Marketing Technology Spend: Stop Buying Tools, Start Buying Outcomes

Marketing technology spend is the budget allocated to software, platforms, and automation systems that support how a marketing team plans, executes, and measures its work. Most organisations get the spending part right and the outcomes part completely wrong.

The problem is not how much companies spend on martech. It is what they expect in return, and how rarely they stop to check whether they are getting it.

Why Martech Buying Decisions Go Wrong Before the Contract Is Signed

I have sat in enough vendor pitches to recognise the pattern. Someone in the business has a problem, real or perceived. A vendor appears with a polished deck and a compelling demo. The procurement process begins, and somewhere between the first meeting and the signature, the original problem gets quietly replaced by the vendor’s framing of it.

By the time the contract lands, the team has committed to solving a problem defined by the people selling the solution. That is not a coincidence. It is the entire point of enterprise software sales.

The fix is not to be more sceptical of vendors. It is to be more precise about what you are trying to achieve before you speak to any of them. What specific business outcome are you trying to improve? What does success look like in twelve months? What does the data environment look like today, and what needs to change before any new platform can work? These are not procurement questions. They are strategic ones, and they should be answered before a single demo is booked.

BCG has written extensively about the talent and capability gap sitting underneath most digital marketing transformations. The technology is rarely the limiting factor. The clarity of intent almost always is.

The Vendor Selection Process Rewards the Wrong Things

When I was running an agency and we were evaluating platforms for clients, I noticed something uncomfortable. The tools that won the most RFP processes were not always the best tools. They were the ones with the most polished sales teams, the most persuasive case studies, and the most compelling pricing architecture at the point of commitment. The total cost of ownership, the integration complexity, and the support quality after go-live rarely featured prominently in the decision.

This is a structural problem. The people evaluating the software are often not the people who will use it daily. The people who will use it daily are often not consulted until after the decision is made. And the people who signed the contract are rarely the ones who have to explain, eighteen months later, why adoption is at 30% and the promised efficiencies have not materialised.

Fixing vendor selection means changing who is in the room and what questions they are allowed to ask. The IT team should not be the only ones interrogating integration requirements. The analysts who will live inside the reporting dashboards should be testing them before sign-off. The campaign managers who will build workflows should be walking through the builder, not watching a pre-configured demo flow.

If you are thinking about how automation fits into your broader marketing infrastructure, the Marketing Automation Systems hub covers the strategic and operational dimensions in more depth.

What “Unused Tool” Actually Costs You

Every marketing stack has at least one. The platform that was bought with genuine intent, onboarded with reasonable effort, and then quietly abandoned when the champion who bought it left the business, or when the use case it was supposed to serve turned out to be more complicated than the demo suggested.

The direct cost is obvious: the licence fee that keeps renewing because nobody has got around to cancelling it, or because the cancellation process is deliberately painful. But the indirect cost is larger. Unused tools create data fragmentation. They sit in the stack consuming API connections that could be used elsewhere. They appear in security audits. They confuse new team members who cannot tell whether a platform is live, deprecated, or somewhere in between.

I once inherited a martech audit at a mid-size business where the team was paying for three separate social scheduling tools simultaneously. Not because anyone had decided to use three. Because each one had been bought by a different person in a different year, and nobody had ever done a full inventory. The combined annual cost was not catastrophic. But the fragmented data, the duplicated workflows, and the time spent managing three separate login environments was a genuine drag on the team’s output.

The discipline of a quarterly tool audit is not glamorous. But it is one of the highest-return activities a marketing operations lead can run. A simple spreadsheet mapping every active licence, its owner, its monthly cost, its last login date, and its primary use case will surface waste faster than any external consultant.

The Outcome Definition Problem

Martech ROI is consistently described as a measurement problem. I think that framing is wrong, and it lets the real issue off the hook.

The measurement problem is real. Attribution across a modern marketing stack is genuinely difficult. But the reason most organisations struggle to demonstrate martech ROI is not that they cannot measure the outcomes. It is that they never defined specific, measurable outcomes at the point of purchase. They bought a platform to “improve personalisation” or “streamline campaign management” without ever specifying what improvement looked like in numbers, or what the baseline was they were improving from.

You cannot measure progress toward a goal that was never set. And you cannot hold a vendor accountable to outcomes that were never written into the commercial agreement.

The organisations that get genuine value from their martech spend tend to do one thing differently at the buying stage: they define success in advance. Not in vague directional terms, but in specific, time-bound, measurable ones. “Reduce email production time by 40% within six months.” “Increase lead-to-opportunity conversion rate from 12% to 18% by end of Q3.” These are not perfect metrics. But they create accountability, and accountability creates honest evaluation.

HubSpot has covered how AI-assisted tools can reshape customer experience outcomes, but the same principle applies: the tool only delivers if the outcome it is supposed to drive has been clearly articulated before deployment.

How Organisational Structure Shapes Martech Waste

One of the less-discussed drivers of martech overspend is organisational fragmentation. In large businesses, different teams buy different tools for overlapping purposes because there is no central visibility into what already exists. In smaller businesses, the problem runs the other way: one person makes all the buying decisions without the technical depth to evaluate integration complexity or long-term scalability.

BCG’s research on the digital marketing talent divide points to a structural tension that most organisations have not resolved: the people with the commercial authority to approve martech budgets often lack the technical fluency to evaluate what they are buying, and the people with the technical fluency often lack the commercial authority to shape the decision.

The answer is not to centralise all martech decisions into a single function. That creates bottlenecks and removes the contextual knowledge that individual teams bring to their own tool needs. The answer is to create a lightweight governance framework: a shared inventory, a defined evaluation process, and a named owner for every platform in the stack. Not bureaucracy for its own sake. Just enough structure to prevent the same mistake from being made four times in four different teams.

When I was scaling an agency from around twenty people to over a hundred, the martech decisions that aged well were the ones made with a clear view of where the business was going, not just where it was. The ones that created problems were the ones made reactively, in response to a specific short-term need, without considering how the tool would sit in the stack twelve months later.

The Hidden Cost of Switching Costs

Vendors understand switching costs better than their customers do. The longer a platform is embedded in your operations, the more expensive it becomes to leave. Data is stored in proprietary formats. Workflows are built around the platform’s specific logic. Integrations with other tools in the stack depend on it being there. The team has invested time in learning it.

This is not accidental. It is the commercial architecture of enterprise software. The best vendors make their platforms genuinely indispensable. The less scrupulous ones make them artificially difficult to leave.

The practical implication is that the buying decision carries far more weight than most organisations give it. A platform you choose today will likely still be in your stack in five years, not because it is the best option available at that point, but because the cost and disruption of switching will always seem higher than the cost of staying. That asymmetry should make every initial evaluation more rigorous, not less.

Three questions worth asking before any significant martech commitment: What does data export look like if we need to leave? What happens to our workflows if this vendor is acquired or shuts down? And what is the realistic cost of migration in two years if this does not work out?

For smaller businesses evaluating their options, Vidyard’s breakdown of martech priorities for smaller teams is a useful reference point for thinking about proportionality in tool selection.

Where Consolidation Creates Real Efficiency

There is a version of martech consolidation that is just cost-cutting dressed up as strategy. Fewer tools, lower spend, done. That version usually creates new problems: capability gaps, team frustration, and a stack that cannot support the marketing function it is supposed to serve.

Then there is the version of consolidation that is genuinely strategic. It starts not with the tools but with the workflows. What does the marketing team actually do, repeatedly, at volume? Where are the handoffs between systems that create friction or data loss? Where are team members spending time on manual tasks that a well-configured platform should be handling automatically?

Answering those questions honestly usually surfaces two or three areas where a single, well-integrated platform could replace several disconnected tools. The efficiency gain is not just in licence costs. It is in the reduced cognitive load on the team, the cleaner data that comes from fewer integration points, and the faster execution that comes from workflows that do not require constant human intervention.

I have seen this work well in practice when the consolidation decision is led by the people closest to the workflows, not the people closest to the budget. The finance case for consolidation is usually obvious. The operational case requires someone who understands how the work actually gets done.

If you want a more detailed view of where automation genuinely earns its place in a marketing stack, the Marketing Automation Systems hub covers the operational and strategic dimensions across the full automation landscape.

The Build Versus Buy Question Nobody Asks Properly

Early in my career, before I had any budget to speak of, I needed a website for a project I was working on. The answer from above was no. So I taught myself to code and built it. Not because I thought that was the optimal use of my time in the abstract, but because the alternative was doing nothing, and doing nothing was not acceptable.

That experience gave me a perspective I have carried through twenty years of agency work: the build-versus-buy question is almost always answered too quickly, in the direction of buy, because buying feels lower-risk and requires less internal capability. But the things you build yourself, whether that is a workflow, a reporting framework, or a piece of lightweight automation, tend to fit your actual needs far more precisely than the things you buy off the shelf.

This does not mean building is always the right answer. It rarely is for core infrastructure. But the reflex to reach for a vendor solution before asking whether the problem could be solved with existing tools and internal capability is a reflex worth examining. Some of the most effective marketing operations I have seen run on relatively simple stacks, with a lot of thoughtful configuration and a small amount of custom development sitting on top.

Buffer has written openly about their approach to transparent operational decisions, and the underlying principle, that clarity about how you work tends to produce better decisions than opacity, applies directly to martech buying as well.

What Good Martech Spend Looks Like in Practice

After managing hundreds of millions in ad spend across thirty-odd industries, I have developed a fairly clear picture of what separates marketing technology investments that deliver from the ones that do not.

The ones that deliver share a few characteristics. The outcome was defined before the tool was chosen. The people who will use the platform were involved in evaluating it. The integration requirements were mapped before the contract was signed, not after. There is a named owner who is accountable for adoption and performance. And there is a review point in the calendar, typically at six and twelve months, where the investment is assessed against the outcomes that were defined at the start.

The ones that do not deliver tend to share different characteristics. The buying decision was driven by a single champion whose priorities may not reflect the team’s. The vendor’s framing of the problem shaped the evaluation criteria. Integration was treated as an implementation detail rather than a strategic consideration. Nobody owns the platform after go-live. And the review process, if it exists at all, focuses on usage metrics rather than business outcomes.

None of this is complicated. But it requires a discipline that most marketing teams do not consistently apply, because the buying process is exciting and the governance process is not.

The organisations that get martech right tend to be the ones that treat every platform decision with the same rigour they would apply to a significant hire. You would not bring someone into a senior role without a clear brief, a structured evaluation, and a defined set of outcomes you expect them to drive. There is no good reason to treat a six-figure software commitment any differently.

About the Author

Keith Lacy is a marketing strategist and former agency CEO with 20+ years of experience across agency leadership, performance marketing, and commercial strategy. He writes The Marketing Juice to cut through the noise and share what works.

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