Use Generative AI to Segment B2B Email Marketing Audiences
One of the strongest uses of AI in B2B email marketing is personalization.
But personalization is more than inserting someone’s first name into an email.
A useful B2B workflow can divide contacts according to information such as:
- Industry
- Company size
- Job role
- Location
- Previous interactions
- Products viewed
- Downloaded resources
- Sales stage
- Purchase history
- Level of engagement
This allows the same campaign to have different messaging for different audiences.
For example, a software company could create separate email messaging for a startup founder, a marketing director and an enterprise IT manager.
The underlying product may be the same.
The reason each person cares about it may be completely different.
That is where generative AI can help transform structured CRM information into more relevant variations of an email rather than forcing marketers to write every version manually.
Use AI to Research and Personalize B2B Email Messages
Research is another area where generative AI can save time.
Suppose a sales team wants to contact 200 companies.
Instead of giving AI an email address and asking it to invent something personal, provide approved business information such as:
- Company industry
- Website description
- Product category
- Known business challenge
- Prospect’s professional role
- Previous interaction with your company. AI can then help create a first draft that reflects that context.
For example:
Generic approach:
We help businesses improve their productivity. Would you like to schedule a call?
Contextual approach:
I noticed your team is expanding its customer-support operation. We work with growing companies that need to reduce repetitive support tasks without increasing headcount. Would it be useful to show you how that works?
The second message gives the recipient a reason to care.
However, marketers should verify AI-generated research before sending anything. AI should not be allowed to invent company information simply to make an email appear personalized.
Build AI-Powered B2B Email Nurture Workflows
Lead nurturing is another natural application for generative AI.
A typical workflow might look like this:
New lead → Welcome email → Educational content → Case study → Follow-up → Sales conversation
AI can help create different versions of the content at each stage while your automation platform controls when the emails are sent.
For example, someone who downloads a B2B software guide could receive:
- Email 1: Helpful introduction
- Email 2: Common problem-solving advice
- Email 3: Relevant case study
- Email 4: Product comparison or demonstration
- Email 5: Invitation to speak with sales
The important part is that the workflow should respond to behavior.
If someone clicks a product page, the next email can become more product-focused.
If they do nothing, the workflow can provide educational content instead.
Modern marketing platforms already support this type of behavior-based automation. Mailchimp’s automation tools allow businesses to trigger personalized messages based on customer data and behavior.