Scaling Enterprise ABM: Using AI to Personalize Hyper-Targeted Content

According to Accordng to McKinsey, market-leading B2B companies are four times more likely to use one-to-one personalization than their peers. The findings highlight the growing advantage of delivering content and experiences tailored to individual accounts.

For enterprise marketing teams, however, delivering that level of personalization across hundreds of target accounts presents a significant challenge. Each account has different priorities, buying committees, and content needs, making manual customization difficult to sustain as ABM programs grow.

AI is helping marketers scale these efforts by turning account intelligence into personalized content across audiences and channels. With the right company context and AI-powered workflows, teams can deliver more relevant campaigns without the production demands traditionally associated with hyper-targeted ABM.

Here's how to put those capabilities into practice.

Key takeaways

• AI helps enterprise marketers scale ABM personalization across target accounts, industries, and buying groups.
• Combining account intelligence with AI-powered content workflows enables more relevant campaigns without proportionally increasing production demands.
• Shared company knowledge and AI agents help teams maintain accurate, consistent messaging as ABM programs grow.

Why is personalization critical to enterprise ABM?

Account-based marketing focuses resources on a defined set of high-value accounts, with campaigns tailored to their business needs and purchasing priorities.

Effective ABM requires understanding both the organization and the people involved in its buying decisions. A single account may include stakeholders evaluating different aspects of a solution, from financial impact to technical implementation.

Research reinforces the importance of addressing those shared and individual priorities. Gartner found that buying groups exposed to content relevant to their collective needs are three times more likely to report a high-quality deal.

The implication for ABM is clear: personalization should help buyers recognize how a solution addresses their organization's priorities while giving different stakeholders the information they need.

At enterprise scale, that creates substantial content demands. Teams may need to develop industry-specific campaigns, account-level messaging, and variations for different buying groups, then adapt those materials across channels.

AI makes it possible to manage that complexity more efficiently.

How AI enables hyper-targeted ABM content

AI can help marketing teams translate account intelligence into personalized content and deliver it across more touchpoints.

Turn account insights into targeted messaging

Effective personalization starts with reliable account data.

CRM records, intent signals, website engagement, and sales interactions can help marketers understand an account's priorities and identify relevant messaging opportunities.

AI can use these insights to develop content tailored to specific account segments when that information is available within the content workflow.

Consider a software company targeting organizations in healthcare and financial services. While both industries may need the same core solution, healthcare buyers could prioritize operational coordination, while financial services organizations might focus on regulatory requirements.

AI can help marketers adapt messaging to those distinct priorities while maintaining consistent product positioning.

As new insights emerge, teams can refine content and respond to changes in account engagement.

Create content that reaches the buying committee

Personalizing ABM content becomes more complicated when multiple stakeholders influence the purchasing decision.

Marketers may need to address technical requirements, financial considerations, and operational needs within the same campaign. Some assets should emphasize an individual stakeholder's priorities, while others need to communicate value across the buying group.

Jasper's Multiple Audiences capability supports this by allowing marketers to incorporate up to four audiences into a single AI generation on Business and Enterprise plans. Teams can establish a primary audience and add secondary audiences, helping Jasper identify shared priorities and create content that resonates with different decision-makers. This is particularly useful for ABM landing pages, solution briefs, and campaign assets intended to support buying group consensus.

Adapt personalized content across channels

ABM campaigns often span email, paid media, website experiences, and sales outreach. Maintaining relevant messaging across those touchpoints requires coordination. AI agents can help teams create channel-specific variations from a shared campaign brief, adapting content for different formats while preserving the underlying message. An enterprise ABM team could use a single industry campaign strategy to produce targeted email sequences, landing page copy, and supporting sales materials.

This reduces repetitive production work and makes it easier to keep campaigns aligned as they expand.

How to scale enterprise ABM with AI-powered workflows

Interest in AI-powered personalization is growing. According to Jasper's State of AI in Marketing report, 50% of marketers plan to focus on improving or increasing personalization and ABM with AI over the next 12 months. Turning that investment into effective campaigns requires more than generating additional content. Teams need repeatable workflows that connect account strategy with content execution.

1. Prioritize accounts and define audience segments

Start by identifying which accounts need the greatest level of personalization.

Use firmographic data, buying signals, and engagement history to organize accounts into meaningful segments. Strategic accounts may warrant dedicated content, while accounts with similar priorities can share industry- or use-case-specific campaigns.

Define the stakeholders involved in each segment and the information they need throughout the buying journey.

2. Establish a shared foundation of company knowledge

AI needs accurate information about the business to produce relevant content. Product positioning, approved claims, brand guidelines, and audience profiles should be available to the systems generating ABM assets.

Jasper IQ provides this shared context across content workflows. Its capabilities include Brand Voice, Audiences, Knowledge Base, and Product IQ, which helps keep product details and claims consistent. With this foundation in place, marketers can create targeted variations without repeatedly supplying the same company information or reviewing messaging from scratch.

3. Build repeatable content workflows with AI agents

Once account segments and campaign messaging are established, teams can use AI agents to support content development.

An ABM workflow might use an approved campaign brief and defined audience profiles to create industry-specific landing pages, generate email variations, and adapt content for additional stakeholders. Jasper's AI agents can draw on shared marketing context to support these workflows, helping teams maintain consistency across assets. Marketers can then review outputs for account relevance, refine the creative direction, and approve materials before distribution.

4. Measure engagement and optimize campaigns

Scaling content production is valuable only when it contributes to more effective account engagement. Track how target accounts interact with campaigns, including engagement across buying committee members, content consumption, and progression through the sales cycle. Use those insights to identify messaging gaps and refine future assets. AI can help teams update campaign content as account priorities change, making personalization an ongoing process rather than a one-time effort.

Make enterprise ABM personalization more effective with Jasper

Scaling high-touch initiatives like ABM requires more than the right tools. Human expertise remains central to success, particularly when balancing efficient content workflows with the strategic judgment and nuanced understanding of customers that effective personalization demands.

Jasper's forward-deployed engineers and marketing experts work directly with enterprise teams to strike that balance. They help design and implement AI-powered workflows tailored to each organization's needs, with the right context and governance in place to support teams as they scale.

Learn how Jasper's forward-deployed experts help enterprises build AI that knows their business.

Frequently asked questions

What is AI-powered account-based marketing?

AI-powered ABM uses artificial intelligence to personalize marketing content and campaigns for high-value accounts. It combines account insights with automated content workflows to improve relevance and scale campaign execution.

How can AI improve ABM personalization?

AI can help marketers develop messaging based on account characteristics, buyer priorities, and engagement signals. It also supports the creation of content variations for different audiences and channels.

How do AI agents support enterprise ABM?

AI agents can support repeatable content workflows, including generating targeted campaign assets, adapting messaging for buying groups, and producing channel-specific variations. Shared company knowledge helps keep outputs accurate and consistent.

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