Generative AI makes the 95/5 rule a reality for more B2B companies

Research shows that long-term brand building outperforms short-term conversion over time, but high production costs have long held many companies back from sustaining broad initiatives. The 95/5 rule highlights that only 5% of the B2B market is ready to buy right now, while 95% will make purchasing decisions down the line. With generative AI, the barrier to producing tailored content, landing pages, and campaign materials at scale is significantly lowered. This allows mid-sized organisations to afford building mental availability over time – provided the brand's core remains guided by humans.

What does the 95/5 rule mean for your marketing?

The 95/5 rule was formulated by John Dawes at the Ehrenberg-Bass Institute and widely shared via the LinkedIn B2B Institute. The core of the model is simple: at any given moment, roughly 95% of your future B2B customers are not ready to buy. Only 5% are actively searching for a vendor or solution today.

Performance-based campaigns primarily capture those 5% who have already decided to take action. For the remaining 95%, the winners are the brands that are already familiar and top-of-mind when a need finally arises – a concept researcher Byron Sharp calls mental availability.

In their studies for the IPA, researchers Les Binet and Peter Field demonstrated that allocating around 60% of marketing budgets to long-term brand building and 40% to short-term activation delivers the strongest overall impact and highest ROI over time.

The capacity gap that has held mid-sized companies back

For many organisations, the challenge has rarely been a lack of strategic insight, but limited production capacity.

Long-term brand building requires a consistent presence over time, localisations, format variations, and continuous content output. For market-leading enterprises, these volumes are manageable. For mid-sized businesses, the math has often fallen short because production costs become too steep relative to the slower payback period. As a result, budgets have tilted towards quick, measurable clicks over long-term reach.

How AI lowers the production barrier in practice

This is where generative AI changes the playing field. AI does not replace strategic height or creative originality, but it removes friction across the production workflow. Reports like McKinsey’s State of AI show that marketing teams see some of their greatest productivity gains in content creation and creative asset production.

In our client projects, we as digital consultants see how production cycles are shortened in several practical ways:

• Landing pages in more variations: Pages and campaign assets can be structured and rolled out significantly faster with modern development and CMS tools.

• Parallel copy production: Messaging for different segments, target audiences, and channels can be generated and tested in parallel rather than sequentially.

• Continuous A/B testing: Optimising headlines, layouts, and user flows moves from being major one-off initiatives to an integrated part of ongoing operations.

• Efficient localisation: Adapting campaign material for new languages and local markets requires far less manual intervention.

• With well-structured processes, the same marketing budget suddenly covers a much broader footprint, making the 60/40 allocation achievable for more organisations.

The trap of confusing volume with impact

When production costs drop, it is easy to assume that more content automatically leads to better outcomes. However, flooding channels with generic material rarely builds trust.

Research from Ehrenberg-Bass clearly shows that mental availability is built through distinctive brand assets and consistency over time. Scaling up production with standard AI output without human oversight risks diluting what makes the brand unique. Audiences quickly learn to filter out generic content.

Five principles for a sustainable content strategy

To combine the scalability of AI technology with the 95/5 rule’s demand for lasting recognition, we recommend the following principles:

1. Humans guide strategy and brand voice

What makes a brand distinct – positioning, tone of voice, and core values – cannot be handed over to algorithms. The strategic foundation demands human judgement.

2. AI is used for breadth and iteration

Let AI handle format adaptations, translations, metadata, and variations, while creative teams focus on the central concept and original ideas.

3. Cross-functional collaboration across disciplines

As the pace of production increases, strategy, design, development, content, and analytics must collaborate closely. Well-structured design systems, clear frameworks, and modern publishing platforms ensure teams build lasting value without accumulating technical debt or administrative cleanup.

4. Measurement that balances short- and long-term goals

Complement short-term click and conversion metrics with tracking for brand awareness, share of search, and reach among the 95% who are not in the market right now.

5. Consistency over sheer volume

Establish clear guidelines for your visual and verbal identity before accelerating production. It is far easier to set the right direction from the start than to tidy up a fragmented digital presence later on.

Building smart, automated workflows is fundamentally about freeing up time for work that creates genuine value. When we mapped requirements and built an AI-assisted internal editorial tool for Skånes Folkblad, the goal was precisely to reduce manual administration and give the newsroom more time for high-quality journalism.