.jpg)
Would you like to generate sales, leads, and web traffic with content?
Contact us
¡Gracias! Hemos recibido su subscripción.
Oops! Something went wrong while submitting the form.
In a landscape where over 60% of marketers have embraced artificial intelligence (AI), it presents an opportunity for companies to enhance the efficiency of their content creation processes and increase the chances of success in their strategies.
In the B2B world, unlike B2C, the strategic focus centers around a longer and more complex decision-making process involving multiple stakeholders and attention to detail.
In this model, creating, optimizing, and distributing relevant content is crucial for establishing solid relationships with potential clients. This is because purchasing decisions in the B2B realm are often more complex and based on trust and perceived value. Companies can build trust by providing relevant and valuable content demonstrating their expertise and know-how.
Artificial intelligence can effectively help achieve these objectives as it not only assists B2B companies in generating relevant and valuable content but also aids in overcoming challenges in lead generation, content personalization, and optimization.
In fact, according to a 2023 AI marketing comparative report, over 60% of respondents have utilized AI in their marketing operations, and according to a McKinsey Global Institute report, up to 70% of companies will adopt AI by 2030.
It is necessary to know how to build all the stages of a coherent and effective B2B content strategy and understand how AI can assist each.
Knowing and mastering these phases will allow you to develop a well-structured strategy aligned with your brand's objectives and designed to attract and retain your target audience:
The first step of a B2B content strategy is benchmarking against competitors. In this phase, the goal is to gain insights into how other relevant players approach content marketing and target a common audience.
Thanks to data analysis algorithms and natural language processing (NLP), AI can gather different types of information about the content marketing of the studied competitors. It can track and analyze large volumes of online content to identify patterns, trending topics, effective writing styles, and distinctive features of successful content.
With this information, companies can make more informed decisions about the topics to address, the writing style to adopt, and the approach they should take in their content.
Tools like BuzzSumo, Content Insights, True Content, or SEMrush provide content analysis to identify the best-performing topics, formats, and other content characteristics for a specific audience.
According to Salesforce's State of the Connected Customer report, 66% of customers expect companies to understand their unique needs and expectations fully. Therefore, B2B marketers must identify customer needs and preferences and anticipate their desires. This is where AI can provide a strategic advantage in the process. Let's see how:
AI can help segment the audience based on various criteria such as industry, company size, behavior, interests, and search intentions of decision-makers and other strategic personnel within a business.
With this information, AI can build specific audiences according to how companies want to segment and target their target audience. For example, a company like Rockwell, which offers industrial automation and information systems, can segment its audiences by industry and customize content for each.
AI can analyze large customer data sets, such as CRM data, purchase histories, online interactions, and customer feedback. In terms of content, AI can identify content consumption interests, trending topics, format preferences, consulted media, and more.
Thanks to this information, companies can better understand customer behavior and preferences.
For instance, tools like True Content identify the content interests of target audiences. Also, tools like Mindpath analyze the companies visiting your corporate website and, with intent data, filter potential customers by interests and persuade them with personalized content.
AI can identify the emotional tone, sentiment, and readability level of editorial content. A B2B company specializing in packaging, for example, can use AI to ensure that the content directed at the C-level of its target companies is optimized in terms of tone (the overall tone of the content), sentiment (the general sentiment of the content will evoke in the reader), and readability level (content written according to the reader's level of comprehension on a particular topic).
AI-driven tools like True Content can help optimize content in these aspects.
Structuring the strategy is the third step in creating a successful B2B content marketing strategy.
In this stage, the brand's content territory (the "sweet spot" between the brand and audience interests) is defined, content verticals and sub-verticals are built, base indicators for content optimization are determined, and the execution phases of the content marketing project are addressed.
To achieve this, AI can provide recommendations based on accurate and objective information that allows for the efficient structuring of a B2B content strategy. Moreover, it ensures that the strategy is backed by solid data, maximizing the content's impact in terms of SEO, relevance, and appeal to the audience.
For example, the HubSpot Content Strategy tool provides AI-powered content planning tools to assist in structuring and organizing the strategy.
AI has revolutionized how content is produced by providing automated tools and machine learning algorithms capable of analyzing vast amounts of data and generating coherent, high-quality content.
These models have been trained on extensive datasets and can understand and emulate the style and structure of human language.
AI content generation uses advanced language models and natural language processing (NLP) techniques. It can generate texts such as articles, reports, or product descriptions.
For instance, an office furniture company can use AI to create personalized articles for each type of customer (project managers, architects, others) based on their preferences and specific challenges. For example, a post discussing the new interior design trends for 2023 could be created with the assistance of an AI like Chat GPT or Jaspers.ai.
According to a Capterra study, 82% of surveyed specialists believe that content generated by AI software is as good as that produced by humans, meaning it can streamline large-scale content production. However, fully autonomous content generation still presents challenges and requires human supervision and editing.
AI-powered tools like Grammarly and ProWritingAid provide grammatical corrections, style suggestions, readability enhancements, clarity, coherence, and suggest rewriting sentences or paragraphs.
Tools like True Content, Buzzsumo, or SEMrush use AI algorithms to analyze search data and existing online content, identifying trends, popular keywords, and topics generating interest among the target audience. This way, they generate relevant ideas for content.
AI-based content curation tools like Scoop.it or Feedly use algorithms to automatically collect and filter relevant content from different sources, saving time on manual searches and enabling users to find and share high-quality content.
Some AIs automatically generate videos or infographics, such as Wibbitz, which turns texts into professional videos, allowing for the rapid generation of attractive visual content, or Animaker, which automatically creates animated videos with various styles and templates.
Content optimization is key to ensuring that the produced material attracts the right target audience, leading to effective lead generation and conversions (customers).
In this context, artificial intelligence (AI) has emerged as a tool that drives content optimization for the following reasons:
AI-driven tools can analyze existing content and assess its quality, relevance, and SEO performance.
These tools use natural language processing algorithms to identify patterns and features that influence search engine rankings.
They can provide insights into content structure, keyword density, readability, meta tags, and other aspects that impact SEO.
They can also identify popular topics in search engines related to the market niche, helping to generate content that addresses uncovered search needs.
Several AI-powered tools can be helpful in B2B content SEO optimization, for example:
- Yoast SEO: Offers AI-based content optimization recommendations to improve SEO performance.
- SEMrush: Provides keyword analysis, optimization suggestions, and SEO performance tracking.
- Clearscope: Analyzes existing content and provides recommendations to optimize and improve its visibility in search engines.
- Google Search Console: Provides detailed data and reports on organic search performance and potential SEO issues in the content.
AI-driven tools recommend adjusting content structure, optimizing keywords, improving readability and coherence, and adding elements like internal and external links. These suggestions help enhance the quality and relevance of the content for search engines and users.
For instance, using AI, the True Content platform allows analysis and identification of aspects such as tone, sentiment, and readability level, leading to proposed improvements.
AI can analyze search queries, keyword competition, and trends to suggest relevant, high-performance keywords. They can also provide information on the content's appropriate keyword density and distribution.
AI can provide insights into site navigation, content interaction, and user satisfaction by analyzing reader behavior data on a website.
This helps identify areas for improvement and optimize content to offer a more relevant and engaging experience, ultimately enhancing the browsing experience.
AI can assist in distributing and promoting content by utilizing algorithms to identify the most effective channels and optimal times for publishing.
There are several ways to leverage AI-powered tools for content distribution, such as:
Intelligent algorithms can perform A/B tests to compare different variations of content distribution strategies.
By testing different headlines, visuals, publishing schedules, or segmentation parameters, AI can help identify the most effective distribution approaches to improve engagement and conversion rates.
Predictive analysis can be used to forecast the potential performance of your content on different channels and platforms.
By analyzing historical data and market trends, AI can predict which distribution strategies will likely yield the best results, enabling data-driven decision-making.
Programmatic advertising platforms use AI to automate and optimize advertising efforts. With intelligent algorithms, they create targeted and personalized ads, making data-based decisions to maximize return on investment (ROI).
This allows B2B companies to reach their target audience at scale and deliver relevant content on the proper channels.
Automated social media scheduling tools analyze engagement and content performance data to schedule posts at the most practical times, maximizing visibility and audience engagement across multiple platforms.
These tools can automatically publish content on multiple social media platforms. For instance, Mindpath automates and filters your brand's content, displaying it to potential customers through retargeting.
With the exponential growth of available data and the need to make rapid, evidence-based decisions, AI has become an ally in B2B content:
AI can measure and analyze various content performance metrics, such as reach, engagement, conversions, dwell time, bounce rate, and more.
These key metrics provide a clear insight into how content resonates with the audience and whether it achieves established objectives.
AI can compare content performance with set objectives and goals. By using machine learning algorithms, it can assess content effectiveness based on the outcomes.
For example, if the goal is to increase conversions, AI can identify which content or strategies generate better results and suggest necessary adjustments.
AI can provide practical recommendations and improvement suggestions based on data analysis. For instance, it can suggest content strategy adjustments, such as format changes, publishing frequency, or distribution channels, to enhance performance and results.
Using machine learning techniques, AI can predict future content performance. Based on historical data and identified patterns, it can suggest what types of content, formats, or channels may yield better engagement, conversions, and ROI results.
Several AI-driven tools can help track and analyze content performance in terms of engagement, SEO, and ROI, among other parameters:
- Google Analytics: Provides detailed information about user behavior, engagement metrics, and conversions. Additionally, it offers data-driven segmentation and personalization capabilities.
- Content Square: This digital analytics platform uses AI to visualize user behavior on the website and content. It provides heatmaps, session recordings, and in-depth analysis to better understand how users interact with content and identify areas for improvement.
- Salesforce: The advanced analytics tool utilizes AI to provide actionable insights into customer interactions, conversions, and content performance. It offers data visualization and predictive analysis capabilities to optimize marketing strategies.
AI has transformed B2B content marketing, optimizing every step of the B2B content strategy process. It enables a better understanding of the audience, streamlines content production, and distribution, enhances lead acquisition, and provides suggestions to optimize performance.
By adopting AI, B2B marketers gain a competitive advantage, increasing the efficiency and effectiveness of their strategies and promoting business growth.
Bazaman, M. (2022, september 13). Does AI write better copy than humans? Most marketers think so. Capterra. https://www.capterra.com/resources/ai-marketing/
Geyser, W. (2023, february 22). Artificial intelligence (AI) Marketing Benchmark Report: 2023. Influencer Marketing Hub. https://influencermarketinghub.com/ai-marketing-benchmark-report/
Step-by-Step Guide: How to Create a B2B Content Marketing Strategy. (n.d.). Castleberrymedia.co. Retrieved July 11, 2023, from https://www.castleberrymedia.co/post/guide-step-by-step-how-to-create-a-b2b-content-marketing-strategy
Iat. (2020, february 7). La Inteligencia Artificial en el marketing digital. IAT. https://iat.es/tecnologias/inteligencia-artificial/marketing-digital/
La Inteligencia artificial en la estrategia. (s/f). Mckinsey.com. Retrieved July 11, 2023, from https://www.mckinsey.com/featured-insights/destacados/la-inteligencia-artificial-en-la-estrategia/es
Notes from the AI frontier: Modeling the impact of AI on the world economy. (s/f). Mckinsey.com. Retrieved July 11, 2023, from https://www.mckinsey.com/featured-insights/artificial-intelligence/notes-from-the-AI-frontier-modeling-the-impact-of-ai-on-the-world-economy
Reyero, R. (s/f). La Inteligencia Artificial (IA) y su aplicación en Marketing. Hayasmarketing.com. Retrieved July 11, 2023, from https://www.hayasmarketing.com/blog/la-inteligencia-artificial-ia-y-su-aplicacion-en-marketing
Salesforce Research. (2020). ESTADO DEL CLIENTE CONECTADO. Salesforce.com. https://www.salesforce.com/content/dam/web/es_es/www/pdf/forth-state-of-the-connected-customer.pdf
