Since the emergence of Artificial Intelligence (AI) in the business world, different sectors have been gradually adapting to this technology, and B2B marketing is no exception.
AI is becoming an essential tool for companies to simplify their routine tasks and some of their most critical processes. They are now able to optimise everything, from strategic data analysis to the operation of advertising platforms such as Meta Ads and LinkedIn Ads, which integrate AI into their targeting algorithms.
In fact, leading companies such as Salesforce and HubSpot have already incorporated artificial intelligence into their B2B marketing operations. In this article, we explore the most effective applications of AI in B2B and how to successfully implement it in B2B marketing strategies.
B2B marketing strategies where it makes a lot of sense to implement AI
The use of artificial intelligence in B2B marketing can be highly effective where precision and analysis are required. Here are some key areas where the use of artificial intelligence in B2B marketing has been particularly effective.
Customised dynamic price optimisation
One of the clearest benefits of artificial intelligence in B2B marketing is the ability to analyse large amounts of data in real time. In the B2B environment, where pricing is often customised and subject to multiple variables, AI enables the analysis of historical data, market trends and buying behaviour to dynamically adjust prices without manual intervention, maximising the ROI of each transaction.
By implementing dynamic, personalised pricing strategies, companies not only maximise ROI by optimising each transaction, but also increase the customer’s perception of value, which translates into increased loyalty and an increase in the number of deals closed.
Identify cross-selling and up-selling opportunities
Artificial intelligence in B2B marketing can also be useful in identifying cross-selling and up-selling opportunities. By analysing customer buying behaviour in real time, AI can identify patterns and automatically suggest complementary products or services. This capability not only optimises recommendations, but also enriches customer histories, continually improving AI’s predictive models for future actions.
Salesforce is building artificial intelligence into its platform so that companies can analyse their customers’ purchase history and behaviour. In this way, AI in B2B marketing can more accurately identify which additional services each customer might be interested in, increasing cross-sell rates by up to 20%, while enabling more personalised recommendations and generating higher customer lifetime value (CLV) over time.
Automation of responses to RFPs
Responding to B2B requests for proposals (RFPs) is often another time-consuming and manual process that requires the attention of sales teams. However, implementing artificial intelligence in B2B marketing can streamline this process in a number of ways, including the automated creation of proposals and personalised sales presentations. In this sense, the use of AI in B2B enables optimised proposals to be generated for each customer, which sales teams can then review and adjust as necessary. This not only significantly reduces the time it takes to prepare commercial proposals, but also the costs associated with manual work, allowing teams to focus on higher-value tasks.
Predictive analysis of purchasing behaviour
Using data such as content interactions, visit frequency, email clicks and web browsing, the implementation of AI in B2B allows leads to be ranked based on their level of interest and maturity.
B2B marketing teams can then prioritise those prospects with the highest potential to convert and focus their efforts on those most likely to close a sale. A concrete example is the use of platforms such as HubSpot that apply artificial intelligence in B2B marketing to analyse the digital behaviour of leads and assign them a predictive score (lead scoring), which facilitates the personalisation of campaigns and the adjustment of messages according to the stage of the sales cycle.
B2B Account-Based Marketing Optimisation through Artificial Intelligence
Artificial intelligence in B2B marketing is radically transforming Account-Based Marketing (ABM), enabling companies to scale their personalised strategies and optimise associated costs. Traditionally, ABM has required a manual, detailed and highly personalised approach for each target account. However, AI in B2B has simplified this process, particularly in the selection and segmentation of target accounts, thanks to its ability to process large volumes of data in real time and with greater accuracy.
Specialist platforms such as Demandbase and 6sense apply artificial intelligence to B2B marketing to automate dynamic segmentation and message personalisation in ABM campaigns. By continuously analysing past interactions and digital behaviour, AI automatically adjusts content, channels and delivery times to ensure each message is aligned with each account’s stage in the buying cycle. This not only increases the effectiveness of campaigns, but also significantly improves ROI by allowing companies to focus resources on high-value accounts, achieving a level of precision and relevance that would be impossible to achieve manually.
B2B use cases for Artificial Intelligence
Artificial intelligence in B2B is not only useful in the customer acquisition phase, but in Go-To-Market strategies in general. If you are particularly interested in this topic, you may want to consider the go-to-market recommendations in this other article before proceeding.
AI-powered data analysis
One of the key benefits of AI in B2B is its ability to quickly process and analyse large volumes of data. There are already companies that have used artificial intelligence in B2B marketing to analyse complex data and improve decision making in their strategies, with great results. Khoros, for example, integrates intent data from AI company 6sense. By matching this data with their own, they have been able to create fully personalised experiences for their audience, doubling the number of visitors interacting with their website pages.
Content generation with AI tools
The integration of tools such as ChatGPT into B2B marketing, particularly content creation, is redefining the way content is produced and managed at scale. These solutions enable the production of highly personalised content, tailored to the needs of each customer and stage of the sales cycle. For example, in the consideration phase, content needs to focus on highlighting solutions to specific problems, while in the decision phase, artificial intelligence in B2B marketing enables the creation of social proof and success stories that build customer trust. In turn, technologies such as ChatGPT in B2B marketing make it easier to tailor messages according to the channel being used, such as LinkedIn or personalised sales emails, optimising the impact of campaigns.
However, while the use of tools such as ChatGPT in B2B marketing offers significant benefits in terms of efficiency, there are challenges to using artificial intelligence in B2B marketing. It is important to ensure that the content generated is consistent and effective across all platforms, including omni-channel experiences. Each medium requires specific treatment, which means that despite the time savings, a robust strategy is needed to adapt content and maintain its relevance at each stage of the buying cycle.
Automating the customer experience with ChatGPT
Automating the customer experience through artificial intelligence in B2B marketing offers significant optimisation in managing interactions and workflows. Using tools such as ChatGPT in B2B marketing allows companies to create sophisticated automations that dynamically respond to customer behaviour and preferences. This includes personalising communications and managing queries in real time, significantly reducing time spent on manual tasks and improving operational efficiency.
However, effective implementation of these tools requires careful planning to avoid depersonalisation issues. It is vital to ensure that automation maintains a genuine interaction in line with the brand voice. A balanced approach between automation and human intervention maintains a rich customer experience that is aligned with business objectives and audience expectations.
An example of using AI automation in B2B marketing is Modern Sales Pro, which used AI event automation to run 176 webinars in one year, with the AI automatically adding the content to its social calendar.
Proofs of concept in the implementation of Artificial Intelligence in B2B
Before implementing artificial intelligence in B2B marketing on a large scale, it is crucial to conduct detailed proofs of concept. These tests validate the effectiveness of the proposed B2B AI tool before full deployment, optimise the B2B marketing strategy and ensure that the integration of B2B AI is effective and aligned with business objectives.
This systematic approach ensures that the implemented B2B marketing AI solution not only meets the current needs of the business, but also delivers tangible long-term value.
Future of Artificial Intelligence in B2B Marketing
The state of adoption of artificial intelligence in B2B marketing presents both technical and human challenges. While its adoption is booming, its implementation requires not only the right infrastructure, but also a deep understanding of its capabilities and limitations in the B2B environment.
Current challenges and limitations of AI in B2B marketing
One of the main barriers to AI adoption in B2B marketing is resistance to organisational change. This phenomenon is particularly common in companies with less dynamic structures, where digital transformation involves restructuring workflows and training teams to integrate AI-based solutions.
On the other hand, some experts argue that AI can limit innovation. As Jessica Apotheker, global chief marketing officer at BCG, points out in her TED Talk, by relying on historical data, AI can limit the emergence of disruptive ideas and generate a predefined solution framework that, if not combined with human intervention, could stagnate creativity. This is a particularly relevant challenge in B2B marketing, where differentiation and personalisation play a key role in customer acquisition.
Future innovations and the role of AI in the evolution of B2B marketing
Despite the challenges, the future of AI in B2B marketing is extremely promising. The technological innovations on the horizon will profoundly change the way businesses operate. Here are some of the key innovations that will shape the evolution of the industry:
- Explainable AI: One of the big demands from the industry is transparency around the models that AI works on. Much more will be done to break down and make transparent the processes and outcomes of complex algorithms that often operate as “black boxes”, without users or developers being able to clearly understand how decisions are made. This will be particularly important in sectors where transparency and trust are critical, such as medicine and finance. This will make it easier to identify biases and ensure that decisions based on these models are ethically justifiable.
- Integration with Internet of Things (IoT) systems: The convergence of AI and IoT will transform B2B marketing by enabling more accurate, real-time data collection. This will drive the development of marketing strategies based on product usage data, optimising both customer service and offer personalisation.
- Real-time hyper-personalisation: The ability to deliver personalised, real-time experiences will be a key differentiator. Thanks to AI, companies will be able to tailor their communication and content to the specific needs of each customer in real time, significantly improving the effectiveness of B2B marketing strategies and optimising ROI.
