How AI is Revolutionizing Digital Marketing for B2B Clients

In the rapidly evolving digital marketing landscape, artificial intelligence (AI) is no longer just a buzzword. It’s quickly becoming a fundamental driver of success, especially for B2B clients. As the Senior Director of SEO and AI Strategy at BOL, I've witnessed firsthand the transformative impact AI has had across various facets of marketing, from predictive analysis and data analysis to process optimization and personalization. 

The current explosion of MarTech that uses AI and the rate of change that we already see with the capabilities these tools offer is an area of huge growth where marketing agencies are providing value to customers. The ability of digital marketing agencies like the BOL Agency to focus on AI marketing technology on a daily basis allows us to leverage that expertise to keep our clients on the forefront of what is possible as well as help with implementation and application. This is especially true because although AI capabilities are a huge boost to productivity and data-driven insights, they still require human expertise and oversight to ensure successful results.

One of the biggest questions our customers have right now as AI is coming to the forefront of marketing conversations is, “How should I be leveraging AI to improve results and ROI?” There is no simple answer to that question because it depends a lot on your business model, your current MarTech stack, your specific business goals, and of course, budget. Additionally, it’s a moving target – new technologies are exploding at a rate that is nothing short of astonishing.

However, as a starting point for these kinds of conversations, let’s define common AI use cases that are currently driving results for our clients and categorize them in a way that makes it easier to understand potential value propositions. While these are subject to change and grow, as we begin 2024, there are some common use cases that are important to start implementing within your marketing program so you can stay competitive.

This is a broad overview and not exhaustive, but it provides a useful starting point for people to evaluate how to leverage AI to enhance their marketing efforts. This pyramid model is meant to illustrate common use cases and convey the relative difficulty of implementation for most organizations. Incidentally this image was created with Midjourney and edited with GIMP:

Here is a breakdown of each layer of the AI Marketing Pyramid along with some benefits, examples and implementation challenges.

Process Optimization: Enhancing Efficiency and Precision

AI's impact on process optimization spans just about every facet of marketing. AI-driven tools are making marketing processes more effective by greatly reducing the time it takes to accomplish tedious, manual tasks. The integration of advanced AI services, such as Google Workspace Duet AI, ChatGPT, Claude, Gemini and other LLMs (large language models), further enhances our capabilities in document assistance, coding (including Excel functions and RegEx functions) and smart data formatting. This paves the way for seamless, sophisticated and efficient marketing operations.

For example, within our SEO practice, BOL has found efficiencies in creating advanced Excel, RegEx and SQL functions that process and organize data, making it possible for people without coding experience to accomplish these tasks. This creates a more dynamic environment for data analysis, categorization and segmentation, which leads to better, data-driven decisions at faster velocities. 

Similarly, keyword segmentation across hundreds of keywords, meta description creation, keyword ideation and summarizing client and competitive content have all become more efficient with the use of AI and expert human oversight. Additionally, tools that we have been using since before the AI explosion, like Hubspot and Photoshop, now have AI baked into some of their capabilities.

One of the first things any business should do right now is identify tasks within their organization that are mundane, repetitive or time-consuming, then test the ability of AI-enabled LLM technologies to do those tasks. You could save time while also being mindful of accuracy and quality of output. 

Asset Creation: Streamlining Creative Processes

In the creative domain, AI can aid in every step of content creation, from ideation to visualization. Generative AI tools, particularly in Adobe products, Midjourney and DALL-E 3, have streamlined tasks such as background removal, image retouching, image ideation and proof of concept, enabling our creative team to focus more on innovation and less on manual tasks. 

Recently, AI has generated even more attention by moving beyond images and making tremendous leaps in the world of video. Sora from OpenAI is not yet available to the public, but the videos that are being shared on X from people with advance access are mind-blowing.

AI tools that generate landing pages and create ad copy variations at scale can speed up the creative process and enhance testing and optimization. Content creation can be streamlined using LLMs to create initial outlines, summaries and rough drafts to use as starting points in the creative process. These use cases have all proven valuable in creating greater efficiency and better outputs.

There is a lot of overlap between asset creation and process optimization, but both categories have distinctions that warrant them being discussed separately. Additionally, these bottom levels of the AI pyramid are the easiest to quickly implement and find value given the low barrier to entry and intuitive nature of the tool set (although some would argue that Midjourney’s Discord UI is anything but intuitive!).

Research and Strategy: Informing Future Directions

The application of AI tools in market research and strategy formulation can be very useful and add valuable perspectives. Using AI tools to perform competitive and market research by gathering data across numerous sources and summarizing large amounts of information can provide huge efficiencies and save an incredible amount of time. It also makes the output of that research much easier to consume, enabling smarter decisions. 

AI models that have been properly trained for specific use cases can augment marketing strategies with insights and details that are easy to overlook in the face of large amounts of information. AI still needs human validation to ensure accuracy, but there is no doubt that businesses can move much faster with these tools to help them with research and strategy. 

Using ChatGPT4 in conjunction with plugins that allow you to pull up-to-date information from the web and summarize it is a great low-cost entry into using generative AI to help you research topics. Of course, other models like Gemini and Claude can be used for the same purpose. As with anything produced with generative AI, human curation and validation is needed to ensure the accuracy of any output. Despite that fact, it's still possible to save hours of time just using an LLM to help gather and summarize research.  

Conversely, although I have not personally used them, third-party tools like Qualtrics and Quantilope are very advanced market and consumer research tools that leverage AI to deliver customer insights that might be otherwise unavailable or much more expensive to produce. These tools also offer functionality that could be classified under the testing and optimization category of the pyramid. There are many other tools on the market that perform similar kinds of functionality. As I alluded to earlier, oftentimes tools that leverage AI have use cases that fit into multiple levels of the AI marketing pyramid.

Personalization: Creating a Tailored Customer Experience

AI-driven personalization has emerged as a key differentiator in engaging B2B clients. By dynamically recommending personalized content and ensuring cohesive messaging across email, social media and websites, AI enables a uniquely tailored customer experience. This automated multi-channel personalization enhances engagement and relevance, setting new standards for customer interaction in the digital age.

Our partner Drift is an example of a state-of-the-art chatbot company that leverages AI to deliver personalization at scale and create better customer experiences. Drift’s technology listens, understands and learns from buyers in order to deliver personalized content or user journeys that result in better outcomes. This technology is just one example of how AI can be used to create personalization that drives customer experience and sales.

Testing and Optimization: Elevating Campaign Performance

The application of AI in testing and optimization promises to redefine the standards for campaign management and conversion testing. Through AI-powered A/B testing, bid and keyword management, digital marketing campaigns are not just optimized for performance but are also more cost-effective. 

AI's ability to manage bids, automate keyword recommendations and adjust campaign strategies in real time has transformed PPC and social media advertising into a highly efficient process. This kind of optimization, coupled with personalization, extends to ad variation, messaging variation based on customer segmentation and landing page testing, ensuring that each campaign is fine-tuned for maximum effectiveness.

Data Analysis: The Backbone of Informed Decision-Making

In the field of marketing data analysis, AI's prowess in handling big data has unlocked insights that were previously inaccessible. By analyzing traffic performance across multiple channels, offline purchase and customer interaction data, competitor activities, market trends and successful business outcomes, AI-enabled data analysis is able to find correlations that would otherwise be impossible to find given the size of the data set. This is especially true for B2B companies and those with ABM programs where data is being evaluated across multiple influencers within the same company. 

By combining this technology with automated data enrichment and cleansing, companies can ensure that customer databases are not only accurate but also rich with relevant information that leads to more accurate results. This dual approach of leveraging AI for both data insights and data accuracy creates an unparalleled foundation for informed decision-making and strategic planning.

GA4 is probably the most commonly used analytics program with AI-enabled data analysis functionality that most people have at their disposal and don’t even use yet. GA4 Analytics Insights uses machine learning and conditions to surface trends, correlations and changes that you might not otherwise notice.

There are other business intelligence and analytics technologies that offer exciting capabilities like Tableau (with its relatively new AI features), Pyramid Analytics, Polymer, and others. These are just a few of the emerging technologies that promise to deliver great customer insight at faster speeds with visualization tools that enable more people within your organization to understand your marketing data and make smarter, data-driven decisions.

Predictive Analysis: A Gateway to Strategic Planning

Finally, predictive analysis stands at the forefront of AI's potential contribution to digital marketing, offering unprecedented insights into campaign forecasting and sales predictions. By analyzing sales patterns and the data that was just described in the data analysis section, including intent data, AI models are not just predicting outcomes of PPC campaigns but also customizing these campaigns to align with potential customer behaviors. 

Tools like 6Sense, Demandbase (both BOL Agency partners) and custom-built applications in Google Vertex allow for this deep analysis, which results in lead scoring that is more accurate and revenue predictions that can significantly influence strategic planning. The ability to forecast sales with a high degree of accuracy based on market trends and historical data is revolutionizing how we approach marketing strategy and execution as well as sales enablement.

These tools give sales and marketing teams better insight into which companies on your target account list are actually in-market with a much higher propensity to purchase and help you prioritize resources for sales outreach and additional marketing efforts. Aligning your teams in this way can significantly uplevel the ROI of both sales and marketing expenses.


AI's integration into digital marketing promises to not just enhance operational efficiency but also offer strategic advantages that were previously unimaginable. This is just the beginning of the AI revolution in marketing. To create some perspective as to what the next 5, 10 and 20 years are going to look like, I often tell people that we are in the “flip phone” era of AI. As we continue to explore how we can integrate AI into our digital marketing strategies to make them more effective and efficient, the future looks not just promising, but boundlessly innovative.

For B2B marketing agencies like BOL, our challenge is to stay up to date on emerging capabilities that are moving at incredible velocity and to constantly evaluate how AI technology can enhance performance for our clients. It’s an awesome responsibility and an exciting opportunity. AI tools don’t replace humans, but they do allow experts to do more in a shorter period of time and create better and more data-driven business outcomes. 

For B2B marketers who are trying to get ahead of competitors and make sure they’re adapting to this new paradigm in a responsible and effective way, the AI Marketing Pyramid we’ve defined here is a good initial lens to view the possibilities of AI to enhance marketing efforts. Evaluating how you can apply AI solutions to these seven marketing use cases can give you some initial direction that I hope will prove valuable:

  • Process Optimization
  • Asset Creation
  • Research and Strategy
  • Personalization
  • Testing and Optimization
  • Data Analysis
  • Predictive Analytics

Ultimately, the long-term goal is to connect all of these solutions across your entire marketing program and have them working synergistically with each other. This will not only produce optimal results, but also set a foundation that supports agile adoption of new AI technologies and capabilities as they emerge. Need some guidance? Drop us a line. We love to chat about innovation, technology, AI and results.