MARTECH · MEASUREMENT · 9 MIN

Your Martech Budget Is Bleeding and Nobody's Measuring It

AUG 06, 2026

A food pantry worker posted on r/MarketingAutomation last week with a problem I can't stop thinking about. Her organization runs on $60,000 a year and feeds about 200 families a month. She was considering a $25-a-month social scheduling tool, and she phrased the cost the way only someone with a real budget would: "this $25 a month could buy 50 pounds of rice."

She wanted to know how to tell whether the tool was worth it. The replies were honest. One marketer with 15 years of experience said the real barrier is loss aversion, and suggested treating the purchase as a short experiment with before-and-after numbers. Another said do the work manually first and only buy software once the manual way genuinely hurts.

That thread is the most rigorous martech ROI discussion I've seen this year, and it happened in a subreddit because nobody at the food pantry had a vendor deck to work from. Meanwhile, teams with seven-figure martech budgets renew their stacks every year without doing the $25 math.

The utilization problem is measured. The value problem isn't.

Gartner's 2025 Marketing Technology Survey found that only 49% of the tools in the average martech stack are actively used. Just 15% of organizations surveyed qualify as high performers on martech utilization. The 2024 edition of the same survey found large organizations run an average of 10.2 martech tools while relying on four or five for day-to-day work.

So half the stack sits idle even before anyone asks whether the active half is doing anything useful.

The market keeps feeding the pile. Chiefmartec's 2025 landscape map counts 15,384 martech solutions, up 9% in a year, with AI-native products doing most of the growing. And the money isn't growing with it. Gartner's CMO Spend Survey has marketing budgets flat around 7.7% of company revenue, and coverage of the 2026 edition by Chief Marketer puts martech's share of the marketing budget at a five-year low: 19.4%, down from 26.6% in 2021. Flat budget, more tools, smaller slice per tool. That is the sound of a line item getting squeezed while nobody checks what the squeeze buys.

AI made buying easier, which is not the same as smarter

AI features gave every vendor a fresh demo and a reason to raise the invoice. The pitch works because production speed is visible: more drafts, more variants, more campaigns per week. You can watch it happen in the meeting.

The measurement side did not get the same upgrade. Knak's "Marketing Production in the Age of AI" report, covered by MarTech in July, surveyed 333 marketing decision-makers in the U.S., U.K., and Canada at companies with $50 million or more in revenue. Marketers in that group were 68% more likely to measure email and landing page performance by click-through rate than by revenue or pipeline influenced. Sixty-nine percent track CTR. Forty-one percent track revenue or pipeline influence.

One in three said they consistently meet or exceed their campaign performance targets, which means two in three consistently don't, and most of them are judging the miss with a click metric.

And the AI output itself still needs hands on it: 88% of respondents said AI-generated content requires moderate or substantial editing before it can ship. Faster production, unchanged review burden, and weaker measurement add up to more output you can't account for, produced more quickly.

MarTech's write-up lands on the part that annoys me most: enterprise automation and CRM platforms can already connect email engagement to opportunity records. The data plumbing exists. What's missing is the reporting process built on top of it. Teams aren't waiting on a feature. They're avoiding a chore.

Your dashboard is lying to you politely

If you want to see what unexamined measurement does to a budget, the paid search world just published a clean example. In Search Engine Land, Maggie Humphrey of Cypress North walked through an account where brand and non-brand campaigns were blended together. Blended automation does what automation always does: it finds the cheapest conversion. Brand searches convert well because those customers were already looking for you. The algorithm buys them, reports a strong ROAS, and takes a bow.

When the team split brand and non-brand and stopped paying for demand that already existed, reported Google PPC revenue dropped 25% year over year, roughly $2.3 million. Read in isolation, that number looks like a failure. It isn't. Organic revenue rose 99% as branded searches shifted to the free listing. Combined paid plus organic revenue grew 15%, and new customer acquisition grew 20%.

The search tactic matters less than the pattern: the pre-restructure dashboard reported success while the account mostly bought its own customers. A healthy ROAS can be a receipt for money you didn't need to spend. Multiply that pattern across a martech stack, where every tool reports its own wins in its own dashboard, and you get a budget that looks measured and isn't.

The four questions worth asking before the next renewal

MarTech also published a piece on how the team behind MAICON, the Marketing AI Institute's conference, decides where AI belongs in a workflow. Their CMO Cathy McPhillips runs four questions before adding anything, and they translate cleanly to any martech purchase:

That last answer is the contrarian one. In a year when every vendor demo ends with an AI feature, the team that runs an AI marketing conference bought people, not subscriptions. They'd already measured what they had.

The audit checklist

If you can't remember the last time your stack was reviewed, here's a starting point. None of it requires a consultant.

• List every marketing tool that cost money in the last 12 months, including the AI add-ons that showed up inside existing contracts.
• Next to each one, write the monthly cost and the name of the person who actually logs in. If the second column is blank or it's someone who left the company, that's your first cut.
• For each tool, answer one question in a sentence: what number would go down if we cancelled it? If the answer is "we'd have to think about it," the tool is running on vibes.
• Pull the utilization report if your platform has one. Compare seats paid against seats active in the last 90 days. Gartner's benchmark says expect roughly half.
• Check what each tool measures. Clicks and opens don't count as an answer. Revenue, pipeline, or a named cost saving does.
• Run one cancellation experiment per quarter. Downgrade or cancel the weakest tool, measure for 60 days, and see who complains. Nobody complaining is the result.

The food pantry thread nailed the psychology of step one. The commenter who does pro-bono nonprofit marketing called it a discomfort with ROI: people know the math works and still flinch at the spend. The fix he suggested is the same fix that works at mid-market scale. Frame it as an experiment, measure before and after, and let the numbers close the argument.

What this costs, roughly

The visible part of a martech line item is the invoice. The rest is what the invoice never shows:

Those are directional numbers for a mid-market stack, not a quote, but the structure holds: the invoice is usually the smallest real cost of any tool you buy, and the only one anyone budgets for.

The measurement gap is not a technology gap. The platforms can already connect the dots; Gartner says the data plumbing exists, and the teams that do connect them are the 15% Gartner counts as high performers. Everyone else is paying full price for a stack they half use, judged by metrics the vendors picked.

Your budget is not bleeding because the tools are bad. It's bleeding because asking "what did this return" is unglamorous work, and AI made it very easy to buy the next thing instead of doing it.

Browse the MartechSignal tools directory before the next renewal. The right question isn't what a tool costs. It's what you'd notice if it disappeared.