Leveraging AI in B2B Marketing
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B2B marketing is changing at an impressive rate, and at the center of this transformation is artificial intelligence (AI). AI has quickly become an important tool for marketers looking to stay competitive, optimize their strategies, and deliver exceptional customer experiences.
AI is uniquely suited to address some of the toughest challenges in B2B marketing, including lengthy sales cycles, complex decision-making processes, and the need for hyper-targeted campaigns to reach niche audiences. From enabling personalization at scale to uncovering deeper insights from your own data, AI allows marketers to focus more on creativity, strategy, and innovation.
According to the CMO Survey, marketers are using AI roughly 11% of the time in their marketing activities. B2B sectors show moderate adoption of AI in marketing activities while B2C marketers lag slightly.
Why AI Matters in B2B Marketing
Artificial intelligence represents a shift in how B2B businesses can approach marketing. By leveraging its capabilities, marketers can identify key trends quicker and more efficiently than ever before, allowing marketers to engage with their target audience with the right message at the right time.
Unlike traditional marketing strategies, AI-driven solutions offer the ability to:
Predict Outcomes: AI tools analyze vast datasets to identify patterns, allowing marketers to forecast which strategies are most likely to resonate with their audience. For example, predictive analytics can help identify the most promising leads, saving time and resources.
Streamline Processes: By automating repetitive tasks like data entry, reporting, or audience segmentation, AI eliminates inefficiencies. This allows marketing teams to focus on high-value activities, such as creative content development and campaign optimization.
Enhance Personalization: AI enables marketers to deliver customized messaging that aligns with a prospect's unique interests, behavior, or stage in the buyer journey.
Ad Optimization: Paid media platforms like Google Ads and LinkedIn Ads are increasingly leveraging AI to optimize campaign performance. From automated bidding strategies to dynamic targeting, AI is transforming how marketers approach paid media campaigns. To stay competitive, B2B marketers must embrace these advancements and actively test AI-driven features to unlock their full potential.
For example, imagine you’re a manufacturing marketer, targeting aerospace procurement managers. These buyers often require specialized components and in-depth technical details during their research. For this example, here are some relevant use cases:
Predict Demand Trends: AI analyzes historical sales data, seasonality, and market dynamics to predict when aerospace companies might require specific parts or materials. This insight allows you to customize your outreach campaigns to align with purchasing cycles.
Personalized Engagement: AI-powered tools segment your audience based on company size, industry, or behavior (e.g., downloading a CAD file). You can then deliver content like case studies or webinars showcasing how your product improves efficiency in aerospace manufacturing.
Streamlined Communication: AI chatbots on your website provide instant responses to technical queries or RFQ requests, ensuring prospects receive the information they need without delays. The questions that are asked in the chatbot can then fuel content-creation strategies.
By integrating AI, businesses can move beyond traditional marketing strategies and tactics to deliver precision, efficiency, and personalization– all key elements for success in the competitive B2B space.
The Impact of AI on B2B Marketing in Numbers
- 80% of B2B companies plan to incorporate AI into their marketing strategies by 2025.
This statistic reflects the growing trend of AI adoption in B2B marketing, as companies recognize its potential to enhance efficiency and effectiveness.
- By integrating Chatbots into their marketing strategy, 26% of US B2B marketers have experienced an increase in lead generation by 10-20% and 99% of B2B marketers believe AI chatbots improve lead conversion rates.
These statistics show the importance of leaning into technology, intending to shorten the (generally speaking) long sales cycles that many B2B marketers face.
Artificial intelligence is redefining what’s possible. As we dive deeper into this guide, you’ll discover actionable insights and proven strategies for leveraging AI to transform your B2B marketing efforts.
AI’s Impact on The Search Landscape
The rise of AI technologies is reshaping the search landscape, creating both challenges and opportunities for B2B brands. To stay competitive, it’s important to adapt strategies that align with these changes.
AI-Driven Search Changes and Their Impact
1. AI-Driven Search Results
AI-powered overviews are becoming more prevalent on search engine results pages (SERPs), significantly reducing organic clicks. If you haven’t heard about zero-click searches, nearly 60% of Google searches were expected to end without a click in 2024… thus the coined phrase “zero-click searches”.
What to do about it?
Implement Generative Engine Optimization (GEO) strategies to ensure your content remains visible across search platforms like Google, Bing, and AI-driven tools such as ChatGPT, Gemini, or Perplexity. Focus on creating clear, concise, and directly relevant content that addresses user needs to rank for AI-driven search results.
2. User Behavior is Shifting
Users are increasingly engaging with search engines in a conversational way, similar to how they interact with AI tools like ChatGPT and voice assistants such as Alexa or Google Assistant.
What to do about it? Refine your B2B content strategies to address natural language queries and focus on user intent. Content should feel conversational, intuitive, and aligned with the way users phrase questions in these emerging search formats.
3. Search is Expanding Beyond Google
Search behaviors are diversifying, with users turning to alternative platforms such as AI-powered Bing, TikTok Search, ChatGPT plugins, and AI-driven voice assistants to find information.
What to do about it? Develop a diversified search strategy to ensure visibility across multiple platforms. Brands that embrace these emerging tools will have a competitive advantage in maintaining strong digital visibility.
4. Content Expectations are Higher
AI is raising the bar for content quality by prioritizing E-E-A-T principles: Experience, Expertise, Authoritativeness, and Trustworthiness. As AI evaluates content to deliver trusted answers, meeting these criteria has become critical to ranking success.
What to do about it? Collaborate with subject matter experts to produce high-quality, credible content that demonstrates deep industry expertise. Prioritize well-researched, authoritative material to build trust with both users and AI algorithms.
Consider the stage your potential customer is in:
Information-Gathering Phase: If your audience is in the early stages of their journey, focus on creating content that answers common questions or provides educational value. Use question-based triggers such as “how,” “what,” or “why” to address their curiosity and establish your brand as a trusted source.
Buying Phase: For audiences ready to make decisions, provide actionable content such as comparison guides, product demos, case studies, or success stories to help them take the next step confidently.
5. Paid Media is Becoming More AI-Driven
AI is reshaping paid media strategies by automating tasks such as ad optimization, audience targeting, bidding strategies, and predictive analytics. Platforms like Google and Facebook are also introducing tools for automated image and video creation, enabling faster turnarounds for getting campaigns live.
What to do about it? Dedicate testing budgets for new ad formats and creative enhancements to maximize AI-powered tools. Leverage first-party data for improved targeting and personalization, and embrace automation to streamline ad management and scale performance.
AI Use Cases in B2B Marketing
Incorporating artificial intelligence into your B2B marketing strategies empowers you to analyze data more efficiently, create personalized and highly targeted campaigns, and significantly reduce the time spent on repetitive tasks. With AI, you can make more accurate predictions, enhance lead generation efforts, and accelerate your time to close—all while focusing on high-value strategic initiatives.
Below are a few ways you can leverage AI in B2B Marketing:
Customer Segmentation
AI enables precise customer segmentation by analyzing large datasets to identify shared characteristics, behaviors, or buying patterns. This allows marketers to create highly targeted campaigns for specific segments, such as industry, company size, job title, or stage in the buying cycle.
- Examples:
AI can group customers based on their browsing behavior, such as frequent visits to a specific product page, and send customized content to keep them engaged.
At Workshop Digital, we use AI to create lookalike segments in Google Demand Gen campaigns based on your first-party customer data. This allows us to target people who are found to have similar characteristics to your existing customers.
Google Analytics 4 can use AI to generate predictive audiences based on visitors’ likelihood to convert. These audiences can be used as segments for detailed reporting or exported to use in remarketing lists. Although this is currently only available to e-commerce sites, we expect that Google will expand to include lead generation objectives as well.
Lead Generation & Qualification
AI can monitor website activity, email responses, and other touchpoints to determine a lead’s level of interest and readiness to buy.
- Examples:
Salesforce Einstein or Hubspot AI can rank leads based on the likelihood to convert, ensuring your sales team focuses on high-quality leads.
Tools like CallRail call tracking can automatically qualify or score your calls and pass that data back to you to optimize campaigns toward the most qualified leads.
Landing page A/B testing platforms like Unbounce use AI to direct visitors to the landing page variant who is most likely to convert to a lead.
Predictive Analytics
Predictive Analytics uses AI to anticipate customer needs and behaviors, such as likelihood to purchase, churn, or engage. This helps marketers allocate resources more effectively and plan proactive strategies, versus reactive ones.
Use case: A manufacturing company might use predictive analytics to forecast demand trends for a specific product, allowing marketing to align campaigns with peak purchasing periods.
Chatbots and Virtual Assistants
AI-driven chatbots provide real-time engagement with prospects and customers, offering instant answers to FAQs, technical support, or RFQ submissions. They can also collect valuable data about customer needs.
- Example:
A chatbot on a manufacturing website can guide buyers through a product configurator, helping them find the best solution based on their specifications.
Personalization
AI makes hyper-personalization possible by customizing content, recommendations, and messaging to individual prospects based on their preferences and behaviors. Websites can display dynamic content, such as case studies or product demos, based on the visitor’s industry or role.
- Example:
An aerospace procurement manager sees a tailored landing page with CAD downloads and a webinar invite relevant to their sector.
Sales Intelligence
AI improves sales intelligence by gathering and analyzing data about prospects, competitors, and market trends. This provides sales teams with actionable insights to drive conversations and close deals. AI can identify buying signals, such as frequent visits to pricing pages or multiple interactions with emails, prompting timely sales outreach.
Example: LinkedIn Sales Navigator uses AI to track prospect engagement and recommend connections or messages to accelerate deal progress.
Content Creation and Optimization
AI can help B2B marketers brainstorm blog ideas, create content outlines, and optimize existing content. Tools like Clearscope and MarketMuse analyze keywords and competitor content to help marketers craft high-performance content ideas. AI tools like Jasper or Copy.ai assist in creating ad copy, email campaigns, or even long-form blogs. With any AI-assisted content creation, we recommend that there is a human component to review accuracy and readability for your target audience.
- Example:
An AI tool analyzes trending topics in industrial manufacturing and suggests relevant blog ideas such as “How CNC Machines are Transforming Aerospace Production”
Ad Optimization
AI drastically impacted paid media advertising by automating and refining campaign management:
Bidding Strategies: AI optimizes bids in real-time to meet campaign goals, like maximizing conversions or minimizing cost-per-lead (CPL).
Targeting: AI identifies and targets high-value prospects based on browsing behavior, intent signals, or demographic data.
Creative Testing: Google or Microsoft ad platforms test multiple ad variations, through creatives such as Google Responsive Search or Display ads, to determine the most effective combination of visuals, headlines or descriptions, and CTAs.
Campaign Types: AI-powered campaign types are emerging, with the inclusion of campaign types such as performance max and demand gen.
How to Implement AI in Your B2B Marketing Initiatives
For businesses ready to adopt AI, a strategic approach ensures smooth integration and impactful results.
Step 1: Audit Existing Processes and Tools
Analyze your current marketing stack to identify inefficiencies and gaps. Look for areas where AI can add value, such as lead generation, ad optimization, data analysis, or personalization.
Many SaaS tools are already incorporating AI, but not all are created equal. Inventory your current software stack to see if you may already have access to existing AI-enhanced functions.
Understand your company’s technology and security policies to determine if you will need IT, legal, or compliance approval before sharing proprietary information with AI tools.
Step 2: Set Clear Goals
Define specific, measurable goals for your AI initiatives.
Metrics-Driven Examples: Increase lead-to-opportunity conversion rates by 15%, reduce cost-per-acquisition (CPA) by 20%, or improve email open rates by 10%.
Workflow Example: Shorten campaign launch times by 25% or improve campaign reporting efficiency.
Step 3: Select the Right Tools
Choose AI tools customized to your needs.
For Lead Scoring: Salesforce Einstein, 6sense
For Content Creation: Jasper, MarketMuse
Imagery: Pebbly AI Product Photography
For Ad Optimization: Google Performance Max, LinkedIn Ads
Step 4: Train Your Team
Equip your marketing and sales teams with the knowledge to use AI tools effectively. Establish the importance of QA’ing the outputs and checking for copyright and/or trademark issues before publishing AI-generated content. Many platforms offer online tutorials, certifications, or hands-on training sessions.
Step 5: Start Small and Pilot
Begin with a small-scale project, such as implementing chatbots for customer inquiries or testing our new campaigns such as performance max or demand gen in Google Ads. Make sure to always measure performance and make data-driven adjustments and optimizations.
Step 6: Scale and Iterate
Expand AI implementation to other areas of your marketing strategy based on what worked in your pilot. Continuously monitor performance and refine tactics.
B2B Marketing AI Tools
AI-driven tools are reshaping the way B2B marketers plan, execute, and optimize their campaigns. By leveraging a mix of tools, businesses can streamline processes, uncover deeper insights, and create highly personalized and impactful strategies that resonate with their audiences.
Below are a few of tools that we use at Workshop Digital, though not an exhaustive list by any means:
Paid Media Management and Optimization
Tools like Google Ads, Microsoft Ads, LinkedIn Ads, and Meta Ads utilize AI to automate and optimize campaigns. They provide advanced features such as predictive bidding, audience segmentation, and creative recommendations, ensuring you maximize ROI while reducing manual effort. Campaign types are more and more moving toward more AI-based strategies, with the launch of campaign types like Performance Max and Demand Gen in Google Ads.
How it helps: AI can automatically adjust bids, identify high-performing ad creative, and target the most relevant audiences based on historical data and real-time signals. This enables your paid campaigns to perform efficiently and adapt to changing conditions.
Search Engine Optimization and Content Performance
Platforms such as Semrush and ChatGPT/Gemini empower teams to craft data-driven content strategies. From keyword research and competitive analysis to AI-generated content outlines and custom Google scripts, these tools help B2B marketers stay ahead and competitive.
How it helps: AI tools streamline SEO by identifying content gaps, analyzing competitors, and optimizing pages for high-impact keywords. This enables marketers to focus on delivering value while AI handles the heavy lifting of analysis and recommendations.
Customer Journey Analytics and Personalization
Understanding how users interact with your site and content is key to B2B success. Tools like Google Analytics 4 (GA4), Adobe Analytics, and Hotjar provide AI-powered insights into user behavior, helping marketers identify friction points, optimize user flows, and create more personalized experiences.
How it helps: With heatmaps, session recordings, and advanced attribution modeling, these tools allow marketers to pinpoint where users are dropping off or converting—and adapt strategies accordingly.
Conversion Rate Optimization
Platforms like Unbounce and CallRail are essential for improving lead capture and nurturing. Unbounce leverages AI to create high-converting landing pages, while CallRail provides AI-driven call tracking and lead scoring.
How it helps: By using AI to test variations, track call outcomes, and integrate lead data into your CRM, these tools enable you to improve your conversion rates and sales pipeline effectiveness.
Integrated Analytics and Decision Support
Combining tools such as GA4, Adobe Analytics, and other AI-driven analytics platforms enables marketers to build a holistic view of their campaigns. AI supports predictive modeling and trend analysis, making it easier to identify which strategies are working and which need refinement.
How it helps: By synthesizing data across platforms, AI helps B2B marketers focus on the metrics that matter most while automating reporting and forecasting.
Why Should These AI-Driven Tools Matter to B2B Marketers?
B2B marketing is complex, with long sales cycles, multiple decision-makers, and a growing demand for personalization. AI tools like these empower marketers to:
Automate tedious tasks, freeing up time for strategic thinking.
Deliver better insights, leading to more informed decision-making.
Enhance customer experiences, building trust and driving conversions.
Stay agile and competitive in a progressing digital world.
By integrating AI tools into every stage of your marketing funnel—from discovery to decision-making—you can achieve greater efficiency, precision, and results… freeing up for more strategic thinking.
AI in B2B Marketing is Changing The Way Businesses Operate
No longer just an emerging technology, AI has become an important tool for companies aiming to stay competitive. By adopting AI-powered tools and strategies, businesses can improve productivity, deliver hyper-personalized customer experiences, and make smarter, data-driven decisions.
The opportunities AI brings—from automating repetitive tasks to enhancing lead generation and optimizing campaigns—are reshaping what’s possible in marketing. Now is the time to embrace AI, start small, and scale strategically.
Ready to start advancing your marketing approach through advanced digital marketing strategies? Let’s chat about your marketing strategy.
