Fractional CMO: Fixing Marketing Systems Built for Yesterday’s Buyer

Date : September 30, 2026 By Andrei Iunisov

Most companies do not need a fractional CMO because they are missing another senior marketer. They need one because the way their customers buy has changed faster than the way their marketing works. Let me explain what I mean.

A few years ago, the typical B2B journey was relatively easy to understand. A potential customer searched Google, visited several vendor websites, downloaded content, spoke to sales and gradually built a shortlist. That journey is becoming much less visible. Buyers can now research a problem through ChatGPT or another AI platform, compare vendors without visiting their websites, read online community discussions and reviews, watch product demonstrations, check G2 and other review platforms, ask colleagues and arrive at a vendor website already knowing much of what the company would normally try to explain. In some cases, the website visit happens close to the end of the research process rather than at the beginning.

But many marketing organisations still operate as if nothing has changed. SEO teams optimise for rankings and traffic. Paid media teams optimise for leads. Content teams publish against keyword calendars. Agencies report on their own channel performance. Sales waits for qualified opportunities. Each part may be working reasonably well on its own, while the overall marketing system is becoming disconnected from the way buyers actually make decisions.

This is where I see the fractional CMO role becoming particularly useful. The job is not simply to supervise marketing activities or produce another strategy document. It is to understand how customers are discovering, evaluating and selecting vendors now in 2026, after AI discovery has arrived, identify where the existing marketing system no longer matches that behaviour, and decide what should change.

That can mean changing positioning, reallocating budgets, fixing measurement, improving sales and marketing alignment, changing the content strategy, building visibility in AI-generated answers or simply stopping activities that continue to produce metrics but no meaningful commercial impact. The problem fractional CMOs address here is the distance between how customers actually buy and how a company’s marketing organisation assumes they buy. The wider that gap becomes, the easier it is to spend more on marketing while understanding less about what is really driving the pipeline.

What Does a Fractional CMO Actually Do?

A fractional CMO provides senior marketing leadership without joining the company as a full-time executive. But the useful part of the role is not the title. It is the ability to look across the whole marketing system rather than optimise one channel in isolation. A good fractional CMO should be able to answer questions such as:

• Where is the pipeline actually coming from?
• Which marketing activities influence revenue, and which mainly produce reporting metrics?
• How has the buyer journey changed?
• Where are prospects researching the company before they speak to sales?
• Are positioning and messaging still relevant to the way customers evaluate vendors?
• Which channels deserve more investment, and which should be reduced or stopped?
• Are marketing, sales and external agencies working towards the same commercial outcome?
• Can management trust the attribution and reporting being used to make budget decisions?

The role can include positioning, demand generation, paid acquisition, SEO, AI visibility, content strategy, analytics, CRM, sales alignment and agency management. But these are tools, not the objective. The objective is to identify the biggest constraints on marketing performance and make sure the different parts of the system work together to produce pipeline and revenue.

This is also what separates a fractional CMO from hiring another specialist. An SEO consultant will normally look for ways to improve organic search. A paid media agency will look for ways to improve advertising. A content agency will suggest more or better content. Those recommendations may all be valid. But sometimes the right decision is to reduce SEO investment, stop a campaign, change the offer, rebuild attribution, replace an agency or move budget into an entirely different part of the buyer journey. Someone needs to make that decision without being commercially dependent on one particular channel. That is the role I see a fractional CMO playing.

The Buyer–Marketing Gap

The idea behind this framework is inspired by Duane Forrester’s excellent article, “AI Changed Your Buyer Faster Than Your Business Can Adapt.”

The central argument in this post is simple: AI has changed the behaviour of buyers much faster than most companies have changed the systems designed to market and sell to them. Buyers can now compress hours or days of research into minutes, while businesses still change messaging, budgets, content priorities and measurement through quarterly or annual planning cycles.

I think this creates a broader marketing problem that is useful to describe as the Buyer-Marketing Gap. This gap is the distance between how customers actually discover, research and evaluate a company and how the company’s marketing organisation assumes that process works. That gap is becoming visible in several places.

1. The knowledge gap

Buyers increasingly arrive much further into the decision-making process. They may already understand the category, know the major vendors, have compared features and pricing, read user discussions and identified potential weaknesses before they ever speak to sales. Duane describes this as the company no longer being the first conversation. Research, comparison and narrowing may already have happened before the prospect reaches the website. Yet many companies still start every interaction from the beginning. Landing pages explain what the category is. Nurture sequences send introductory material. Discovery calls repeat information the prospect already found elsewhere. The content may be correct, but it is being delivered at the wrong stage of the buyer’s thinking.

2. The discovery gap

The company also has less control over where a shortlist is created. A traditional search journey might expose a buyer to ten vendors across several pages of search results. An AI-generated answer may reduce the same market to three or four names. As Duane points out, the shortlist can now be written somewhere else, using evidence the company does not directly control. That evidence may include:

• third-party reviews;
• industry publications;
• professional communities;
• YouTube;
• comparison sites;
• documentation;
• customer discussions;
• citations from other authoritative sources.

This creates a different marketing question. It is no longer enough to ask:

How do we rank for this query?

Companies increasingly also need to ask:

What evidence makes us part of the answer when a buyer asks an AI system which vendors belong in this category?

3. The content gap

Content is increasingly doing useful work even when nobody clicks on it. Duane makes an important point here: a page can be read, interpreted and incorporated into an AI-generated answer without receiving a visit. In that case, the content still influenced the research process, but conventional analytics may record nothing. This changes what content needs to do. I increasingly think of B2B content as having three separate jobs:

Role	What the content needs to achieve
Acquire	Bring the right audience through search, advertising or distribution
Convince	Give a human buyer evidence that changes or reinforces a decision
Inform machines	Give AI and search systems clear, structured and credible evidence about the company

A content strategy built only around traffic can therefore miss part of its real value. At the same time, this does not mean every page suddenly becomes valuable because an AI system might read it. Content still needs a clear purpose, credible information and a connection to the buying decision.

4. The measurement gap

The next problem is attribution.

A prospect might:

ask ChatGPT → read Reddit → watch YouTube → check G2 → search the brand → visit the website → request a demo

Analytics may record only:

Google → website → demo

The rest of the buying journey effectively disappears. This is why I am increasingly cautious when management asks questions such as:

How much pipeline did AI traffic generate?

The question is understandable, but it assumes AI behaves like another referral channel. It often does not. A better set of questions can be:

• Are we present in the answers buyers are likely to see?
• How are we being described?
• Which sources are being used as evidence?
• Are buyers reaching sales with knowledge or assumptions that came from those sources?
• Is branded demand changing?
• Are opportunity patterns changing even when referral traffic is not?

Traditional attribution remains useful, but it simply cannot explain the entire decision anymore.

5. The operating gap

Finally, buyers and companies now move at very different speeds. A buyer can adopt a new research behaviour almost instantly. They open ChatGPT, Claude, Gemini or another tool and start using it. A company cannot adapt that quickly. Changing the business may require:

• new budget;
• management approval;
• agency changes;
• new content;
• technical implementation;
• revised KPIs;
• changes to sales processes;
• changes to reporting.

Duane describes this as the fundamental asymmetry: buyers adapt at the pace of software, while businesses adapt at the pace of planning cycles. This may be the most important gap of all. Because even a company that correctly understands what is changing can still spend a year discussing ownership, tooling and measurement while buyer behaviour continues to move.

These five gaps are connected. A company may have strong SEO, good advertising, capable agencies and a healthy content calendar, yet still struggle because the individual parts were designed around assumptions about the buyer journey that are becoming outdated. This is why I see the fractional CMO role less as managing a collection of marketing channels and more as identifying where these gaps are appearing and deciding what the organisation should change first. The goal is not to rebuild marketing every time a new platform appears. It is to make the marketing system adaptable enough that the business does not remain permanently one planning cycle behind its customers.

How I Run a Fractional CMO Engagement

I do not start a fractional CMO engagement by producing a long strategy document or adding more marketing activity. I start by understanding where the current marketing system is breaking.

Assessment

The first stage is a structured review of the existing setup: positioning, acquisition channels, content, analytics, CRM, sales process, agencies and current reporting. The goal is not to audit everything for the sake of it. It is to identify the few issues that are having the biggest impact on pipeline. Sometimes the problem is weak positioning. Sometimes paid acquisition is inefficient. Sometimes traffic is healthy but conversion is poor. Sometimes the company is generating leads but cannot explain which sources create real opportunities. In other cases, the buyer journey has changed while the marketing strategy has not. The output is a clear view of what should be fixed first, what can wait and what should probably be stopped.

90-Day Roadmap

I normally work in 90-day cycles rather than annual marketing plans. The roadmap focuses on a limited number of priorities that can materially improve performance within that period. That might include changing campaign structure, rebuilding a landing page, fixing attribution, improving bottom-of-funnel content, testing new acquisition channels, changing positioning or improving visibility in AI-generated research. The important part is prioritisation. A marketing team can easily generate twenty good ideas. The harder job is deciding which three or four are worth doing now.

Execution Oversight

I can work with an existing internal team, agencies and specialist contractors rather than replacing them. My role is to make sure that individual activities support the same commercial objective. That includes writing briefs, reviewing campaigns and content, challenging agency recommendations, helping teams resolve priorities and making sure execution does not gradually drift away from the original strategy. I can also step directly into execution where it makes sense, particularly in areas such as paid acquisition, SEO, AI visibility, analytics and demand generation.

Measurement

The next step is to establish whether the changes are actually improving the business. I try to move measurement away from isolated channel metrics and toward pipeline. Traffic, rankings, impressions, CPL and conversion rates are still useful, but they need to be connected to opportunities and revenue wherever possible. This is particularly important when several channels influence the same buyer journey and conventional attribution only shows part of what happened.

Reallocation

The final stage is not reporting. It is deciding what to change next. Every cycle should answer a few basic questions: what worked, what did not, what did we learn and where should the next unit of budget or effort go? That may mean increasing investment in a successful channel. It may also mean reducing spend, stopping an agency programme or abandoning an idea that looked good three months earlier. A fractional CMO should not be paid to defend the existing marketing plan. The job is to keep reallocating resources toward the activities that are most likely to improve pipeline.

Where I Have Applied This

The problems I work on are usually different on the surface, but they often come back to the same question: where is marketing activity becoming disconnected from commercial results?

Enterprise software: from more leads to better pipeline

At one enterprise software company, lead generation grew from a few hundred inbound leads per year to several thousand. At that point, the problem was no longer simply how to generate more demand. The more useful question became which lead types were actually turning into opportunities and revenue.

We started looking more closely at the difference between high-volume lead sources and commercially valuable ones. Some channels generated large numbers of conversions but relatively little pipeline. Others produced fewer leads but a much stronger opportunity rate. That changed the discussion from:

How do we increase leads?

to:

Which types of demand are worth generating more of?

This is the kind of shift I expect from a fractional CMO engagement. Once volume is no longer the primary constraint, the marketing system has to optimise for quality, sales progression and revenue rather than simply producing larger numbers at the top of the funnel.

Local services: when analytics did not match the business

For a consumer services business, marketing dashboards initially suggested one version of performance while the actual booking system showed another. Website analytics underreported transactions and revenue, which made campaign performance difficult to interpret correctly. The immediate temptation would have been to optimise advertising based on the numbers available in the analytics platform.

Instead, we compared advertising data, website analytics and the booking system to understand where the measurement was breaking. That changed the priority. Before making major budget decisions, the business needed a more reliable view of actual bookings and revenue. This is a common marketing problem: the dashboard can look precise while the underlying measurement is incomplete. Improving the campaigns before fixing that problem can simply mean optimising against the wrong signal.

B2B SaaS: AI visibility was not following traditional SEO assumptions

For several B2B software companies, I have also been analysing how their brands and content appear in AI-generated answers. One useful finding was that AI systems were not necessarily citing the pages we would traditionally expect to perform best. Generic listicles were often absent. More specific educational resources, product-related guides and authoritative third-party sources appeared much more frequently. In some cases, commercially important pages had very little AI visibility while external publications, review platforms and competitors were shaping the answer instead.

That led to a different content question. Rather than simply asking which new articles should be published, we started asking which existing pages could provide stronger evidence, which third-party sources mattered, what information AI systems were actually citing and where the company needed more external authority. This is a good example of the Buyer–Marketing Gap in practice. The company can have a functioning SEO programme while the way buyers discover and compare vendors is already moving beyond conventional search results.

The common pattern

These situations look very different: enterprise software, local services and B2B SaaS. But the underlying approach is the same. I try to find the point where the current marketing system is giving management the wrong signal, optimising the wrong metric or continuing to operate on an assumption that is no longer true. That is usually where the biggest opportunity for improvement starts.

Fractional CMO vs Full-Time CMO

A fractional CMO is not simply a cheaper version of a full-time CMO. The difference is usually more about stage, scope and operating model. A full-time CMO makes sense when the company needs permanent executive ownership of marketing, has a large enough team to manage and expects that person to spend substantial time on internal leadership, hiring, budgeting and cross-functional management.

A fractional CMO is often a better fit when the company needs senior marketing judgement but does not yet need that role five days a week. That may be because the business is in a transition period, the existing team needs stronger direction, several agencies need coordination, marketing performance has stalled, or management needs an experienced person to diagnose what should change before committing to a larger permanent structure.

	Fractional CMO	Full-Time CMO
Time commitment	Part-time	Full-time
Typical focus	Diagnosis, priorities, change	Ongoing executive ownership
Best fit	Transition, growth problems, restructuring	Established marketing organisation
Execution model	Works with existing teams and agencies	Builds and manages internal function
Commitment	Flexible	Long-term employment

The cost difference can be significant, but I do not think cost should be the main reason to choose the fractional model. The bigger advantage is flexibility. A company can bring in senior marketing experience to solve a specific growth problem, improve the existing system and determine what kind of long-term leadership or team structure is actually required. In some cases, the correct outcome of a fractional engagement is eventually hiring a full-time CMO. In others, the company may discover that it does not need another executive at all. It may need better measurement, clearer positioning, stronger channel management or a different mix of specialists.

When You Probably Don’t Need a Fractional CMO

Not every company needs a fractional CMO.

If your positioning is clear, acquisition channels are performing, marketing and sales agree on what a qualified opportunity looks like, reporting is reliable and someone senior already owns the entire buyer journey, adding another layer of marketing leadership may not solve anything. You may also not need a fractional CMO if the main constraint is simply execution capacity. If the strategy is already clear and the problem is that you need more campaigns launched, more content produced or more sales development activity, a strong specialist or additional internal resource may be the better answer. The same applies when marketing is too small to require senior coordination. If there is one channel, one person and a straightforward route to market, the business may be better served by a specialist who can improve that specific area.

I would normally consider a fractional CMO when the problem is more structural: performance has stalled, different teams are pulling in different directions, management does not trust the numbers, agencies are optimising their own channels in isolation, or the company knows marketing needs to change but is not yet clear what should change first. In other words, the role becomes useful when the problem is not a lack of activity. It is a lack of clarity about where the next meaningful improvement should come from.

When a Fractional CMO Is Useful

A fractional CMO is most useful when the company is already doing marketing, but the system is no longer producing enough clarity or growth. That often happens when activity has expanded faster than coordination. There may be several channels, agencies and internal stakeholders, but no single person looking across the whole buyer journey and deciding what matters most.

It can also happen when performance has stalled. Traffic may be growing while pipeline is flat. Lead volume may be healthy while opportunity quality is falling. Paid media may still generate conversions, but management is no longer confident that those conversions are commercially valuable.

In other cases, the issue is change.

Buyer behaviour may be moving faster than the marketing organisation. AI-assisted research, new discovery channels, changing attribution patterns and different expectations from sales can make an existing strategy less effective even when the individual channels still appear to be working.

This is usually where I can add the most value. The role is to identify the biggest constraint, set priorities, align internal teams and external partners, and keep reallocating effort toward what is most likely to improve pipeline. A fractional CMO is therefore not primarily an additional pair of hands. It is useful when the business needs someone to decide where those hands should be working.

If you are considering fractional CMO support, I can start with a focused assessment of your current marketing setup and the main constraints affecting pipeline.