-world applications of agentic AI

Agentic AI isn't just changing industries — it's helping to reinvent them. Here are two examples of how these intelligent systems are being applied.

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GE Healthcare has leapt into agentic AI with cloud-related research and development efforts. Their "Health Companion" project explores whether an agentic AI approach driven by multiple agents, each an expert in a particular area (i.e., genomics, radiology, pathology), could help physicians streamline their clinical decision-making and deliver more personalized care. Their vision for the project is for these agents to collaborate and analyze multi-modal data in order to proactively generate treatment plan recommendations, continuously adapting based on new information.

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Toyota is one manufacturing company that's been raising operational efficiency with agentic AI. Its “O-Beya" system draws on design data from real-life engineers and other sources to inform nine specialized AI agents. If, for example, a car designer asked O-Beya how to make a car run better, an "engine agent" might give an answer related to engine output while a "regulatory agent" provides an answer on limits to emissions, which O-Beya would then consolidate into a single reply. 

What is agentic AI's future

We can expect agentic AI to become more integrated into business strategy, but ethical considerations and regulatory frameworks will be critical for its responsible development and scalability. Here are just a few things you can anticipate in the development of agentic AI:

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• Increased automation. AI will handle more complex, real-time tasks across sectors like marketing, healthcare, finance, risk management, and autonomous driving.
• Personalization & interactivity. Expect more adaptive, human-like AI that personalizes interactions in areas like virtual assistants, e-commerce, and education. AI will increasingly understand and respond to human emotions, making interactions more natural and useful.
• AI ethics and governance. As AI autonomy grows, there will be a stronger push for ethical guidelines, regulation, and making sure AI aligns with human values to avoid harmful outcomes. AI content generators themselves have already run into some ethical snags in education, as students use AI generators to complete assignments.

Rellify's AI difference

Rellify will continue evolving alongside agentic AI technology, harnessing it to help businesses find topics and create content that resonates with their target customers.

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As we have seen, part of agentic AI involves one model thinking about how to solve a problem and then asking other models to go solve it. In a sense, that's what a Relliverse™ does for our clients. It "thinks" about the content opportunities and then prompts another model to capture them. ‍With a custom Relliverse™, you can leverage deep learning, machine learning and AI research to change the way you plan, write, and distribute content.

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Ready to find out how? Contact a Rellify expert today for a demo and find out exactly what you're missing.

By Jayne Schultheis — As AI-powered language learning models improve at a rapid pace, many businesses are integrating AI-generated content into their processes. Others are waiting to see if that content is worthwhile. AI-generated content might seem like a time-saver for businesses that lack the resources to employ human writers. However, it comes with many caveats and limitations, most notably, AI content quality.

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In this article, we'll take a closer look at the effectiveness, creativity, and authenticity of AI versus human content, providing insights into maintaining editorial standards and consumer trust.

Understanding AI-generated content: The mechanisms at play

AI-generated content is text produced through the use of advanced technologies, including machine learning and natural language processing. These technologies allow systems to analyze vast datasets and learn linguistic patterns and contextual nuances. As of 2025, AI can generate coherent and contextually relevant content when given a great prompt. To effectively integrate AI into their content strategies, businesses need to understand its foundational mechanisms.

Machine learning (ML) in AI-generated content

Machine learning is a subset of AI that involves training algorithms to recognize patterns in data and make predictions or decisions based on that data. In the context of AI-generated content, ML helps models learn from vast amounts of text data and improve their ability to generate relevant and meaningful content over time. The key ML techniques used in AI content generation include:

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• Training on large datasets. Machine learning models, particularly deep learning models (e.g., transformers), are trained on huge datasets that include books, articles, websites, and other forms of human-written text. This training enables the model to learn grammar, syntax, tone, context, and even specific domains or styles of writing.
• Reinforcement learning. This technique can be used to refine the output of a content-generating model based on feedback. For example, the model could be rewarded for generating content that aligns with specific goals, such as clarity, accuracy, or relevance to a topic.
• Fine-tuning. After the base model is trained on general data, it can be fine-tuned on specific types of content (e.g., scientific papers, marketing copy) to improve its performance for certain applications.

Natural language processing (NLP) in AI-generated content

NLP is a subfield of AI that focuses on the interaction between computers and human language. It allows machines to understand, interpret, and generate human language in a way that is both meaningful and contextually appropriate. In the generation of content, NLP allows AI to produce coherent, grammatically correct, and contextually accurate text. The main components of NLP that facilitate AI-generated content include:

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• Tokenization. Breaking down text into smaller units like words or phrases, which allows the AI to process and understand the structure of language.
• Syntax and grammar parsing. The AI uses syntactic rules to structure sentences properly, ensuring they adhere to grammar conventions and sound natural.
• Named entity recognition (NER). Identifying and categorizing entities like people, places, organizations, and dates within the text. This helps the AI generate content that is contextually aware and relevant.
• Contextual understanding. Modern NLP models, like GPT, leverage large-scale transformers that can capture long-term dependencies and nuances in language. This allows them to generate text that flows logically and coherently, maintaining the context across long passages.
• Sentiment analysis. This technique helps the AI detect the emotional tone of the text and adapt its output accordingly, which is especially useful for tasks like content marketing or social media posts, where tone is critical.

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Together, machine learning and natural language processing work to produce "natural language generation," or NLG.

What to consider when looking at AI content quality

While you might think that AI-generated content will save you loads of time and money, it's not without shortcomings. Here are some of the main pitfalls and pain points that marketers should keep in mind if they plan on using AI-generated content.

Accuracy

Accuracy is a huge concern for any marketer using AI-generated content. Even ChatGPT includes a disclaimer at the bottom of the page that says: "ChatGPT can make mistakes. Check important info." It should also be noted that most content generators are unable to produce verifiable facts, peer-reviewed studies, and well-sourced statistics. And great content that wins reader trust and builds authority provides verifiable, accurate information.

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Plagiarism presents a major ethics concern for those who rely on AI-generated content, especially since AI content generators are known to scrape information from sources without giving proper credit. Human oversight through proofreading and fact-checking should be a crucial part of content processes that rely on automation.

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Generative AI models might also exhibit biases, whether held by the company that owns it, or by the data that it was trained on. If you're going to rely on AI-generated content, it's crucial to have a critical eye for these types of biases and prejudices, and make sure that you're not exacerbating them.

Effectiveness

While entirely AI-generated content sounds like convenient resource for a business with limited resources, it has its caveats. Most AI-generated content can't seamlessly integrate SEO keywords into its copy. Human writers have a unique ability to integrate certain words based on semantic understanding and creativity, and AI is confined to its algorithmic capacities. And if your long-form content isn't SEO-optimized with great keywords, it won't reach your target audience. Not only that, AI-powered NLGs often favor certain phrases and organizational structures for writing that might not match your company's vision. A lack of consistency between your content and your target audience could make it more difficult for users to organically find your website through search engines.

Efficiency

While AI can generate content in mere seconds, if you have to go back and check facts, humanize the tone, and re-word your text to better match your brand, how much time and money are you really saving? Use of AI-generated content still requires a knowledgable expert to create the prompts, and eventually, review and edit the content. This is crucial as you're deciding how to allocate your resources when you decide to use AI.

How to reach your customers with AI-generated content

AI-generated content is continuously being refined during the current digital transformation. However, you still need the intelligence of a writer or editor who can plan, edit, and make good content great. Here are some tips for content management that will help you navigate the world of AI-content generation.

Define your target audience, topics, and keywords

Before creating AI-generated content, identify your target audience's needs, pain points, and interests. What questions do they ask? What problems do they need to solve? This will help you choose the right keywords and structure your content effectively.

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Use tools like Rellify, Google Keyword Planner, and Ahrefs to find relevant keywords, focusing on a combination of short-tail (broad) and long-tail (more specific) keywords. AI tools can suggest semantically related keywords that help improve relevance and ranking.

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Rellify rises above other tools in this category, as it uses machine learning and AI to find topics and keywords. In the Rellify platform, once you have your topics and keywords ready, you can create content that comes with real-time feedback on improving SEO. You can even use our AI support feature to help you get started, whether that's suggesting headlines, continuing text, or writing meta descriptions.

Provide value

Even though AI can generate content quickly, make sure it adds real value for your readers. Content should be useful, informative, and answer specific questions or solve problems that your audience is searching for. Pay special attention to user intent as you curate content, focusing on the "why" behind each search query.

Optimize length and depth

Aim for comprehensive, in-depth content (around 1,500–2,500 words) that covers a topic thoroughly. Long-form content often performs better in search rankings, but be sure to keep it engaging and not verbose. Generative AI will often use the same repetitive phrases or even cover the same points over and over.

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One of the best ways you can use AI in your processes is by asking for a comprehensive outline. AI tools can be especially helpful in structuring heading, subheadings, and bullet points to break it down for readers. Rellify's AI tools can quickly generate an outline based on your chosen keywords and phrases.

Focus on originality

While AI can generate content efficiently, make sure the content is unique. Plagiarism can hurt SEO rankings. Use tools like Copyscape or Grammarly to check for originality before publishing. And again, a little bit of "humanization" can go a long way when it comes to user experience. Readers want to know that someone cared enough about the topic to take some time to speak to them about it. In the words of one of my colleagues, "why would I want to read something that no one could be bothered to write?"

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As you're looking for ways to "humanize" your text and set it apart, consider including:

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• Statistics relevant to your industry
• Case studies and testimonials
• Interesting and relevant facts
• Information about your unique product or services
• Stellar photos and/or graphics
• Colloquial phrases or humor that aligns with your brand's style

Optimize your SEO

We've talked a lot about "humanizing" but now we're going to talk about "Google...izing," that is, optimizing your content for search engines.

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• Title tag. Craft an engaging, keyword-rich title that is both informative and compelling. Ideally, include your primary keyword at the start of the title.
• Meta description. Write a concise meta description (150–160 characters) that includes your target keywords. This won’t directly affect rankings but can influence click-through rates.
• Header tags (H1, H2, H3). Use header tags to structure your content logically. The H1 tag should typically contain the main keyword and summarize the topic. H2 and H3 tags should break down the content into digestible subsections.
• URL structure. URLs should be simple, short, and include relevant keywords.
• Alt text for images. If you include images, make sure to add descriptive, keyword-rich alt text. AI can sometimes miss this, but it's essential for accessibility and SEO.
• Linking. Link to other relevant pages or blog posts within your website. This helps improve user experience and increases time on site. It also helps search engines crawl your site more effectively. You should also link to authoritative external sources where relevant, such as studies, research papers, or high-quality articles from well-known websites. Finally, acquire hyperlinks from other well-respected websites to your own site. These links, called backlinks or inbound links, indicate to search engines that your website is reputable, trustworthy, and authoritative. Backlinks are a ranking factor for Google SERPs and obtaining them is known as "link-building."

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These are just a few elements of SEO optimization, but you can find lots more information on Rellify's blog about how to improve your content by following some best practices.

The future of AI content quality

In the next few years, we're likely going to see rapid improvements in AI content quality. Platforms will be capable of generating content that is more creative, engaging, and personalized to individual user needs.

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However, human oversight will remain crucial for authenticity, originality, and ethical use. Ultimately, AI's role in content creation will be collaborative — enhancing human creativity, streamlining processes, and helping businesses to scale their content strategies more efficiently.

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Rellify is on the cutting edge of AI integration in a few different ways. Most notably, with a custom Relliverse™, you can better understand your company, topics, and content with a few clicks. With AI integration in topic clustering, you'll always know what to write about and how to write it so your content will be found by your target audience. Ready to find out more? Contact a Rellify expert for a brief demo and quote, and find out exactly how Rellify can revolutionize your content processes.

By Jayne Schultheis — The world of content creation is rapidly changing, and businesses increasingly face the challenge of producing high-quality material efficiently and cost-effectively. With the introduction of AI content generators, we have revolutionary technology transforming how content is created and used. By leveraging machine learning and natural language processing, AI content generators can potentially transform the way your company does content marketing.

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Request a live demo here to see Rellify's approach to contact marketing in action. Meantime, this article will explore the impact of AI on content creation, the ethical considerations, and the future innovations driving digital transformation in the business landscape.

Understanding AI content generators

These sophisticated tools leverage advanced algorithms to produce text that mimics human writing. By using machine learning and natural language processing, they can understand context, tone, and style. OpenAI is the creator of perhaps the most well-known conversational content generator model, ChatGPT. But plenty of other models have been created. They have been trained on different data sets, but have the same underlying technology and mechanisms.

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AI content generators are a versatile solution for creating different types of content — from short, quippy marketing copy to long-form articles packed with helpful information. Savvy businesses can streamline their content production processes, saving both time and resources for everyone working at the company. This adaptability makes AI content generators valuable to anyone who wants to maintain a competitive edge in the world of online marketing.

The technology behind AI content generators

AI content generators rely on the synergy of machine learning and natural language processing. This combination enables AI systems to analyze vast datasets, comprehend linguistic nuances, and generate content that closely resembles human writing. Let's look more closely at each element.

Natural language processing

Natural language processing (NLP) is a tool that uses computer science, AI concepts, linguistics, and data to allow computers to analyze human language — both written and verbal. It converts written or spoken words into data and makes it possible for devices to communicate with each other.

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These connected devices have changed our world — think of Amazon's "Echo Dot," for example. "Alexa" uses NLP to analyze voice-based  prompts, then uses that information to carry out instructions. That might be turning on the lights or adding to your grocery list. Other services and devices that use NLP include: chatbots (query management), climate control devices (thermostats), and home monitoring devices (security systems).

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We may not be aware that the response to our inquiry is generated by an algorithm, the driving force behind NLP, but it is. NLP allows computers to analyze vast amounts of data from chatbots, social media posts, documents,  webpages, and other sources.

Machine learning

Machine learning is a subset of artificial intelligence that involves computers' ability to learn by analyzing data and past experiences without explicit programming. Computers use algorithms to find patterns within and from data to solve problems and make predictions.‍

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‍In a typical day, the average person might use a few different machine learning systems. These could be simple, utility-based applications, like using a Roomba vacuum to clean a room. Or you could use machine learning for more complex tasks, like asking ChatGPT to give you a dairy-free recipe for snickerdoodle cookies.

AI content generators and their impact on content creation

Anyone who's worked in SEO can tell you that creating great longform content that organically resonates with both search engines and readers is no simple task. You need an extensive understanding of your target reader, how they prefer to ingest content, and what topics they're most interested in. This can feel overwhelming, especially without a large team of staff writers who have extensive knowledge of a target industry.

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AI content generators significantly help with efficiency, scalability, and quality by automating the writing of high-quality material at scale. They can rapidly produce articles, blog posts, product descriptions, and other forms of content. That means reduced time and effort required for human writers. Businesses can generate large volumes of content quickly without sacrificing quality.

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AI tools can also be fine-tuned to match specific tones, styles, and even industry nuances. When used effectively, AI-driven content generation means companies can quickly adapt to changing demands or create personalized, relevant content for various audience segments — all with less money, time, and effort.

The future of AI content generators

If you've been paying attention, you've seen that AI content generators have improved quite a bit since their inception. Ten years ago, barely anyone had even heard of the technology, and now it's everywhere. Since the nature of this technology is adaptive, it's going to continue to be refined, both by self-learning and by input from users. Let's look at some other ways we can expect AI content generators to evolve.

Integration with existing platforms and tools

AI content generators can be seamlessly integrated with lots of platforms and tools  —  whether it's a CMS, a grammar checker, or customer relationship management software. This allows users to generate or refine content directly within their current environment without needing to switch between multiple applications. Moreover, AI content generators can sync with data analytics platforms and SEO tools, providing real-time insights to optimize content for search engines or audience engagement. Rellify integrates AI content generation directly into our platform, which means you can streamline your entire content creation process, and automate the aspects you want.

Trends and innovations

You might have heard of "hyper-personalization" in the context of marketing. This is the practice of tailoring marketing messages, products, services, and experiences to individual consumers based on their preferences, behaviors, and demographics. It goes beyond traditional personalization by leveraging real-time advanced data analytics and AI algorithms to create customized and relevant interactions with customers.

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Businesses can use this marketing strategy with AI content generation to deliver curated content, customized products, and tailor-made product recommendations and services. They also can use it for targeted customer support through an AI chatbot. 

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McKinsey talks about customer care as the crucial missing piece that bridges the gap between hyper-personalization through AI and customer trust, calling it "proactive, predictive service." With the application of AI in customer care, its very nature changes from reactive to proactive. Companies will be better able to anticipate customer needs and resolving issues before they arise.

Challenges of AI content generators

As AI content generators become integral to business strategies, ethical considerations and challenges emerge. After all, humans have a much firmer grasp on the concept of nuance, personality, and creativity than machines do. How do you mitigate those concerns as you use this kind of technology?

Quality control

To maintain quality control while using AI content generators, implement robust monitoring and feedback systems. Leverage user insights and performance metrics to refine AI outputs to more closely align with your target audience's expectations. The more data you put into your AI content generator, the better your output will be.

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But even if you implement all the data you have on your customers' preferences and your company's branding, you might still end up with content that sounds a bit ... algorithmic. Until AI reaches its next phase of performance, use AI content generators as a content tool rather than an employee. That is — use AI content generators to help brainstorm ideas, build outlines, or build a foundation for your content that's ultimately refined by human intelligence. Every piece of content you put out should be edited and revised by one or more writers or editors.

Environmental concerns

The conversation around AI has veered into ethical concerns regarding energy consumption, carbon emissions, and resource usage. Training large-scale AI models, especially a language model like GPT-4, requires significant computational power. This process often involves powerful data centers running thousands of GPUs (Graphics Processing Units) or TPUs (Tensor Processing Units) for days or weeks, consuming large amounts of electricity.

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Once trained, AI models also require energy during inference (when the model generates responses or content). Although the energy required for inference is typically lower than for training, large-scale usage can still add up, increasing the carbon footprint of these operations.

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The question arises about whether the environmental costs of training and deploying these models are justifiable given the benefits of AI content generation, such as enhanced efficiency and scalability. Additionally, if AI tools are used in ways that generate massive amounts of content (like spam or low-quality material), the environmental impact may be disproportionate to the value created.

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To address these concerns, many organizations are now prioritizing sustainable AI practices, including using AI to optimize energy usage, reduce waste, and find solutions for climate change. The AI community is exploring how to balance technological advancements with environmental sustainability.

Upgrade your content processes with Rellify

Rellify can help you harness AI to transform your content processes for the better. Whether you're looking for content gaps in your niche or need to implement robust marketing campaigns to win better leads, Rellify implements targeted AI content solutions to help you meet your goals. With a custom Relliverse™, you can have an in-house, customized AI subject-matter expert that shows your team the best content opportunities.  

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Contact a Rellify expert today for a brief demo to find out more.

What does the post-DeepSeek era of AI mean for marketers?

I’m still replying to texts from colleagues (and friends, and family members) about DeepSeek’s breakthrough last week, and what it means for the future of artificial intelligence in the Valley. Our data scientists and ML engineers are busy testing DeepSeek, as we do all major models; so this week, I thought we should discuss a more specific piece of that question:

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What does the post-DeepSeek era of AI mean for marketers?

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First and foremost, we now know the cost of compute power using LLMs is no longer a key budgeting issue. This was enforced days after the news broke, when researchers at UC Berkeley were able to create a small scale reproduction of DeepSeek — for just $30 in compute costs! Of course the final training run for a small scale model build like this (or even DeepSeek's reported $6M cost) is just a fraction of the total infrastructure and R&D costs to catch up with the current market leaders; however, the main point here is the models themselves are rapidly being commoditized.

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I'm seeing first-hand the rapidly growing cost effectiveness of LLMs at my own company: In just the last year, our model training costs have been cut in half.

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This macro trend probably represents the imminent end of Google Search as we’ve known it over the last 25 years. Now that we can very affordably apply LLMs for most search requests, human use of Google-style landing pages rapidly dissipates. I think it’s likely up to 80 percent of classic Google search queries will be replaced by new AI-agent based search experiences over the next few years.

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And these cost savings are particularly exciting for digital marketing with startups and smaller companies. Without having to pay exorbitant computing costs, they can better compete with larger companies, creating LLM–powered content, analysis, and marketing research plans with modest budgets.

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The lessening of cost considerations also suggests that marketers should no longer treat AI as a “nice to have if we can afford it” side tool, but as an essential part of their work. Here’s why:

Content Marketing in the Era of Agentic Workflows

With LLM computing costs decreasing, the emerging opportunity for marketers goes far beyond content creation and summarization. My advice is they look into the potential of agentic AI workflows. Instead of using a single LLM for generating outcomes from direct prompts, agentic workflows ask a reasoning AI how it would solve a particular problem – and also, to ask other more specialized AI to solve it.

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Agentic workflows can help marketers better and more comprehensively collect customer insights into their audience and their competitors, along with the strength of their content strategies and business intelligence. And in a refreshing break from the SEO era search terms / web analytics mindset, we’re able to explore the market using more natural language definitions and topics analysis, and find breakout trends. And post-DeepSeek, do so at increasingly reduced cost, and with specialized vertical market applications!

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At Rellify, we've developed a platform that automatically generates company-specific machine learning-based models with deep knowledge of relevant topics which in turn are used to prompt LLMs. This way, our customers can focus more on the strategic questions like what topics to cover and differentiate their offering ---- focusing the power of LLMs in the creative process to help generate relevant content.

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This approach has repeatedly led to our customers' content investments driving visibility in both AI and classic SEO search results, because our vertical models identify what topics matter -- what are the relevant natural language questions that quality content should address -- not just what keywords drive the most search volume.

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All of the above is not to imply Google Search and the company's search algorithms are going away, I should add; data analytics around Google’s web index is still important for marketers working with LLMs; my own company uses it as a the best approximation of audience interest. It’s just that we should expect it to become less important – especially when building our marketing / content strategies.

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As for our company, Rellify, we have been planning for the time when OpenAI is no longer the undisputed industry leader in LLM models. I believe I’m not the only one glad to say that time is now.

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If you’re interested in what we’re doing, please get in touch; happy to chat further!

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Peter Kraus is CEO and founder of Rellify, the Content Intelligence company built from the ground up with AI to generate insights and strategies that transform the entire customer journey.

By Jayne Schultheis — A great website structure involves more than just looking good — it's a crucial factor in boosting your SEO performance. The architecture of your website directly impacts how easily search engines crawl and index your content, which in turn influences your rankings.

In this article, we’ll explore why website structure is an essential part of search engine optimization and how you can optimize your website to improve visibility, user engagement, and search engine rankings.

Website structure defines user experience

A well-designed site that provides useful and engaging content will encourage visitors to stay longer, reducing bounce rates and giving your site a better chance to draw attention.

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How do you use site structure to boost traffic and gather leads? What are the crucial elements that signal to both search engines and readers that you're a trustworthy and authoritative resource in your industry? We'll share a number of clear and effective ways to improve your content creation and web design. Let's call it a "UX design for SEO best practices" checklist for a site audit.

UX and URL best practices

When you're building an effective website, put yourself in the perspective of a site visitor who knows nothing about your site or products. In general, URLs should be:

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• Clean
• Short
• Descriptive
• Keyword rich
• Representative of the site's page hierarchy. For example: https://rellify.com/blog/content-strategy-challenges.

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When crafting a seamless user journey into and within your site, you'll want to implement:

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• Main navigation (top-level pages). The most important pages of the site should be easily accessible from the homepage. Most sites use a navigation bar across the top of the homepage that leads to product and service pages, contact page, about the company page, and others. The “hamburger,” which is three lines in the upper left corner of the site, the vertical bar, and the vertical drop-down bar are ways to offer vertical navigation bars that are useful on mobile devices.
• Categories and subcategories. Use categories, subcategories, and sub-subcategories to group related content logically, making it easier for search engines to crawl and understand.
• Breadcrumb navigation. Organize your URLs so that wherever visitors are on your site, they can see the path back to the home page. This technique takes its name from trail of breadcrumbs Hansel and Gretel left behind them to find their way home — although breadcrumb navigation works much better. Every page on your site should have an icon that can be clicked to return to the home page. Even so, this arrangement of URLs allows search engines and readers to see how your site is organized. You can see the site's content hierarchy, and the URLs provide information in search results that help to improve click-through rates.
• Clear call to action (CTA). Each page should have a clear CTA to guide users toward completing an action, improving engagement and conversions.
• Search functionality. A well-functioning internal search tool can help users quickly find content. Be sure to index all relevant pages for search results.

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Dynamic URLs with unnecessary parameters (e.g., domain.com/page?id=12345) are less SEO-friendly than static URLs, so avoid them if you can.

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Let's look at an example of how to structure your URLs. Imagine you're a consulting firm named "Silverstone Strategy Group." You want to add a blog section to your website to capture more foot traffic from search engines. You call that blog section "Insights" and one subsection of the blog is a collection of articles on corporate leadership development. The focus keyword of the latest article is "online seminars and conferences." In that case, a great URL structure would look like this:

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www.silverstonesg.com/insights/leadership-developement/online-seminars-and-conferences

Internal linking

When you have lots of great content that shows off your expertise, you want your readers (and search engines) to know that they don't have to leave your website to find what they're looking for. That's where internal links can help. They can encourage a reader to click into another page. This gives you another chance to show a Call to Action and book them as a customer. Here are some best practices for the use of internal linking.

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• Anchor text. Choose descriptive anchor text that accurately reflects the content on the linked page. Use keywords and page titles as anchor text to make the relevance clear to readers and bots.
• Link distribution. Important pages (e.g., cornerstone content or pillar pages) should have the most internal links pointing to them.
• Contextual linking. Link from one page to another that will shed more light on the subject or provide more context. For example, from this article on UX and SEO through site structure, we can contextual linking to connect readers with an article in this blog about link-building and one on how to design a user experience. The first one adds context for this paragraph and subsection on linking. The second one adds context for this article about improving the UX experience. This form of linking  improves the flow of link equity and content relevance.

Mobile-friendly design

The percentage of web traffic that comes from mobile devices has steadily increased every year since smartphones hit the scene. As a result, Google has consistently prioritized mobile-friendliness and uses mobile-first indexing. It bases indexing and ranking on the mobile version of websites. Here are some tips for being mobile friendly.

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• Responsive design. The site should use responsive design, which enables it to adjusts seamlessly to screens of any size. They load quickly and look good on smartphones, personal computers and everything in between.
• Page speed optimization. Slow-loading pages ruin the user experience. Minimize heavy images, use browser caching, and compress files to improve loading times.
• Server performance. Make sure your hosting provider offers reliable performance with minimal downtime.
• Image optimization. When you reduce file sizes, you can get faster load times and smoother user experiences on mobile devices with varying screen sizes and network speeds.

Clean and crawlable code

What exactly is "crawlability? To put it simply, search engines have bots they send out to look through websites' code and content, then report their findings. They register many different aspects of your site, but if your code isn’t "clean" enough it impedes the bots and your rankings may suffer.  That's why your site's code architecture is crucial. Here are some aspects of coding to keep in mind as you're looking at the more technical aspects of your site's SEO.

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• Well-formatted HTML. Use clean, semantic HTML that is easy for search engine crawlers to read.
• XML sitemap. Create and submit an XML sitemap to help search engines discover and index pages more effectively.
• Robots.txt file. Use the robots.txt file to manage which pages should or shouldn’t be crawled by search engines.
• Canonical tags. Use canonical tags to avoid duplicate content issues. They tell search engines which version of a page is the preferred one.
• Security. Google favors secure websites (HTTPS) over non-secure ones (HTTP). SSL certificates ensure that the website is encrypted and secure for users, which also helps in ranking.
• Alt tags for images. Use descriptive alt attributes for all images to ensure search engines understand their context.
• Structured data (schema markup). Think of structured data like a map key for search engine crawlers. It gives them a shortcut to understanding your content. It also helps rich snippets (star ratings, product info, etc.) to appear in search results, increasing visibility and click-through rates.

404 pages and redirects

Sometimes, website maintenance or migration can cause snags in your user experience and a dip in traffic. Redirects help prevent this.

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• Custom 404 page: Provide a user-friendly custom 404 error page to help users find what they’re looking for if they encounter a broken link. You can even get fun and creative with them.
• 301 redirects: When a page is moved, a permanent 301 redirect should be set up from the old URL to the new URL to pass SEO value and prevent broken links.

Improve your website's returns with Rellify

Rellify can help you streamline your site architecture, making it more intuitive for users while boosting your SEO performance. More critically, Rellify uses AI-powered topic ideation and keyword optimization to help you find exactly what you need to write about in order to be better found on search engines. If you're ready to find out how Rellify can revolutionize the way you do SEO content, talk to one of our experts today.

By Jayne Schultheis — A great content strategy typically isn't going to be your first draft. And if you've ever wondered why your content isn't hitting the mark, you may have some unseen challenges that are preventing the content from hitting your goals. This article dives into the hurdles many face and offers practical solutions. Together, let's look at how to set the stage for content success by catching potential pitfalls before they affect your bottom line.

Understanding Content Strategy Challenges

The best way to prevent setbacks is to anticipate challenges before they arise.

Understanding your audience.

Among the 22% of B2B marketers who said their organization is very or extremely successful, 79% of these top performers most often attribute their success to knowing their audience. But when you think about all the potential people who could potentially be your "audience," it's easy to get overwhelmed. Who are they? What are their shopping habits? Where are they spending their time online? What kind of budget do they have? There are a million questions you could ask, all of which takes some serious market research. From those insights, along with a thorough analysis of existing customers, you should develop a few different buyer personas-- that is, detailed descriptions of your ideal, target customer. When you're trying to find that ideal customer, try using A/B testing to narrow the groups down.

Finding the right marketing channels.

This can be a complex challenge, especially given the diversity of platforms available. With each channel catering to different audience demographics and content types, it can be difficult to determine where to invest time and resources. Marketers must consider factors such as audience preferences, engagement levels, and the nature of their content, all while navigating the ever-evolving landscape of social media, blogs, email, and emerging platforms. Snags in channel selection can lead to ineffective campaigns, wasted budgets, and missed opportunities for engagement.

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To choose the right content marketing channels, marketers should start by clearly defining their target audience and understanding where that audience spends their time. Conducting audience research through surveys, social media analytics, and competitor analysis can provide valuable insights into preferred platforms and content consumption habits. You can also test different channels through pilot campaigns to help identify which ones yield the best results.

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It’s also beneficial to consider the type of content being created. Visual content may perform better on platforms like Instagram or TikTok, while long-form articles might be more suitable for a company blog or LinkedIn.

Lack of clear goals.

When surveyed, that same 22% of B2B marketers who said their organization is very or extremely successful, 68% of them attributed their success to content that aligns with the organization’s objectives. You might be confused, thinking, "Isn't my goal just to get people to to buy my product or services?" Well, ultimately, yes. That's your over-arching goal. But there are lots of different smaller goals that content can achieve, including, but not limited to:

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• Brand awareness
• Lead generation, conversions, or customer retention
• Customer engagement or education
• Increase website traffic
• Improve SEO rankings
• Establish thought leadership

Inconsistent brand voice or tone.

An inconsistent brand voice or tone can significantly undermine a content marketing strategy, creating confusion and diluting brand identity. When different pieces of content convey varying tones—whether overly formal, casual, humorous, or serious—it can lead to mixed messages that frustrate audiences. This inconsistency can make it difficult for customers to understand what the brand stands for, weakening their trust and emotional connection. Over time, this can result in diminished brand loyalty as consumers may struggle to recognize the brand amidst a sea of competing voices.

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Moreover, an inconsistent brand voice can hinder the effectiveness of marketing campaigns. Content that lacks a cohesive tone may fail to resonate with the target audience, resulting in lower engagement rates and missed opportunities for conversion. If a brand’s communication shifts erratically across different channels or campaigns, it may also create a fragmented customer experience, where individuals feel disconnected from the brand's values and messaging. Maintaining a consistent voice and tone is crucial for reinforcing brand identity, ensuring clarity, and fostering deeper relationships with audiences.

AI.

We'd be remiss if we didn't address the elephant in the room: artificial intelligence. One of the biggest content marketing challenges facing companies presently is how to effectively incorporate artificial intelligence into their processes. Nearly half of content marketers use AI to brainstorm new topics, and 46% use it to research headlines and keywords. More than one-third (36%) use AI tools for writing, though many feel conflicted about the idea. There's still quite a bit of gray area as companies and consumers alike grapple with the ethics and practicality of AI in marketing.

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But there's a lot more to AI than just hitting a button and generating text. AI can be used in countless ways throughout your processes, even in analytics. At Rellify, we've harnessed the power of AI to make topic and keyword research exponentially more effective. With a Relliverse™, customized for your brand, you can easily discover topics and keywords that are already doing well within your industry niche. Then, you can create content that's poised to climb the SERP rankings and be better found by your target audience.

Competitors.

The digital landscape is saturated with content vying for audience attention. With countless brands producing similar types of content, standing out becomes increasingly difficult. This saturation not only makes it challenging to capture potential customers' interest but also raises the stakes for quality and originality. Content marketers must consistently innovate and find unique angles to differentiate their messages, which requires a deep understanding of both their audience and their competitors’ strategies.

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Additionally, competitors often engage in aggressive SEO tactics, making it harder for new or smaller brands to rank highly on search engines. They may also leverage social media and paid advertising more effectively, drawing attention away from other content. This means that content marketers must not only focus on creating high-quality content but also continuously monitor competitors’ activities, adapt to shifting trends, and invest in strategic promotion to maintain visibility in a crowded market.

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A thorough competitor keyword analysis can also be a helpful strategy. This is the a process of examining the keywords that your competitors are targeting in their online content and SEO strategies. This helps you identify opportunities and threats in your own SEO strategy. A competitor keyword analysis can lead to a boost in your SEO when you successfully identify high-value keywords that your competitors are ranking for, then target similar terms with your own optimized content.

Tight Budgets.

Demand for high-quality content is high, but budgets are tight. Only 45% expect their content spend to ‌increase this year—a 13% drop from the 2023 survey. It's no secret that lots of companies are increasingly cutting down their teams to skeleton crews and looking ways to cut corners in any way they can. But when it comes to content marketing, you have to be careful where you cut corners. A colleague of mine recently started a small business, and when asked how they intended to fill out their website with content, they said they asked ChatGPT for a list of topics and had it write the articles, too. This is an example of how you should not cut corners. Not only does a tool like GPT lack the insights regarding SEO topics and keywords, it also generates its content based on pre-set algorithms and formulas. Absolutely no one will be finding that website through search engines, or any other avenues, unless they have the specific URL.

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If you find yourself struggling with budget constraints, marketers can adopt several strategies. First, they can prioritize content that offers the highest ROI, like evergreen pieces that remain relevant over time or user-generated content that leverages customer contributions. Repurposing existing content into different formats—like turning a blog post into an infographic or cross-promoting across platforms—can also maximize the value of prior investments. Additionally, utilizing cost-effective tools and platforms for content creation and distribution, as well as leveraging organic social media reach, can help stretch a limited budget further. Remember, the amount of time and effort you put into making content will be reflected in your returns.

Understanding and managing analytics.

Analytics are a huge part of a healthy content strategy, as they can help you hone in on what's working, what isn't working, and how to modify your strategy to improve your ROI. While eight in 10 content marketers use content analytics to decide what to create, yet three in four aren’t entirely clear how that content performs. Interpreting vast amounts of data and translating insights into actionable strategies is a huge task, especially for those who have tight content budgets. Without a solid grasp of data interpretation, marketers risk making decisions based on incomplete or misleading information, which can lead to ineffective campaigns and wasted resources.  

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To tackle these challenges, marketers can leverage a variety of user-friendly analytics tools that simplify data analysis and visualization. Google Analytics is a powerful option for tracking website performance, providing insights into visitor behavior, traffic sources, and conversion rates. For social media analytics, platforms like Hootsuite or Buffer offer comprehensive dashboards that allow marketers to monitor engagement metrics and audience demographics across multiple channels.

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Additionally, tools like HubSpot and SEMrush provide integrated solutions for content performance tracking and SEO analytics. Rellify even can pull analytic insights on content performance directly into the platform after publishing so you can plan, write, monitor all in one place. By utilizing these tools and prioritizing ongoing education in data analysis, marketers can develop a more nuanced understanding of their performance metrics and make informed decisions.

Difficulty keeping up with changes in the market.

The ever-changing content marketing landscape presents a huge challenge for marketers striving to stay relevant and effective. Rapid shifts in consumer behavior, technology, and search engine algorithms require constant adaptation and agility. What worked yesterday in terms of content formats or distribution channels may quickly become outdated as new trends emerge or audience preferences evolve. Anyone who's keeping up with the recent innovations in AI can tell you that. Marketers must continuously monitor these changes and be willing to pivot strategies, which can strain resources and complicate planning.

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Additionally, the proliferation of new platforms and tools can create a sense of overwhelm, making it difficult for marketers to determine where to focus their efforts. Marketers face the challenge of not only mastering various formats but also integrating them into a cohesive strategy. This constant need for education, experimentation, and optimization can lead to burnout and frustration, especially for smaller teams or organizations with limited resources. Ultimately, success in this dynamic environment hinges on the ability to embrace change and leverage insights effectively while maintaining a clear vision and consistent brand messaging.

Ineffective content planning.

Ineffective content planning can severely hinder a content marketer's ability to execute successful campaigns. Without a clear strategy, marketers may produce content that lacks focus, fails to address audience needs, or misses key deadlines. This disorganization can lead to inconsistent messaging, wasted resources, and missed opportunities for engagement, ultimately diminishing the overall impact of the content. When content is created on an ad-hoc basis, it often lacks cohesion, which can confuse audiences and weaken brand identity.

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To overcome these challenges, marketers should implement a structured content planning process that includes:

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• setting clear objectives and KPIs
• identifying target audiences
• developing a content calendar
• setting editorial guidelines
• establishing a workflow for the content lifecycle
• potential for scalability

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This roadmap not only helps ensure that all content aligns with the brand’s goals but also allows for strategic scheduling that maximizes reach and engagement. Regularly reviewing and adjusting the content plan based on performance metrics can also help marketers stay agile and responsive to changing audience preferences.

Preventing and Overcoming Content Strategy Challenges with the Experts at Rellify

Rellify has helped many companies with their content marketing efforts and assisted them in setting and achieving their specific goals. With an interactive content calendar for planning, expert topic and keyword research, and analytics pulled directly into the platform, you can seamlessly prevent and overcome any content challenges you might face. And with a Relliverse™, you can harness the power of customized AI and deep machine learning to find topics and keywords that will naturally position your content higher in SERP rankings and resonate with your target audience. Ready to find out more? Contact a Rellify expert today for a brief demo and learn exactly how Rellify can transform your content strategy, processes, and returns.

By Jayne Schultheis — Imagine walking into a brand new store in your area and finding exactly what you need without asking an employee for help or looking for signs.

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That's the kind of magic that effective local SEO can provide — guiding local customers straight to your business's virtual doorstep. In today's digital landscape, understanding and harnessing the power of local SEO is crucial for any business aiming to capture the attention of nearby customers.

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This article will delve into the key elements of local SEO, from optimizing your Google Business Profile to leveraging local link-building strategies. Let's dive in!

Understanding local SEO

Local SEO is a pivotal strategy for businesses aiming to boost their visibility in local search results. By optimizing for local rankings, businesses can attract more nearby customers who are searching for their products or services. Consumers increasingly rely on search engines to find local businesses that meet their needs, especially when it comes to restaurants, entertainment, and in-person services. Local SEO not only helps improve search visibility but also enhances your overall digital presence, making it easier for potential customers to find and engage with your business.

Key elements of local SEO

Local SEO hinges on several crucial elements that combine to establish your local credibility with search engines.

NAP consistency in local SEO

NAP is short for Name, Address, and Phone number, and NAP consistency is a vital aspect of local SEO success. Accurate and consistent business listings on Google and other search engines, as well as local business directories, builds credibility with search engines. This consistency helps potential customers easily find and contact your business, and shows Google that you're a reliably consistent establishment.

Optimize your Google Business Profile for better visibility

To enhance local SEO, a well-optimized Google Business Profile, formerly called Google My Business, is crucial. This is the sidebar that pops up on Google when you type in the name of a specific business or restaurant. It can show photos, customer reviews, hours, website, phone number, and other helpful information. It’s a form of digital storefront. When the profile is accurate and complete, your visibility is boosted in local search queries, attracting more local customers.

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One of the most important SERP features for local businesses is the Local Pack, the map and listing of local businesses in an area that appear when someone does a search like "find the nearest X to me." If you haven't thoroughly filled out a Google Business Profile, you won't appear on that Local Pack, but your competitors might.

Geo-targeting

Geo-targeting goes hand in hand with local SEO. Make sure your website is set up to determine a user's location and have content ready that is based on their location. For example, if you have multiple locations, have a separate landing page for each one with specific "Contact Us" information for each branch.

Conduct keyword research for local SEO

To effectively target local audiences, businesses must focus on identifying relevant local keywords. Start by analyzing what potential customers in your area are searching for, using tools like Google Keyword Planner or Moz’s Keyword Explorer.

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It’s essential to include location-specific terms and phrases that reflect the local culture and community. This will help you align your content with local search queries, enhancing visibility and driving more local traffic to your business.

How to do effective local keyword research

Let's assume that you're opening a vegan bakery in Denver, Colorado. These are the steps you should take when you're ready to build engaging content that will boost your local SEO.

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Understand your audience. Identify your target demographic and their needs. In this case, you'd be looking to target vegans with a sweet tooth. Consider their location, interests, and search behaviors. Are there places in Denver where you'd be more likely to find these people? What other types of products and services would they be searching for?

Brainstorm seed keywords. Start with broad keywords related to your business. For example, if you own a bakery, your seed keywords might include “bakery,” “cake,” "vegan," and “pastries.”

Assess the competition. Look at local competitors’ websites and their keyword strategies. What keywords do they rank for and what gaps can you exploit?

Use keyword research tools. Use Rellify, Google Keyword Planner, Semrush, or similar services to find keyword ideas and search volumes. Look for local-specific keywords by including your city or region. Focus on long-tail keywords that may have lower search volumes but are more specific and often lead to higher conversion rates (e.g., “gluten-free birthday cake in [Denver]”).

Understand the user intent behind the keywords, too. Are users looking to make a purchase, find information, or compare options? This will help you create content that meets their needs.

In our example, users could be looking to buy a snack. But they might also be compiling a list of vegan restaurant options in the area or comparing vegan catering options for a wedding. Rellify is unique in its ability to use deep machine learning and AI to understand your niche market and search intent, suggesting keywords that are already doing well in your sector and local area.

Incorporate local modifiers. Add geographic terms to your seed keywords. For example, “best vegan bakery in [Denver]” or “vegan cupcakes near me.”

Monitor and adjust. Regularly check the performance of your chosen keywords using analytics tools. Tools like Moz Local, BrightLocal, and Google Analytics can offer insights into local search performance, helping you refine your SEO strategies. Adjust your strategy based on what’s working for the search engine algorithms.

Craft geo-specific content for local audiences: Community engagement

To truly resonate with a local audience, create geo-targeting content that speaks directly to the community's unique characteristics and needs. This involves incorporating location-specific details and cultural nuances into your content to make it more relatable and engaging.

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Mentioning specific landmarks or local events to establish a connection with your audience. In our above example, we might include a blog post on the "Denver Union Station Farmers Market." This summer event features local produce and vegan vendors, and would likely be an interesting event for vegans searching for local places to grab food (like your bakery).

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It's not just what you know about the local area, but who you know. Content marketing with blog posts can be one of your most effective local SEO tools. However, if you can diversify your efforts and make real-world tie-ins within your content, search engines are much more likely to rank you as the best answer to what the locals are looking for.

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You could use social media to reach out to travel bloggers or local influencers who make specific content like "best places to grab breakfast in Denver" or "vegan-friendly restaurants in Denver." You could reach out to local news channels and let them know about your grand (or soft) opening, and share the video content on social media. The more you can pair local SEO content and efforts with real-world community engagement, the more familiarity and trust you'll build with both search engines and potential customers who use them.

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Local reviews and customer feedback also play a pivotal role in enhancing your local SEO. Positive reviews boost your credibility while improving your visibility in search results. Engaging with feedback, whether positive or negative, demonstrates responsiveness and builds trust, encouraging more local customers to choose your business. Reviews are important for online directories and listings. It's a good policy to encourage customers to post reviews. Then, take the time to respond to comments on your blog content, social media posts, and review sites.

Leverage local link-building strategies

Another way to bolster your SEO is by building local partnerships in the digital realm. By collaborating with nearby businesses and organizations, you can create valuable link-building opportunities that boost your website's authority and search engine rankings. Local link building not only improves your visibility in search results, but also enhance your position as a trusted and integral part of the local community.

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In our Colorado vegan bakery example, consider your target audience. At the risk of making generalizations, they might also be interested in small, local groceries, clothing exchanges, and eco-friendly and sustainable brands. As you write content about "the health benefits of going vegan," you could link to a local integrative medicine clinic that focuses on holistic health. In your article on "the power of non-processed foods," you could link to a local no-packaging co-op that sells food and toiletries in bulk. No matter what kind of connections you make, be sure that they're willing to link back to your website so you can mutually benefit from local link-building.

On-page SEO techniques for local search optimization

To effectively enhance local search optimization, it’s important to use robust on-page SEO techniques. We’ve touched on the importance of integrating local keywords naturally within your content. It also pays to use them in titles, headings, alt tags, and meta descriptions to align with local search queries. Implementing schema markup can help boost local SEO by giving search engine crawlers detailed information about your business.

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Is your website mobile-friendly? Many users conduct local searches on their smartphones. According to research from Exploding Topics, in 2024, over 60% of website traffic comes from mobile devices. When you consider that someone who's looking for a local spot is potentially roaming around your city, smartphone in hand, it becomes evident how mobile optimization is crucial for any business hoping to get local traffic.

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Voice search is another crucial consideration when you're working on local optimization. According to Synup, more than 58% of smart device users use voice search to find local businesses. What's more, businesses with complete Google Business Profiles are 70% more likely to attract location-based inquiries via voice search. The better you optimize for local SEO, the more likely you'll be drawing in traffic from [Denver] users who use voice search to find " [vegan bakeries] near me."

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Page speed is another crucial part of the user experience. Can you imagine being hangry at 10 a.m. on a Saturday in Denver and the website that promises a hot, melt-in-your-mouth vegan cinnamon bun takes 45 seconds to load? A seamless and intuitive website layout keeps visitors engaged, reduces bounce rates, and makes you a more trustworthy resource for your target audience. A streamlined website can help you achieve higher traffic, click-through rates, and sales.

Let Rellify help you optimize content for local SEO

Content optimization for local SEO takes quite a bit of research, effort, and know-how. Fortunately, Rellify has built a simple, intuitive content intelligence platform that puts AI-powered deep machine learning at your fingertips. Rellify's SEO tools can optimize every aspect of your content creation with a fraction of the time and effort it would take on other platforms.

With a custom Relliverse™ you can conduct keyword research within your specific niche and quickly build out a content plan that will guarantee results. Ready to get started? Contact one of our experts for a brief demo to find out exactly how Rellify can transform the way you do content and maximize your returns.

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By Jayne Schultheis — Keyword research is a fundamental part of search engine optimization, but there's a crucial piece of the process that's often overlooked: user intent. In this article, we'll look at how keyword research and consideration of user intent can intersect to help you build the perfect content strategy. Let's dive in!

What is keyword research?

If you've spent any time writing SEO-optimized blogs, you've probably done some keyword research. Keyword research is the process of identifying and analyzing the terms and phrases that users enter into search engines when they are looking for information, products, or services. The goal is to understand what keywords are most relevant to your audience and to optimize your content so that it ranks higher in search engine results pages (SERPs) for those keywords and gets more organic traffic.

Tools for keyword research

Fortunately, it's not too difficult to find keywords — lots of tools are built specifically to help content marketers find words and phrases that boost your chances of ranking on SERPs for certain topics, including:

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• Google Keyword Planner
• Semrush
• Ahrefs
• Moz Keyword Explorer
• Rellify

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But Rellify isn't your run-of-the-mill keyword research tool. Our magic starts with content strategy itself. With a Relliverse™, a custom-AI subject-matter expert trained on your relevant focus topics, you can make data-driven strategic decisions about which topics and keywords are exactly right for your brand's content. Then, after writing and publishing, you can have Google Analytics and insights pulled directly into the platform, where you watch your optimized content climb the search engine rankings.

What is user intent?

In the context of SEO, "user intent" refers to the underlying purpose or motivation behind a user's search query. Understanding user intent helps in creating content and optimizing websites in a way that aligns with what users are actually looking for when they perform a search.

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There are a few different user search intent categories:

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• Informational intent. The user is looking for information or answers to a question. This can include how-to guides, definitions, or explanations. For example, a search query like “how to bake a pie” indicates the user is seeking a recipe or baking instructions.
• Navigational intent. The user intends to find a specific website or web page. For example, “Instagram login” suggests the user wants to navigate directly to Instagram’s login page. Why didn't they just type it into the URL? We don't know, that's none of our business.
• Transactional intent. The user is ready to make a purchase or complete a transaction. This could be indicated by queries like “where to buy the newest iphone.”
• Commercial investigation. The user is in the research phase before making a purchase decision. Queries like “best keyboards for gaming” or “top-rated Korean skincare products” show that the user is comparing options and seeking reviews or comparisons.

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Categorizing query type is easy enough, but understanding and mastering the match between your keywords and user intent can be more challenging. You're competing with other high-quality content that also aligns with the same (or at least, similar) user intent, and uses the same keywords. Differentiating your own content with long-tail keywords, unique insights, added value can be a tough, but necessary task.

How should keyword research and user intent work together?

Keyword research and user intent are interrelated components of an effective SEO strategy. When combined thoughtfully, they help your content rank well in search engine results while also meeting the needs of your audience. They work together to create a fuller, clearer picture of the different "buyer personas" you should be targeting with your content.

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Here’s how keyword research and user intent should work together to optimize your SEO efforts:

Use keyword tools to analyze the data

Use keyword research tools to gather data on keyword difficulty, search volume, competition, and variations. This type of SERP analysis helps you understand the types of queries users are entering and what information or actions they are seeking.

Categorize keywords by intent, then create content accordingly

Group keywords based on their user intent — informational, navigational, transactional, or commercial investigation. This helps you target content more effectively. For example:

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• Informational keywords might include “how to clean a white sneakers.”
• Transactional keywords might include “buy shoe cleaner.”

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Develop content that directly addresses the intent behind the keywords. For example, informational queries lend themselves to detailed guides, how-to articles, and tutorials. Transactional queries are a better fit for product pages, reviews, or buying guides that facilitate purchase decisions.

Optimize the content

Pay attention to keyword placement throughout your optimization process. Make sure that the content structure — headings, subheadings, and formatting — aligns with the intent behind the keywords, too. Use clear, concise headings for informational content and persuasive language for transactional content. You can even use specific questions that users are typing into search engines as headers.

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The keywords that are most relevant to the user intent should also be incorporated in title tags and meta descriptions. For example:

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• An informational title could be “How to Clean White Sneakers: A Step-by-Step Guide.”
• A transactional title might be “Top 10 Sneaker Cleaners for 2024: Reviews and Buying Guide.”

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Backlinking and internal linking are also factors that signal to search engines you understand the user intent behind the queries you're hoping to rank for. When you're linking, whether externally or internally, choose to link with anchor text that reflects that intent.

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Let's use our "sneaker" example from above, assuming we are a luxury shoe company. If we wrote the article, "Top 10 Sneaker Cleaners for 2024: Reviews and Buying Guide," then we would select the keyword phrase "sneaker care" to anchor a link to our other blog article about how to correctly care for shoes.

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Assuming that your target audience is stylish, image-conscious, young professionals who take a lot of pride in their appearance, this would be a way to signal to search engines that you're in-step with your buyer persona and user intent, a true expert in the industry who deserves the subsequent domain authority status.

Adapt to trends and changes

Search trends and user behavior can change over time, in addition to ranking factors and algorithms set by search engines. Keep an eye on your click-through rate and bounce rate. Regularly update your keyword research and content strategy to stay aligned with what's current. With the continued advancements in voice search and AI, how users express intent and search for information is ever-changing, too. Adjust your content optimization strategy to accommodate these changes. It can seem tedious, but it's the only way to make sure you can stay on top of your audience's shifting semantic searches and google algorithm updates.

Address multi-intent queries

For queries with multiple intents, develop content that addresses different aspects of the user’s needs. For example, a query like “best budget smartphones” could be addressed with a guide that includes buying tips, product reviews, and comparisons.

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You can also address this issue by guiding users to relevant content within your site that meets different aspects of their intent, like the "shoe cleaner" example we mentioned above. This helps provide a more complete answer to their queries and improving overall user experience.

Rellify: Search engine optimization experts

Rellify doesn't just guess about user intent — our state-of-the-art Relliverse™ is customized content intelligence — AI that deeply analysis and understands your company, topics, and keywords. With our competitive analysis, we provide insights beyond your typical keyword research tools. Our platform can guide your content creation every step of the way with SEO tips and suggestions. Ready to maximize your conversion rates with top-notch content? Hop on a call with one of our experts to find out exactly how Rellify can super-charge your content marketing returns with just a fraction of the effort.

Do you remember when you could ask a cartoon butler named "Jeeves" a question and he would search the internet for your answer?

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How times have changed. RIP, Jeeves. Tell "Clippy" we say hello.

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The evolution of search engines has been revolutionary, constantly changing the way we research, do business, and function in the digital world. In this article, we'll take you through the timeline of how search engines have changed over the years, and take a look at how you can best implement search engine optimization (SEO).

The internet without search: A new frontier

Before the advent of search engines, the World Wide Web (hence the "www") was a more fragmented and less navigable space — a "Wild West Web," so to speak.

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In the early 1990s, users primarily accessed content through static web pages sometimes reached through hyperlinks. The web was essentially a collection of individual sites, organized by directories like Yahoo!, which required manual categorization and browsing. Finding specific information often meant knowing the exact URL or relying on word of mouth to discover new sites.

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Without search engines, users had a lot more trouble locating the information they needed. Resources were often scattered across various platforms, and the lack of centralized indexing made it tedious to navigate. Many people relied on bookmarking favorite sites or engaging in discussions on forums to share and find useful links.  

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The emergence of search engines fundamentally transformed this landscape, allowing efficient information retrieval and significantly improving the web’s usability.

The evolution of search engines: A timeline

Search engines didn't have one particular "inventor," they evolved through contributions from various individuals and teams. The first search engine, Archie, was developed in 1990 to index File Transfer Protocol (FTP) sites, allowing users to search for and locate downloadable files across the internet.

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The name "Archie" is a play on the word "archive," reflecting its primary function of indexing and retrieving files. Unlike modern search engines that index web pages, Archie focused on file names and directory structures, generating a list of available files that users could browse. Users could query the Archie database using simple search terms, making it easier to discover resources that would otherwise require knowing specific URLs. This innovation laid the groundwork for the development of more advanced search technologies.

1. Early beginnings (1990s)

• Basic indexing. The first search engines were developed. These included tools like Archie, which indexed FTP sites, and Veronica, which searched Gopher servers.
• Web crawlers. In 1994, WebCrawler became the first search engine to index entire pages, allowing users to search for any word on a page, not just titles or URLs.
• Directory-based search. Yahoo! started as a directory of websites, where human editors categorized links. This model was popular until the volume of web content exploded.

2. The rise of algorithmic search (Late 1990s)

Search engines became increasingly complex, employing algorithms to improve the relevance and speed of search results.

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• AltaVista and Ask Jeeves. AltaVista (1995) introduced more advanced search capabilities, including natural language queries. Ask Jeeves (1996) focused on user questions, attempting to provide direct answers.  
• PageRank. In 1996, Larry Page and Sergey Brin developed PageRank as part of their PhD project, which later became the foundation for Google. It evaluated web pages based on their link structure, promoting high-quality, relevant pages.
• Launch of Google. In 1998, Google was officially launched, quickly becoming the preferred search engine due to its clean interface and superior search results driven by PageRank.

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By the end of the 1990s, search engines had transformed from rudimentary tools into essential components of the internet, facilitating easier access to information and significantly shaping online behavior.

3. Google’s dominance (2000s)

After the world survived Y2K and kept spinning on Jan. 1, 2000, search engines underwent significant transformations driven by technological advancements and evolving user needs. The evolution of search engines was, for the most part, represented by the evolution of Google.

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• Personalization and localization. Google introduced features like personalized search results and localized content, leading to a better user experience based on individual preferences and geographical location. Local SEO became a helpful new tool for marketers who wanted local shoppers to find and patronize their businesses.
• AdWords. In 2000, Google launched AdWords, revolutionizing how businesses could advertise online through pay-per-click (PPC) advertising, which contributed significantly to Google’s revenue.
• Real-time search. In 2009, Google began incorporating content from social media and news sites into search results.

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One of the most notable developments was the refinement of algorithms to improve search result relevance and page rankings on SERPs. Google's PageRank algorithm, which assessed the importance of web pages based on backlinks, became a benchmark for search quality. This era also saw the introduction of personalized search results, which tailored the user experience based on individual preferences and behavior.

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The rise of social media and user-generated content further influenced search engine functionality. Search engines began to integrate social signals and real-time data, leading to features like news search and video search capabilities. Mobile search also emerged as a critical focus, prompting engines to optimize for mobile-friendly sites.

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Overall, the 2000s marked a shift towards more sophisticated, user-centric search technologies that not only provided better results but also adapted to the changing dynamics of online information consumption.

4. Semantic search and user intent (2010s)

This is when things really start to pick up! Overall, the 2010s marked a move toward more intuitive, personalized, and multimedia-rich search experiences, fundamentally transforming how users interacted with search engines.

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• Caffeine. In 2010, Google introduced a new infrastructure for faster indexing and more frequent updates, including Google+, which placed a stronger emphasis on social signals in search results.
• Knowledge graph. Launched in 2012, this feature presented information in a structured format, giving users direct answers without clicking through to other websites.
• Hummingbird algorithm. In 2013, Google introduced Hummingbird, which focused on understanding the context and intent behind qu. eries, improving its ability to provide relevant results.
• Featured snippets. Introduced by Google in 2014, this feature aimed to provide users with quick answers to their queries directly at the top of the search results page, highlighting concise information from relevant web pages.
• Mobile search. Google adapted to mobile search by emphasizing mobile-friendly websites in 2015 with an algorithm update known as "Mobilegeddon." A voice search feature followed in 2016 when users could speak directly into their phones and ask search engines questions.
• RankBrain. In 2015, Google incorporated RankBrain, a machine learning component that helps process search queries and improve results based on user interactions.

5. AI and machine learning (Late 2010s to present)

Search engines became so integrated into our everyday lives, it's hard now to even imagine a world without them. During this time, it because commonplace to hear people say things like: "Hey, Google! Find me a local Italian restaurant with outdoor seating!"

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• BERT. Launched in 2019, BERT (Bidirectional Encoder Representations from Transformers) significantly advanced the understanding of natural language, allowing Google to better grasp the nuances of user queries.
• Mobile-first indexing. Google further advanced its mobile search capabilities with the introduction of mobile-first indexing in 2019. This meant that the mobile version of a site would be considered the primary version for ranking purposes. This shift underscored the importance of mobile optimization search as a central focus for search engines and web developers alike.
• Voice search. Though voice search already existed, the proliferation of voice-activated devices (like Google Assistant and Amazon Alexa) led to increased emphasis on optimizing search for conversational queries.

6. Current trends and future directions (2020s)

Artificial intelligence and natural language processing have launched search engines into a new trajectory, and content marketing experts have their jobs cut out for them as they adapt and modify their approaches SEO.

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• AI and chatbots. AI continues to evolve, with search engines integrating conversational AI to enhance user interaction and provide instant answers. Machine learning is playing a crucial role in transforming the search engine landscape, as this for of AI can self-train and adapt when it's presented with new information.
• Visual search. Platforms like Google Lens allow users to search using images, making search more intuitive and practical.
• Privacy concerns. As awareness of data privacy grows, search engines are adapting by offering more transparent data usage policies and options for users to control their data.
• Sustainability. There's a growing focus on the environmental impact of digital services, prompting search engines to consider eco-friendly practices in data centers and operations.

How to use search engines for content marketing.

Since AI integration and summarization has become such a prominent feature in how users engage with search engines, you might be wondering how it will affect your content marketing strategy. How will AI integration impact SEO if you rely on content to draw in organic traffic from search engines?

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The short answer is: You have to create better content.

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You don't just need to add more keywords, but better keywords. Your content should reflect the search intent of your target audience, meaning that it directly answers their specific questions or provides niche information that they're seeking. Are they looking for a specific product? Do they need detailed background information about a certain subject? What stage of the customer journey are they in and how do you craft your content to meet them there?

Search engine optimization has always been at the core of long-form content marketing, at least as long as search engines algorithms have crawling been around. We'll look at some of the core aspects of this process, so you can make sure you're staying on top of SERPs.

Search engine optimization in the age of AI

Think "E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness)." Google's algorithm places a lot of weight on these as it ranks your content on its pages. Here are some other ways you can boost your domain authority and stay on top of algorithm updates:

Choose your topics and keywords wisely

Research relevant topics. Tools like Google Trends, Semrush, or Ahrefs can help you identify trending topics in your niche that resonate with your audience and align with their search intent. But if you need an expert tool that seamlessly integrates AI, Rellify is your solution. With a custom Relliverse™, you can use machine learning to provide detailed insights into what topics and keywords are going to resonate best with your target audience.

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Long-tail keywords. When you're doing keyword research, target long-tail keywords that reflect specific queries. These tend to have lower competition and higher conversion rates, allowing you to capture a more defined audience. For example, an article with the focus key phrase, "ladders" would be much harder to rank for than "retractable steel ladders"

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Content relevance. Make sure your content is comprehensive and directly answers user questions. This not only boosts your relevance in search results but also helps boost user satisfaction.

Develop a fool-proof linking strategy

Quality backlinks. Focus on acquiring backlinks from reputable and authoritative websites in your niche. High-quality inbound links signal to search engines that your content is valuable.

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Internal linking. Create a strong internal linking structure to guide users through your content and help search engines understand the relationships between different pages on your site. Choose anchor text that reflects the topics and keywords of your other valuable content.

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Outreach and collaboration. Engage in outreach efforts to connect with other creators and websites. Guest blogging, partnerships, and collaborations can help you earn valuable backlinks and increase your site's visibility.

Mind your technical SEO

Technical SEO is just as important as the topics and keywords, just a bit more tedious.

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Site speed optimization. Make sure your website loads quickly on both desktop and mobile devices. Use tools like Google PageSpeed Insights to identify and address issues that may slow down your site.

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Mobile-friendliness. Implement responsive design to make your website accessible and functional on all devices. Google prioritizes mobile-friendly sites.

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Schema markup. Use structured data (schema markup) to help crawlers navigate your site and search engines better understand your content.

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Secure your site. Implement HTTPS to secure your site. It adds a layer of security to the data exchanged between a user's browser and a web server. Google considers security a ranking factor and it helps build trust with your users.

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Monitoring. Most importantly, you should regularly monitor your core web vitals and organic site traffic. Look at click-through rates and bounce rates. Note how you need to adjust to your content as you evaluate what is and isn't working. Rellify pulls in this kind of information directly into the platform, so you can keep all your relevant content data all in one place.

Rellify can help your audience find your content

Rellify embraces search engine innovations and works to make content creation an increasingly effective and efficient marketing tool for clients. With a custom Relliverse™, you can leverage AI tailored to your niche to find the right topics, use the right keywords, and answer the right questions. That way, you're set to start climbing the search engine rankings. Ready to get started? Contact a Rellify expert today.