AI-driven personalisation: 9 key tactics for B2B marketers to boost campaign success

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As a CMO who works with numerous forward-thinking B2B tech firms, I understand firsthand the importance of personalisation in today’s marketing landscape. With so much competition vying for the attention of potential customers, businesses must find new and innovative ways to engage with their target audience. 

That’s where AI-driven personalisation comes in. By leveraging the power of artificial intelligence, marketers can create tailored experiences for individual customers that resonate with their unique needs, preferences, and behaviour. With advanced algorithms and data analysis tools at our disposal, businesses can gain a deep understanding of their audience and create personalised content and campaigns that truly connect. 

For B2B marketers, adopting AI-powered personalisation can be a game changer. By delivering highly relevant content to their audience, businesses can increase engagement, build stronger relationships, and boost the effectiveness of their marketing campaigns.

In this blog, I will delve into nine key tactics B2B marketers can use to leverage AI-powered personalisation in their marketing efforts. From data collection and analysis to personalised email marketing and chatbots, I will share practical tools and techniques to help businesses create compelling, personalised marketing campaigns that drive results.

1. Data collection

At the heart of AI-driven personalisation is data collection. For personalised marketing to be effective, businesses must collect pertinent data from various sources, such as customer relationship management (CRM) systems, social media platforms, web analytics, and email marketing tools. For example, marketers can identify customer behaviour and preference patterns by collecting and analysing this data, forming the basis for personalised campaigns.

The significance of data collection lies in its ability to provide businesses with a holistic view of their customers. Marketers can gain valuable insights into customers’ preferences and behaviour by leveraging data analysis tools and algorithms. As a result of collecting and analysing data, businesses can create highly-targeted and personalised campaigns that directly address their audience’s interests, leading to increased engagement and conversions.

Several tools and platforms can help businesses collect data, including Google Analytics, Adobe Analytics, Salesforce, HubSpot CRM, Hootsuite, and Mailchimp. These tools allow businesses to track website traffic, social media engagement, email open rates, and other relevant metrics. 

2. Data integration and analysis

Data integration and analysis play a crucial role in AI-driven personalisation, helping marketers gain deeper insights into their target audience. This process involves combining and analysing data from multiple sources, such as CRM systems, social media, web analytics, and email marketing platforms, to identify patterns and uncover valuable insights. By leveraging AI algorithms, marketers can make sense of the vast amounts of data they collect, gaining valuable insights into customer behaviour, preferences, and pain points.

To automate and streamline this process, marketers can use data integration and analysis tools such as Microsoft Power BI, Tableau, Google Data Studio, IBM Watson Analytics, and Domo. These tools help to save time and effort while enabling marketers to create interactive dashboards and visualisations that make it easier to identify trends and patterns in data. By leveraging these insights, marketers can refine their campaigns, personalise their messaging, and improve their overall performance.

By leveraging AI algorithms to integrate and analyse data, B2B marketers gain a competitive edge and can gain a deep understanding of their customer’s needs and preferences. With this insight, they can deliver personalised experiences that drive better results, build stronger customer relationships, and make data-driven decisions that maximise their marketing ROI.

3. Customer segmentation

Customer segmentation is a fundamental step in creating effective marketing campaigns. Dividing customers into groups based on their characteristics and behaviour allows marketers to tailor their messaging to each group’s specific needs and preferences. The traditional manual segmentation process can be time-consuming and imprecise, but AI-powered tools can significantly improve the accuracy and efficiency of this process. 

AI algorithms can analyse vast amounts of data, including demographics, past purchases, and online behaviour, to identify patterns and trends that can inform segmentation. This analysis can help marketers create more nuanced customer segments and identify new opportunities for engagement. AI-driven tools such as HubSpot Marketing Hub, Adobe Experience Platform, Salesforce Einstein, Optimizely, and Marketo provide advanced analytics and segmentation capabilities, enabling marketers to create targeted campaigns that deliver the right message to the right customer at the right time.

Businesses can improve their marketing efforts and customer satisfaction by leveraging AI-driven tools for customer segmentation. Personalised campaigns that speak directly to customers’ needs and preferences result in more engaged audiences and better conversion rates.

4. Content creation

Marketers can create tailored and targeted content that resonates with each segment’s specific needs and preferences by leveraging the data collected and analysed in the previous stages of AI-enabled personalisation. Various content types, such as emails, landing pages, social media posts, and product recommendations, can be used to achieve this. Additionally, AI-enabled content creation tools can help marketers develop and execute personalised content at scale. These tools use machine learning algorithms to analyse customer data and identify the most relevant and engaging content for each individual. They can also help create and deliver personalised content across multiple channels, saving time and effort for marketers.

For instance, HubSpot Email Marketing is a popular AI-enabled content creation tool that enables marketers to send personalised emails to their target audience. The tool leverages data-driven insights to personalise subject lines, images, and content based on the recipient’s preferences and behaviour. Similarly, Salesforce Marketing Cloud offers advanced content creation and delivery capabilities, allowing marketers to create and deliver personalised content across multiple channels, including email, social media, and mobile.

By leveraging AI-driven content creation tools, marketers can create personalised content that resonates with their audience and drives engagement, ultimately leading to better customer experiences and higher conversions. As a result, businesses can increase customer satisfaction, boost brand loyalty and advocacy, and achieve long-term success.

5. Personalised email marketing

Personalised email marketing has become a crucial aspect of modern marketing strategies. In the past, email marketing was more of a one-size-fits-all approach, but with AI-driven personalisation, marketers can create more targeted and relevant content for each recipient. AI can optimise email marketing campaigns by analysing recipient behaviour, preferences, and past interactions with the brand. Personalising subject lines, content, and send times using this information can result in higher open and click-through rates, ultimately leading to increased engagement and conversions. 

One significant advantage of using AI for email marketing is identifying the best time to send emails to each recipient. By analysing past behaviour, AI algorithms can determine when the recipient will most likely engage with the email and optimise the send time accordingly. This precision improves deliverability and ensures that the recipient sees the email at the most opportune moment.

Tools such as Mailchimp, Campaign Monitor, and HubSpot Email Marketing use AI to provide personalised email marketing services. These tools analyse data and use algorithms to create personalised content for each recipient, resulting in more effective and efficient email marketing campaigns.

6. Chatbots and conversational AI

Chatbots and conversational AI have modernised how businesses provide customer support and engage with potential clients. By implementing AI-powered chatbots, businesses can offer tailored experiences to customers, answer questions, provide product recommendations, and even qualify leads.

One of the primary benefits of using chatbots and conversational AI is the immediate support they provide 24/7, without human intervention. Customers can get the help they need, regardless of the time of day or the business’s operating hours. Additionally, chatbots and conversational AI can collect data on customer interactions and use it to improve their responses over time, resulting in a better customer experience.

A wide range of tools are available for implementing chatbots and conversational AI, including Drift, Intercom, MobileMonkey, Ada, and Bold360. These tools can help businesses create chatbots that integrate with their website, social media, or messaging platforms, providing a seamless customer experience. Some of these tools even offer natural language processing capabilities, enabling chatbots to understand and respond to customers’ messages more effectively and in a more human-like way.

7. Predictive analytics

Using advanced algorithms and data analysis, marketers can predict future customer behaviour and make informed decisions about engaging with potential clients. These insights can be a game-changer for B2B marketers, allowing them to tailor their messaging and offerings to each customer’s specific needs.

One of the key benefits of predictive analytics is that it allows marketers to be proactive rather than reactive. Instead of waiting for customers to take action, predictive analytics can help identify potential customers and engage with them before they even know they need a product or service. By anticipating customer needs, B2B marketers can stay ahead of the curve and create a competitive advantage.

Several tools are available for predictive analytics, including EverString and Lattice Engines. These tools use machine learning and other AI-driven techniques to analyse customer data and provide insights into their behaviour. Other tools include Infer, 6sense, and Radius for lead scoring, account-based marketing, and other predictive analytics applications.

8. A/B testing

A/B testing, or split testing, involves comparing two different versions of an element in a marketing campaign, such as a subject line or a call-to-action, to see which performs better. A/B testing can help marketers identify the most effective personalisation strategies and improve campaign performance.

AI can automate and optimise the A/B testing process, allowing marketers to identify the most effective strategies for personalisation quickly. For example, AI-enabled tools can automatically adjust the elements being tested based on user behaviour, such as changing the colour of a button if it’s not performing well.

AI for A/B testing can also help identify customer behaviour patterns to personalise marketing campaigns further. For example, if a certain segment of customers consistently responds better to a particular type of content or offer, AI can identify this pattern and enable marketers to tailor their messaging accordingly.

Many tools are available for A/B testing, including Optimizely, VWO, Google Optimize, AB Tasty, and Adobe Target. These tools use AI algorithms to analyse data and provide insights that optimise personalised marketing campaigns for better results.

9. Continuous learning and improvement

Continuous learning and improvement are essential for ensuring the effectiveness of AI-driven personalisation strategies. By monitoring the performance of these strategies, marketers can identify areas for improvement and adjust their approach accordingly. This process involves regularly reviewing data and updating AI models to accurately reflect changing customer needs and behaviours.

Tools such as Google Analytics, Adobe Analytics, Mixpanel, Amplitude, and Heap can help marketers monitor and analyse data to identify trends and patterns. Marketers can then use this information to refine personalisation strategies and improve campaign performance. For example, if a certain type of personalised content consistently performs well with a particular customer segment, marketers can adjust their strategy to create more content tailored to that segment’s preferences.

In addition to monitoring and adjusting personalisation strategies, keeping AI models up to date is vital. As customer behaviours and preferences change, AI models may become less accurate. By regularly updating these models, marketers can ensure they remain effective and continue to deliver the best possible results.


AI-enabled personalisation has become a must-have for B2B marketers who want to deliver the right message to the right person at the right time. The key tactics for successful AI-enabled personalisation include data integration and analysis, customer segmentation, content creation, personalised email marketing, chatbots and conversational AI, predictive analytics, A/B testing, and continuous learning and improvement.

By integrating these tactics into their marketing strategies, B2B marketers can drive better results and improve customer engagement. For example, AI-driven personalisation can help marketers identify customer needs and preferences, create relevant content, and deliver personalised experiences that resonate with customers.

It is crucial to remember that AI-driven personalisation is not a one-time effort. Continuously monitoring and adjusting the AI-driven personalisation strategies is necessary to ensure they remain accurate and effective. The tools discussed in this blog can help marketers continually learn and improve their personalisation efforts.

B2B marketers must embrace AI-driven personalisation to stay competitive in today’s market. The benefits are clear, and the tools are readily available. By implementing these tactics, B2B marketers can improve their campaigns, drive better results, and create a more engaging customer experience.

Optimise B2B marketing with AI-driven personalisation from Resonate

If you are curious about AI but are unsure how it can help your marketing efforts, please get in touch. At Resonate, we specialise in AI-driven personalisation, offering tailored solutions that help businesses engage with their customers more effectively. 

Our team leverage the latest AI algorithms and data analysis tools to create highly targeted and personalised campaigns that drive results. From data collection and analysis to customer segmentation and content creation, we deliver bespoke marketing solutions that help businesses build stronger customer relationships and increase revenue. Let’s discuss how we can help your business stand out in today’s rapidly-evolving marketing landscape.

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Girish is the CMO & Co-Founder of Resonate.

GV is our Marketing and Delivery head. He keeps our clients’ marketing strategy on track and leads the Resonate team to deliver commercial outcomes.

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