Marketers use only one-third of their martech stack’s capability, according to Gartner’s 2023 Martech Report. You are paying for three times what you use. Martech stack consolidation is the obvious fix, but picking one platform over best-of-breed tools is a risk decision, not a cost-cutting reflex. Here is how to make it without regret.
The case against your current stack is mostly about utilization
The same report puts utilization at 42% a year earlier and 58% in 2020. Over that period, spending climbed. The article cites Statista figures showing martech spend rising 35% from $15.3 billion in 2020 to $23.6 billion in 2023.
More tools, less use. That is the pattern most influencer and creator teams recognize. One tool for discovery, another for contracts, a third for payments, a fourth for reporting, and a spreadsheet gluing them together.
Budget pressure makes it worse. Gartner’s CMO Spend Survey found that average marketing budgets fell to 7.7% of company revenue, down from 9.1% in 2023. When every line item gets questioned, a stack full of shelfware is hard to defend.
Low utilization is the real consolidation signal. If you cannot name who uses a tool weekly and what decision it changes, you are renting a feature, not running a capability.
When a single platform wins
Consolidation pays off in specific conditions. Look for these.
- Your team is small and the workflow is linear. A three-person influencer team does not need five admin logins. Fewer handoffs means fewer dropped briefs and late payments.
- Data fragmentation is costing you decisions. If creator performance lives in one tool and pipeline data in another, reconciling them eats analyst hours. A unified data model can fix that faster than another connector.
- Governance matters more than features. Regulated categories (finance, health, alcohol) need consistent disclosure, approvals, and audit trails. One system of record is easier to defend to legal.
- Two tools with heavily overlapping features are an easy cut. Audit before you shop.
- Integration upkeep exceeds license cost. Count the engineering and ops hours spent keeping APIs alive. They rarely show up on the martech budget.
Think of the suite as a bet on operational efficiency. You trade peak functionality for fewer failure points.
When best-of-breed still earns its seat
Specialists win where the capability is your competitive edge. If creator-led content is a primary revenue channel, a generic module bolted onto an email platform will not match a purpose-built tool for vetting, rights, or media buying.
Three cases stand out.
- The function is core to differentiation. Creator matching and fraud detection are examples. A weak tool here costs you more in bad partnerships than any license saves.
- The suite’s module is immature. Suites often ship a “good enough” feature to close a gap on a comparison sheet. Ask to see customers running it at your scale.
- You need speed of innovation. AI features are shipping monthly at point-solution vendors. Large suites move slower.
For example, rights and licensing is an area where shortcuts bite. Our look at usage window risk shows why a thin module can leave exposure on the table. Payments are similar: the admin burden of creator payments is often what a specialist removes, and a suite may not.
Is the stack really getting smaller?
Not usually. That surprises people.
In practice, swapping out a tool rarely shrinks a stack.
Replacing is not consolidating. Teams swap one tool for another and add a third for the gap. If your plan does not name which tools get retired, and by when, you are running a replacement project, not a consolidation.
The survey also shows what buyers weigh. In the evaluations I see, cost leads the criteria, with integration capability and open APIs right behind it. Notice that integration ranks second. Even buyers who want fewer tools expect the remaining ones to connect to everything else.
A scorecard before you sign
Run each candidate function through five questions. Score 1 to 5. Do it with the people who use the tools, not just procurement.
- Strategic weight. Does this function differentiate us, or is it plumbing? Plumbing consolidates. Differentiators get scrutiny.
- Usage reality. What share of licensed features do we use? Pull login and activity data.
- Integration cost. What do we spend maintaining the connections? Include ops time.
- Exit cost. Can we export our data, creator records, and contracts cleanly? Suites make this harder by design.
- Risk concentration. If this vendor raises prices, gets acquired, or has an outage, what stops working?
Exit terms deserve extra weight. Our guide to data ownership and exit terms covers the contract language to demand before you commit to a single vendor for everything.
Consolidate in layers, not all at once
The cleanest approach is a hybrid. Pick one platform for the foundation (CRM, data, workflow) and keep two or three specialists on top where they carry real weight.
Start with the data layer. If your customer and creator data do not join up, no workflow tool will fix attribution. The CDP and CRM pairing question is usually the first one to settle, because it decides what every other tool can see.
Then address workflow. Before buying a suite’s built-in module, compare it against dedicated options using a stage-by-stage lens like the one in our breakdown of workflow automation platforms. Gaps tend to cluster at briefing, rights, and payment.
Finally, assign ownership. Utilization falls partly because nobody owns the stack. Gartner’s press release notes that CMOs are seeing diminishing influence over martech as IT and other leaders take more control. If you want a say, bring your own scorecard to that conversation. A formal center of excellence gives marketing a standing owner for these calls.
The question is rarely “suite or specialist.” It is “which three functions do we refuse to compromise on, and which can we standardize?”
Pitfalls to avoid
- Buying on the demo. Suite demos show the best module. Ask for a reference customer using the weakest one you need.
- Ignoring migration. Historical creator performance, contracts, and usage rights have to move. Budget time for it.
- Counting license savings only. Include training, change management, and lost productivity in the first quarter.
- Skipping the retirement date. If the old tool is still running six months later, you have added cost.
Next step: list every tool in your stack, mark each as differentiator or plumbing, and pull 90 days of usage data. Anything that is plumbing and under-used is your first consolidation candidate.
FAQs
What is martech stack consolidation?
It is the process of reducing the number of marketing technology tools you run by retiring overlapping or under-used ones. Often that means moving functions onto a single platform. The goal is lower cost, cleaner data, and fewer integrations to maintain.
Is a single platform always cheaper than best-of-breed?
No. License fees may drop, but migration, training, and weaker modules can offset the savings. Compare total cost of ownership, including integration maintenance and the cost of any capability you lose.
When should I choose best-of-breed tools?
Choose specialists for functions that differentiate your program, such as creator vetting, rights management, or media buying, and where a suite’s module is immature. Also consider them when you need fast access to new AI capabilities.
How do I know which tools to cut first?
Start with tools that overlap in features, have low login activity, and sit outside your core differentiators. Pull usage data for the last 90 days and ask each owner what decision the tool informs.
What are the biggest risks of consolidating onto one vendor?
Vendor lock-in, price increases at renewal, and concentrated outage risk. Negotiate data export rights, price caps, and clear exit terms before signing.
Can a hybrid approach work?
Yes, and it is the most common outcome. Standardize on one platform for CRM, data, and core workflow, then keep a small number of specialist tools where they deliver measurable advantage. Insist on open APIs so the pieces connect.
How long does consolidation take?
It depends on contract end dates and data complexity. Plan in phases, usually starting with the data layer, and set firm retirement dates for each tool you are replacing so the stack actually shrinks.
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