The marketing industry has a productivity problem

There is a curious feature of modern marketing. Almost every innovation promises to make it easier. Yet the work itself seems to become more complicated.

Consider the marketing department of a reasonably successful B2B company. It has a sophisticated CRM, an automation platform, analytics software, a content management system, social publishing tools, advertising accounts and perhaps a growing collection of AI applications.

Each system, considered individually, is impressive. The CRM remembers customers. The analytics platform measures behaviour. The automation system sends communications. The content tools produce material. The advertising platforms find audiences.

Yet someone still has to decide what all these systems should do together.

That someone is usually a person surrounded by spreadsheets, dashboards, meetings and competing priorities.

The tools have become more intelligent. The marketing operation, as a whole, often hasn't.

The paradox of marketing productivity

Marketing has become exceptionally good at measuring and organising activity.

We can tell you how many emails were delivered, how many people clicked an advertisement, which pages attracted attention and how many contacts entered a campaign.

What remains surprisingly difficult is answering a more important question: what should we do next to win more customers?

The industry has largely approached this problem by adding more tools.

Need more leads? Introduce prospecting software.

Need better content? Add a content production platform.

Need more conversions? Deploy another optimisation product.

Need better reporting? Buy a dashboard.

Each purchase is perfectly rational in isolation. Collectively, they can create an operation that spends much of its time coordinating its own machinery.

It is rather like an orchestra in which every musician has become technically brilliant, but no one is listening to the others.

The problem isn't that any individual instrument is inadequate. It is that technical excellence does not automatically produce harmony.

The missing intelligence

A customer's journey rarely conforms to the neat sequence imagined by marketing software.

Someone might discover a company through an AI answer, read three articles, disappear for six weeks, speak to a colleague, visit a product page and then respond to an email about a different service.

Each interaction contains information. The challenge is to connect that information to a useful commercial decision.

A conventional marketing operation may record all these activities across several systems.

But recording an event and understanding its significance are two different things.

A visitor reading a technical specification might be researching an immediate purchase. They might also be writing a university essay. The page view itself tells us very little.

The relevant question is not simply what happened. It is what the available evidence suggests, how confident we should be and what response would be appropriate.

This is where artificial intelligence becomes interesting.

Not because it can write an email in seconds, although that is useful. Not because it can generate another campaign, although it can.

Its more consequential contribution is the possibility of bringing previously disconnected information together and reasoning about what to do with it.

From production to decisions

For years, marketers have been taught to think in terms of campaigns, channels and workflows.

These are means of execution. They are not commercial objectives.

A more intelligent operation starts somewhere else.

What are we trying to achieve? Which buyers matter? What do we know about their requirements? What evidence would suggest they are interested? What action might help them progress? What happened when we tried?

It then uses the appropriate channels and content to act on those decisions.

This reverses the traditional relationship between technology and strategy.

Instead of people configuring systems to execute predetermined instructions, technology helps people interpret evidence, make decisions and execute within agreed boundaries.

Human judgement remains essential. Markets are ambiguous. Commercial priorities change. Buyers are unpredictable. Brand reputation matters.

But human expertise should be concentrated on the decisions that deserve it, rather than the administration of increasingly elaborate systems.

The next productivity revolution

The great promise of AI in marketing is not that a department of ten people will suddenly produce the work of a hundred.

It is that much of the work those hundred people might have produced will no longer be necessary.

Fewer disconnected campaigns. Fewer arbitrary communications. Less content created without a clear purpose. Less time moving information between systems.

More effort directed towards identifying opportunities, understanding customers and helping buying decisions progress.

The productivity question, in other words, is not how much more marketing can we produce?

It is how much less unnecessary marketing can we do while achieving more?

That is a rather different ambition. And potentially a far more valuable one.