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Building an AI Marketing Strategy for Growth: A Data-Driven B2B Approach

Founder of Orchid Agency
Carla Sinfon
October 18, 2023
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B2B marketing is drastically changing and as a result, businesses are constantly seeking innovative ways to stand out from the competition… enter AI for marketing!

AI marketing uses artificial intelligence technology to analyze data, predict behaviors, and optimize marketing strategies for better engagement. AI becomes a highly valuable tool in personalizing the customer journey, achieved through AI-powered chatbots, targeted advertising, and content generation.

The market value of AI is worth 100 billion US dollars and is expected to grow to nearly 2 trillion US dollars by 2030! Simply put, the AI market is exploding. 

In this blog, we’ll explore the key steps to building an AI marketing strategy for growth, and why it’s crucial for your B2B business to keep up.

What are the AI marketing benefits for B2B businesses?

In a saturated space where marketers are vying for customers’ attention, AI should be treated more like a “smart marketing companion” in terms of optimizing marketing efforts, driving growth, and staying ahead of competitors through a data-driven approach.

What’s more, it’s predicted that 30% of B2B marketing messages and content will be AI-generated by 2025, according to Gartner.

B2B businesses can gain the following benefits when incorporating AI into their marketing strategy:

  • Improved Personalization: AI enables you to tailor-fit your marketing strategy to customers’ needs.
  • Data-Driven Insights: AI is powerful enough to process and analyze large sets of data, which translates to more reliable, accurate, and measurable results.
  • Lead Scoring and Qualification: AI-powered lead scoring systems can assess the likelihood of a lead becoming a customer.
  • Marketing Automation: It can automate repetitive tasks, analyze vast amounts of data, predict customer behavior, and optimize marketing campaigns.
  • Boosted Customer Support: Chatbots powered by AI can provide personalized and timely responses to customer inquiries, thus improving customer satisfaction and engagement.
  • Search Engine Optimization: By analyzing data patterns, identifying keywords, generating content, and providing insights, AI optimizes website rankings and visibility on search engines.
  • Content Generation: AI can help you come up with relevant content, optimize results, and distribute content to your target audience.

AI is a game-changer when it comes to B2B marketing. By using AI, B2B businesses can gain valuable insights into customer preferences, target the right audience with personalized messages, and ultimately drive growth!

What are B2B AI marketing examples?

1. Predictive Lead Scoring

B2B companies can have a wide range of leads coming in through different channels. But, not all leads are equally likely to convert into customers. AI can be used to implement predictive lead scoring, which involves analyzing historical data to identify patterns and characteristics that indicate a lead's potential to convert.

For example, let's consider a software company that provides a specialized solution for logistics companies. By using AI algorithms, they can analyze past customer data and identify factors such as company size, industry, engagement with marketing content, website behavior, and more. AI then assigns a predictive score to each lead, indicating the likelihood of that lead converting into a paying customer.

With predictive lead scoring in place, the company's sales team can prioritize their efforts on leads with the highest scores. This approach not only saves time but also increases the likelihood of closing deals by focusing on leads that are more likely to convert.

2. Personalized Content Recommendations

B2B companies often have a variety of content, like whitepapers, case studies, webinars, and blog posts, aimed at educating and engaging potential clients. AI can be used to create personalized content recommendations based on each individual lead's preferences and behavior.

Imagine a B2B marketing agency that offers services to other businesses. By implementing AI, they can track a lead's interactions with their website, emails, and other content. AI learns from these interactions to understand the lead's interests, challenges, and pain points.

When the lead returns to the website, AI can dynamically display content recommendations that are most relevant to their needs. This tailored approach not only enhances the lead's experience but also increases the chances of capturing their interest and moving them closer to making a purchase decision.

How can I get started with an AI marketing strategy?

1. Define Your Objectives

Begin by identifying specific goals you want to achieve with AI. Whether it's improving lead conversion rates, enhancing customer experience, better imagery, or creating content having clear objectives will guide your AI strategy effectively. It’s helpful to break down a single use case into repeatable steps to see where AI technology would make the most sense.

2. Know Your Target Audience

Understanding your target audience inside and out is essential before implementing your AI marketing strategy because it forms the foundation for personalized interactions. By knowing your audience's preferences, behaviors, and pain points, AI can be used to tailor content, recommendations, and engagement strategies that resonate deeply.  Without this info, your AI efforts may be irrelevant to your target market.

3. Gather Data

AI thrives on data. Start by collecting relevant data from various sources within your business, such as customer interactions, sales data, website behavior, and more. Always begin with data that is clean, organized, and well-structured for accurate AI analysis. 

4. Choose the Right AI Tools

To say there are a lot of AI tools on the market is an understatement. Narrow down your search by looking for tools that align with your objectives. For example, if lead generation is a priority, consider implementing predictive lead-scoring algorithms. If customer support is crucial, explore AI-powered chatbots. Make sure the chosen tools address your business needs. We’ll chat more about tools further down.

5. Demo and Test

Before a full-scale rollout, conduct pilot projects to test the effectiveness of your AI tools. Use a subset of your data to validate the outcomes and refine the tasks. This phase helps you identify any adjustments needed before the big rollout.

6. Train Your Team

Make sure your team is comfortable with the new AI tools and processes. Provide interactive and engaging training sessions to empower your team. For long-term AI success, it’s imperative to not only train but empower your team on your AI tech.

7. Always Monitor and Refine

After implementing your AI strategy, continuously monitor its performance. Analyze metrics such as engagement rates, conversion rates, and customer experience. Use this data to refine your strategy and make iterative improvements.

8. Stay Updated

AI technology is always evolving.  Stay informed about the latest advancements in AI that could benefit your B2B business. Regularly reassess your strategy to ensure it remains aligned with your evolving goals.

By following these steps, you can initiate an AI strategy that drives innovation, efficiency, and growth in your B2B business. Remember that AI implementation is an ongoing process, and adapting to new insights and trends will help you stay at the forefront of your industry.

What are the 4 types of primary AI technology?

Of course, your AI marketing strategy won’t be effective without the right tools. It is crucial to first identify the tools that will best complement your marketing strategy. These tools are divided into four buckets to help you determine which ones to use:

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The tools are divided into less advanced and more advanced, and those isolated from other platforms versus those which are integrated into broader platforms. 

If you’ll need more advanced tools but those isolated from other platforms, you may go for standalone task automation apps such as basic customer service chatbots and email marketing automation systems; standalone machine learning apps include those tools that use a more targeted approach in providing answers to customers’ needs or queries. If you’re looking into more advanced tools which are integrated into other platforms, then CRM-based predictive sales-led scoring or programmatic digital ad buying may be your best bet.

Key Takeaway

In today's data-driven marketing landscape, building an AI marketing strategy for B2B growth is key to staying competitive. By leveraging AI tools, businesses can gain valuable insights from accurate statistical data, personalize marketing messages, optimize campaigns, and generate leads and conversions. Talk to us today for more information on how you can start a foolproof AI marketing strategy geared toward success!