Category: Artificial Intelligence (AI)

  • How AI Overview Is Changing Manufacturing Content Marketing and SEO—And What You Can Do About It

    How AI Overview Is Changing Manufacturing Content Marketing and SEO—And What You Can Do About It

    The rise of AI Overview in search results is transforming how manufacturers approach online marketing. Google’s AI-generated summaries are changing the way content is discovered, impacting both manufacturing content marketing and SEO strategies.

    While these AI-driven search experiences aim to provide quick, authoritative answers to users, they also present significant challenges for manufacturers looking to build brand visibility and attract high-quality leads.

    As AI Overview in search results continues to evolve, manufacturers must rethink their digital marketing strategies to stay ahead. The question is: How can industrial marketers adapt to ensure their content remains visible and effective in an AI-dominated search landscape?

    What is AI Overview in Search Results?

    Google’s AI Overview or Bing’s Copilot Answer is a generative search feature designed to provide users with an AI Overview at the top of search results. Instead of displaying a list of traditional blue links, Google’s AI extracts and summarizes information from multiple sources to generate a concise, authoritative response directly within the search page.

    For manufacturers, this means:

    • Users may get answers without clicking through to the original content source.
    • AI-generated summaries pull from various websites, making it harder for any single manufacturer to stand out.
    • The emphasis shifts from rankings and organic traffic to brand authority and structured content visibility.

    While AI Overview enhances the user experience by delivering quick insights, it also reshapes how manufacturers must approach digital marketing to maintain control over their brand’s online presence.

    The Impact of AI on Industrial Marketing: Key Challenges and Risks

    As AI-generated search results become more prevalent, manufacturers must deal with the implications of this shift. Here are some of the biggest challenges industrial marketers face:

    1. Declining Organic Traffic and Click-Through Rates

    Manufacturers that rely on search engines for lead generation may see a decline in organic traffic. Since AI Overviews summarize information on the search results page, users often find what they need without visiting the original source. This creates a zero-click search environment, making it harder for industrial marketers to capture potential leads through traditional SEO strategies.

    Recent research highlights this shift:

    • Semrush: The State of Search 2024 found that 57% of Google searches now result in zero clicks, meaning users find their answers directly on the search page.
    • A study from Backlinko showed that click-through rates (CTR) have dropped for both top-ranking and mid-ranking search results, signaling a fundamental change in search behavior.

    For manufacturing marketers, this means fewer organic visitors, lower engagement from search traffic, and a growing reliance on alternative visibility strategies beyond traditional SEO.

    2. Loss of Brand Visibility and Thought Leadership

    AI Overview pulls insights from multiple sources, often without giving prominent credit to individual brands. This means that even if your company provides unique industry expertise, your insights could be blended with competitor content, diluting your brand’s authority.

    Even major brands are feeling the impact of these AI-driven search changes. HubSpot, a leader in digital marketing content, recently reported a loss of nearly 50% of its organic traffic due to Google’s evolving search algorithms.

    According to an analysis by Search Engine Land, HubSpot’s traffic plummeted from 36 million to 18 million monthly visitors in just six months. Their case highlights a major shift: even companies with high-authority content are losing visibility as AI-driven search features prioritize summaries over original content.

    Impact of AI on Industrial Marketing

    I understand—as a manufacturer, you couldn’t care less about what happened to HubSpot. However, it underlines the challenges of AI Overviews and their impact on traditional SEO, making it clear that no brand is immune to these changes.

    3. Shifting SEO Priorities for Manufacturing Content Marketing

    Traditional SEO strategies focusing solely on keyword rankings are becoming less effective. Google’s AI prefers:

    • Structured data and well-organized content that is easy to extract and summarize.
    • Conversational and long-form queries that align with AI-driven search behavior.
    • Authoritative, data-backed insights over generic content.

    For manufacturing marketers, this means rethinking keyword strategies, content structure, and website optimization to maintain visibility in AI-driven search results.

    Manufacturing Content Marketing and SEO in the Age of AI Overview

    To stay ahead, industrial and manufacturing marketers must adapt their content marketing and SEO strategies to align with AI-driven search behavior. While the shift presents challenges, it also creates opportunities for manufacturers willing to rethink their approach.

    1. Strengthening Brand Authority Beyond Google

    With AI Overview pulling content from multiple sources, relying solely on Google for visibility is no longer enough. Manufacturers must build multi-channel content strategies that establish authority across LinkedIn, YouTube, industry directories, and direct customer engagement channels.

    2. Prioritizing Proprietary and Expert-Driven Content

    AI Overviews aggregate existing online content but cannot generate unique, proprietary insights. Manufacturing companies that publish original research, technical whitepapers, and SME-authored content will have a competitive edge.

    However, even if your company produces high-quality, thought leadership content, it may still struggle to gain visibility in search results. AI-driven search algorithms prioritize widely referenced sources and high-authority domains, meaning smaller manufacturers or niche industry experts may be overlooked. This makes it even more critical to develop a strategic content distribution plan beyond relying solely on Google rankings.

    This is where industrial brands can differentiate themselves from AI-generated summaries—by offering deep, data-backed insights and real-world expertise that AI alone cannot replicate.

    3. Optimizing Content for AI-Driven Search

    Manufacturers must shift from traditional SEO tactics to structured content optimization to ensure visibility in AI-driven search results.

    • AI prefers clear, concise content structures like FAQ sections and data-backed insights.
    • Conversational search optimization (long-tail queries) helps to align your content with AI Overview’s extraction process.
    • Thought leadership pieces and industry analysis may hold greater weight in AI-driven searches.

    The Road Ahead: Preparing for AI’s Ongoing Impact on Industrial Marketing

    AI Overview in search results is just the beginning of a larger transformation in how search engines process and present content. Instead of viewing these changes as obstacles, industrial and manufacturing marketers must see them as opportunities to refine their strategies and build stronger, more authoritative content ecosystems.

    Manufacturers that proactively adapt will be well-positioned to thrive in an AI-driven search landscape. Those who ignore the shift may struggle to maintain online visibility and lead generation effectiveness.

    How prepared is your company for the impact of AI-driven search? Let’s talk if you’re navigating these challenges and need a strategy to keep your manufacturing content marketing competitive.

  • SEO for Manufacturers in the Age of AI: How Google’s Search Generative Experience is Reshaping Search Results

    SEO for Manufacturers in the Age of AI: How Google’s Search Generative Experience is Reshaping Search Results

    SEO for manufacturers, or organic SEO for manufacturers, has undergone a seismic shift in the past year. While Google’s AI Overview is still in its experimental phase, early data indicates that it’s already influencing search rankings dramatically—impacting up to 100% of complex queries while prioritizing contextually relevant content. (Source: Search Engine Journal).

    This shift isn’t an anomaly. BrightEdge data confirms that Google increasingly relies on AI Overviews (AIOs) for complex searches, particularly those involving multi-step, conversational queries. This suggests that Google’s growing confidence in AI-generated responses reduces visibility for traditionally optimized content. (Source: Brightedge).

    Why Clicks and Traffic from Organic SEO for Manufacturers are Declining in the Age of Zero-Click Searches

    The dominance of AI Overviews isn’t just shifting search behavior—it’s drastically reducing organic clicks to manufacturer websites. According to SparkToro’s 2024 Zero-Click Search Study, for every 1,000 Google searches in the U.S., only 360 clicks now go to the open web. (Source: SparkToro).

    Google searches generate only 360 clicks for every 1000 seraches

    This trend signals a growing challenge for manufacturers relying on traditional SEO strategies. With Google keeping more users within its ecosystem, fewer searches result in actual website visits. Instead, AI-generated answers, featured snippets, knowledge panels, and product carousels provide information directly on Google’s SERP—eliminating the need for users to click through to manufacturer websites.

    What Is Search Generative Experience (SGE) and AI Overview? How Do They Differ from SearchGPT?

    As organic search traffic declines, manufacturers must understand why Google’s AI-driven features are reshaping search behavior—and what that means in SEO for manufacturers. Search Generative Experience (SGE) and AI Overview are two key technologies driving this shift. While both rely on Google’s AI models, they function differently from SearchGPT, which represents a broader class of AI-powered search tools.

    Google’s Search Generative Experience (SGE)

    SGE is Google’s AI-powered search experience, designed to provide contextual, AI-generated summaries at the top of search results. Instead of displaying a list of blue links, SGE generates a conversational response based on multiple sources, allowing users to refine their queries interactively.

    For manufacturers, this means that traditional ranking factors are evolving, as Google’s AI pulls content from multiple sources rather than directing users to individual web pages.

    AI Overview

    AI Overview is a subset of SGE that appears for certain queries, offering concise, AI-generated answers at the top of the search results. Unlike SGE, which is more interactive and detailed, AI Overview provides quick, summarized insights—often eliminating the need for users to click on any external links.

    Consider this real-world example of my Google search query—“What are the differences between pneumatic and electric actuators in ball valves?”—now triggers an AI Overview that dominates the entire top half of the search results page. As shown in the screenshot, no traditional blog posts or authoritative articles appear above the fold.

    AI Overview instantly delivers a structured answer, reducing the likelihood that users will scroll down to traditional organic results.

    Google's AI Overview

    How SearchGPT Differs—A Niche Keyword Discovery Advantage

    SearchGPT represents a new breed of AI-driven search engines that don’t rely on Google’s ecosystem. Unlike SGE and AI Overview, which aim to enhance Google Search, SearchGPT operates as an independent AI chatbot—similar to ChatGPT but optimized for real-time search queries.

    One of the biggest advantages of SearchGPT for manufacturers is its ability to uncover niche, long-tail keywords that traditional SEO tools often miss.

    Example: Consider a manufacturer of industrial valves for the oil & gas industry. Conventional keyword research tools may suggest broad terms like:

    • industrial valves
    • high-performance butterfly valves
    • ball valves for pipelines

    These terms are often highly competitive and generic, making it harder to rank organically. However, SearchGPT can analyze buyer intent and technical specifications to generate hyper-specific long-tail keywords such as:

    • corrosion-resistant butterfly valves for offshore drilling
    • high-pressure ball valves for LNG applications
    • API 6D-certified valves for hydrocarbon processing

    While these long-tail keywords have lower search volumes, they attract highly qualified leads searching for specific industrial solutions—making them far more valuable for conversions.

    Some industries have seen traffic skyrocket — an increase of ~700% from ChatGPT Search alone. (Source: seoClarity). It’s not just a trend; it’s the new reality.

    Traffic from AI searches

    This ability to discover niche search patterns and generate precise queries is something traditional SEO tools often fail to do, giving manufacturers who leverage AI-powered search engines a competitive edge in their strategy for SEO for manufacturers.

    Improving Manufacturing SEO Requires Rethinking and Refining Your SEO Strategy

    As Google continues to evolve with AI-driven search experiences, manufacturers can no longer rely on traditional SEO tactics alone. The shift toward Search Generative Experience (SGE) and AI Overview means that simply ranking for broad, high-traffic keywords is no longer enough. Instead, manufacturers must focus on refining their SEO strategy to align with AI-driven search behaviors.

    What Needs to Change?

    1. Prioritizing Context Over Keywords – Manufacturers should optimize for topic clusters, search intent, and AI-friendly structured content instead of targeting high-volume terms. AI-generated results pull contextually relevant information rather than relying solely on keyword density.
    2. Expanding Beyond Google’s Traditional SERP – With zero-click searches increasing, SEO must integrate with thought leadership, social media visibility, and AI-based discovery platforms to ensure manufacturers remain visible.
    3. Leveraging AI for SEO Optimization – Generative AI tools can identify gaps in existing SEO strategies, analyze competitive content, and generate insights that traditional analytics tools might overlook.

    For a deep dive into how AI is reshaping industrial SEO, check out:

    Manufacturers looking for a structured approach to SEO, marketing alignment, and business growth should consider a Strategic Roadmap and/or Fractional CMO.

    Writing Industrial Content in a Structured Format That Answers Search Queries

    Google’s AI-driven search features, particularly AI Overview and SGE, prioritize well-structured, authoritative content that directly answers search queries. This means manufacturers must shift from traditional promotional content to a more structured, answer-driven approach in their industrial content marketing.

    Why Structure Matters for Manufacturing SEO

    • AI Overviews favor content with clear headings, bullet points, and concise summaries.
    • Complex technical topics must be broken down into digestible, scannable formats that align with AI’s response structure.
    • Search queries are becoming more conversational, making FAQ-driven and topic-cluster content more valuable.

    Yet, creating high-quality content that ranks and converts remains a major challenge for many manufacturers. According to research from the Content Marketing Institute, one of the top struggles for manufacturing marketers is producing content that is both engaging and leads to measurable business results. (Source).

    Manufacturing marketing content creation challenges

    This is where industrial content strategy must evolve—moving from generic blog posts to highly structured, problem-solving content that aligns with AI-driven search behaviors.

    Manufacturers looking to enhance content performance and ensure their insights are shown in AI-generated search results should focus on:

    Stay Ahead of AI-driven SEO Changes with Tiecas

    Manufacturing SEO is no longer about just ranking on Google—it’s about adapting to AI-driven search experiences that shape buyer decisions. With Google SGE, AI Overview, and evolving search algorithms, manufacturers must rethink their SEO strategy, content structure, and digital presence to remain competitive.

    At Tiecas, we specialize in strategic marketing for manufacturers, helping industrial companies navigate AI-driven SEO changes with data-backed strategies, structured content, and expert guidance.

    Let’s talk about how we can refine your SEO and content strategy to align with AI-driven search trends.

  • Enhancing B2B Marketing for Industrial Companies with AI Strategies

    Enhancing B2B Marketing for Industrial Companies with AI Strategies

    Artificial Intelligence (AI) is emerging as a disruptive and transformative force in B2B marketing for industrial companies. By leveraging AI, industrial businesses are streamlining operations and redefining how they engage with their customers. This technological advancement offers unprecedented opportunities for personalization, efficiency, and insight- and data-driven strategies, enabling marketers to meet the complex demands of the industrial sector.

    As we dive deeper into AI’s role, it becomes clear that its integration into B2B marketing strategies is not just an option but a necessity for staying competitive in today’s rapidly changing industrial marketplace.

    Unlocking AI’s Potential: Top 5 Questions Answered for Improving B2B Marketing for Industrial Companies

    B2B marketing for industrial companies is dynamic, and changes are inevitable. Throwing AI into the mix is both super exciting and a bit daunting. Manufacturers are keen to tap into AI’s potential to boost their industrial marketing game, but they’re also hitting pause and have a bunch of important questions. It’s like they’re standing at the edge, ready to dive into the AI pool but wondering about the water temperature, depth, and even if there’s a lifeguard on duty.

    From what I’ve seen and experienced firsthand, here are the top five burning questions on everyone’s mind when it comes to using AI in B2B marketing for the industrial sector.

    1. How Can AI Improve Lead Generation and the Qualifying Processes?

    Manufacturers are keenly interested in how AI can streamline the lead generation and qualification process. Traditional methods can be time-consuming and may not always identify the most promising prospects. AI technologies can analyze vast amounts of data to identify patterns and predict which leads are more likely to convert into sales.

    This improves the efficiency of lead-generation campaigns and ensures that B2B marketing for industrial companies’ efforts are more targeted and effective.

    Marketing Automation (MA) technology is a good example of how Marketing Qualified Leads (MQLs)are qualified and nurtured into Sales Qualified Leads (SQLs) through a quantitative, data-driven approach. MA uses smart algorithms to score leads by how they interact with your website, emails, and content. (See Industrial Lead Generation – MQL vs SQL).

    This scoring is based on actual data, making it easier to see which leads have shown an intent to buy without guessing. This means sales teams get leads that are not just interested but genuinely ready to have a meaningful conversation, making the whole sales process smoother and more efficient while shortening the long sales cycles.

    2. What Role Does AI Play in Personalizing Industrial Marketing Efforts?

    Personalization in industrial marketing is crucial for cutting through the clutter and engaging with engineers and industrial buyers. This audience is knowledgeable, has technical expertise, and has specific needs. They value content that speaks directly to their unique challenges and requirements.

    Manufacturers are exploring how AI can tailor marketing messages to individual prospects based on their behavior, preferences, and engagement history. This level of personalization helps in creating more relevant and compelling marketing content, which can significantly enhance the customer experience and boost conversion rates.

    By tailoring marketing messages to address their specific work-related interests and concerns, companies can capture their attention more effectively than with generic messaging. This targeted approach demonstrates an understanding of their professional challenges. It helps provide them with the right information at the right time they need to make more informed decisions.

    Personalization helps build trust and credibility, key components in nurturing a relationship with a highly knowledgeable and skeptical audience.

    3. How Can AI Help in Organic SEO for Manufacturers and Industrial Companies?

    AI helps industrial marketers identify trending topics and keywords by leveraging advanced data analysis and machine learning algorithms, significantly enhancing their organic SEO efforts. Here’s how it works in the context of organic SEO for industrial marketers:

    • Data analysis and pattern recognition: AI can identify patterns and trends in user behavior. By examining how engineers and industrial buyers search for solutions online, AI can detect shifts in interest or emerging problems these professionals are trying to solve.
    • Semantic search understanding: AI enhances the understanding of semantic search queries, which means it can interpret the intent behind searches, not just the literal keywords. This is where organic SEO is today as compared to the past when it was more about stuffing keywords in your content. This allows marketers to identify broader topics and questions their target audience is exploring beyond exact keyword matches.
    • Competitive analysis: AI algorithms can monitor competitors’ content and keyword strategies, offering insights into what topics are gaining traction in the industry and which keywords drive traffic to competitors’ sites. This information helps marketers optimize their content to improve their SEO ranking.
    • Content gap analysis: AI tools can quickly and efficiently identify content gaps. This enables marketers to produce and/or repurpose content to fill these gaps, targeting new and trending keywords their audience uses, thereby improving their visibility in search results.

    Incorporating AI into their organic SEO strategies enables industrial marketers to stay ahead of the competition, ensuring their content is both relevant and easily discoverable by engineers and industrial buyers actively searching for solutions. This strategic approach enhances their online visibility and builds authority, positioning their companies as thought leaders and building trust within their target audience.

    Google has released its new generative AI capabilities in search. Here is their article, Supercharging Search with generative AI.

    4. How Does AI Impact Industrial Content Creation and Distribution?

    Content marketing is a vital component of B2B marketing strategies for manufacturers; aimed at educating and engaging technical audiences. There’s a significant interest in understanding how AI can assist in creating good industrial content that resonates with engineers and industrial buyers.

    According to the Content Marketing Institute, 59% of manufacturing content marketers said their organization outsourced at least one content marketing activity. Technical content creation was the most outsourced marketing activity.

    However, it is not about finding cheap content creators; the biggest challenge in outsourcing is finding partners with adequate topical expertise (60%).

    AI-driven tools excel in generating content ideas, optimizing SEO, and automating distribution to hit the right audience in a timely manner. However, they can’t replace human writers and editors, whose skills are crucial for crafting the tone and establishing credibility, underscoring that the blend of technology and human expertise is essential for creating impactful and authentic content in digital marketing strategies.

    5. What are the Ethical Considerations and Potential Risks of Using AI in B2B Industrial Marketing?

    As manufacturers consider the possibilities of using AI in B2B marketing for industrial companies, questions about ethical considerations and potential risks arise. There’s a concern about data privacy, AI predictions’ accuracy (AI Hallucinations), and AI’s potential to spread biases. Manufacturers are looking for guidance on navigating these challenges responsibly, ensuring that their use of AI aligns with legal requirements and ethical standards while maintaining customer trust.

    ethical challenges of using AI in B2B marketing for industrial companies

    That is not to say there aren’t challenges in implementing generative AI in B2B marketing. I read an informative article published by Forrester that discusses the opportunities and challenges ahead.

    Incorporating AI into B2B marketing strategies for industrial companies offers a path to more efficient, personalized, and insightful marketing efforts. However, manufacturers must also consider the implications of AI technology, including its ethical use and the need for continuous learning and adapting.

    Ready to elevate your strategy and drive results from B2B marketing for industrial companies? With over 35 years of hands-on experience working with manufacturers and industrial companies, we bring a wealth of knowledge and expertise to the table. Plus, we understand the unique challenges of marketing to engineers and industrial buyers – we don’t learn industrial marketing at your expense. Reach out to Tiecas today.