MarTech Stack ROI Audit
Most stacks accumulate tools faster than anyone removes them
MarTech stacks grow through a one-way ratchet: a new tool gets purchased to solve a specific problem, the problem gets solved or the team moves on, and the tool's renewal quietly auto-approves year after year because cancelling it requires someone to notice, question it, and do the work of migrating off it. Few organizations have a symmetric process for removing tools to match the process for adding them. A MarTech stack ROI audit is that missing symmetric process — a periodic, deliberate review of what's actually being used, by whom, and whether the cost still matches the value delivered.
Auditing tool utilization vs. license cost
The audit starts with two numbers side by side for every tool in the stack: what it costs (including all tiers, add-ons, and usage-based charges, not just the base subscription) and how it's actually being used (active user count against licensed seats, feature adoption depth, API call volume against what's provisioned, login frequency). The gap between these two numbers is the single most actionable finding an audit produces — a $50,000/year platform with 3 active users out of 40 licensed seats is a far more urgent finding than a cheaper tool being used exactly as intended, even though the cheaper tool might feel more 'in focus' day to day.
Utilization data should come from the vendor's own admin reporting wherever possible (most platforms expose seat activity and feature usage to admins) rather than asking teams to self-report usage, since self-reported estimates are reliably optimistic — people tend to describe a tool by its intended role rather than how often they actually open it.
MARTECH TOOL AUDIT WORKSHEET (per tool)
Tool name: ______________________
Annual cost (all-in, incl. add-ons): $______________
Owner / primary business reason it was purchased: ____________
UTILIZATION
Licensed seats: ____ Active seats (last 90 days): ____
Core use case still happening? Y / N
Feature adoption: using <25% / 25-75% / >75% of paid tier features
Last meaningful configuration change: ____________
OVERLAP
Does another tool in the stack do this, fully or partially? ____
If yes, which, and why are both still active? ____________
COST TRAJECTORY
Cost 1 year ago: $______ Cost today: $______
Projected cost at 2x usage: $______
VERDICT
[ ] Keep as-is [ ] Renegotiate/downgrade tier
[ ] Consolidate into: ____________
[ ] Sunset — migration owner: ____________Low utilization doesn't always mean cancel — sometimes it means the tool is mis-provisioned
Shelf-ware identification
Shelf-ware is software that was purchased, implemented to some degree, and then effectively abandoned — still being paid for, rarely or never opened, with no one actively championing its continued use. It accumulates for predictable reasons: the champion who pushed for the purchase left the company and no one inherited ownership; a point solution was fully replaced by a broader platform's built-in feature but the smaller tool was never formally decommissioned; or a tool was bought for a specific campaign or initiative that ended, with the subscription simply never cancelled afterward.
Shelf-ware is identified the same way utilization is audited — login frequency, feature usage, and crucially, whether anyone can name a current business reason for the tool when asked directly. A tool nobody can defend in under thirty seconds, when asked 'what does this do for us right now,' is a strong shelf-ware candidate regardless of how reasonable the original purchase decision was.
Signals of shelf-ware vs. a healthy, active tool
| Signal | Shelf-ware pattern | Healthy tool pattern |
|---|---|---|
| Named owner | No one can say who owns it today | Clear current owner who can explain its role |
| Usage trend | Flat or declining logins over the past year | Steady or growing usage |
| Overlap | Capability now covered by another platform | Distinct capability nothing else in the stack covers |
| Renewal history | Auto-renewed without review for 2+ cycles | Renewal actively reviewed against current need |
| Business case | Tied to an initiative that already ended | Tied to an ongoing, current business function |
Consolidation decision framework
Finding overlapping tools is only half the work — deciding which one to keep requires more than picking the cheaper option. A consolidation decision should weigh: which tool has deeper integration into the rest of the stack already (switching away from the more deeply embedded tool costs more in migration effort than the license savings may justify in year one), which tool the team has more institutional knowledge in (retraining cost is real and often underestimated), whether the surviving tool's feature set actually covers every use case the retired tool served or whether some workflows will quietly degrade, and what the actual migration cost is — data export/import, any custom integration rebuilding, and a transition period where both tools may need to run in parallel.
A consolidation that saves $15,000/year in licensing but costs three months of a marketing ops specialist's time to migrate, plus a quarter of degraded reporting during the transition, may not be worth doing in the time frame being considered — the audit should surface the total cost of consolidating, not just the licensing delta, before a decision is made.
An audit that doesn't result in any cancellations probably wasn't rigorous
What's next
A stack audit naturally surfaces architectural questions about how the remaining tools should connect to each other — worth revisiting against the foundational layered architecture model.
Next: MarTech Stack Architecture →
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