StackSwap · Q2 2026 · modeled from 100,000 GTM stacks · methodology v1.1.0
The 2026 GTM Stack Benchmark
What does a typical go-to-market stack actually look like — how many tools, how much spend per GTM employee, how AI-native, how much overlap? We modeled 100,000 stacks across 12 operator archetypes through the same engine that powers StackScan. Here's the benchmark, broken down by GTM motion and team size. Find your row, then run your own stack to see where you land.
The typical GTM stack
Benchmark by GTM motion
The single biggest driver of what a stack looks like is its go-to-market motion. Medians per archetype:
| GTM motion | % of stacks | Median tools | Spend / GTM employee/yr | AI-native score | Overlaps | Annual recoverable |
|---|---|---|---|---|---|---|
| Mid-market B2B SaaS (sales-led) | 19.9% | 9 | $8,810 | 35 | 3 | $133,080 |
| Growth-stage mid-market (multi-channel) | 15.0% | 12 | $9,428 | 39 | 5 | $281,880 |
| Early-stage B2B SaaS (founder-led) | 12.1% | 5 | $1,987 | 58 | 0 | $0 |
| Dev-tools PLG | 10.0% | 7 | $3,281 | 65 | 1 | $6,000 |
| Enterprise RevOps | 8.0% | 11 | $7,073 | 28 | 4 | $745,740 |
| PLG + sales-assist hybrid | 7.0% | 9 | $3,665 | 60 | 1 | $23,220 |
| AI-native modern team | 6.0% | 8 | $2,422 | 66 | 1 | $0 |
| Mid-market sales with Apollo + HubSpot | 6.0% | 8 | $4,007 | 53 | 1 | $30,480 |
| Bootstrapped lean (1-15) | 5.0% | 6 | $2,013 | 52 | 1 | $480 |
| Late-stage enterprise (multi-region) | 4.9% | 12 | $6,462 | 28 | 5 | $2,507,880 |
| Post-acquisition tangled (Outreach + Salesloft) | 3.0% | 10 | $8,225 | 31 | 5 | $776,028 |
| Marketing-led B2B (HubSpot heavy) | 3.0% | 8 | $4,352 | 53 | 2 | $42,180 |
Benchmark by team size
Stack size and recoverable spend scale with GTM headcount — but not linearly. The overlap and waste compound as teams add tools faster than they retire them.
| Team size | % of stacks | Median tools | Spend / GTM employee/yr | AI-native score | Overlaps | Annual recoverable |
|---|---|---|---|---|---|---|
| 1–5 | 7.8% | 5 | $2,280 | 54 | 0 | $0 |
| 6–15 | 13.0% | 6 | $2,494 | 57 | 1 | $960 |
| 16–25 | 11.1% | 8 | $6,984 | 43 | 1 | $61,440 |
| 26–50 | 32.0% | 9 | $7,118 | 41 | 2 | $104,160 |
| 51–100 | 18.0% | 11 | $7,897 | 42 | 3 | $256,920 |
| 101–200 | 6.0% | 10 | $6,383 | 35 | 3 | $310,680 |
| 201–500 | 7.2% | 11 | $7,062 | 28 | 4 | $915,360 |
| 501–1000 | 1.6% | 12 | $6,787 | 28 | 5 | $1,567,560 |
| 1000+ | 3.3% | 12 | $6,400 | 28 | 5 | $2,878,680 |
The most common tool overlaps
These are the redundant tool pairs that show up most often — two tools doing substantially the same job. Each row is a place teams routinely pay twice.
| Overlapping pair | % of stacks | Median annual recovery |
|---|---|---|
| HubSpot Marketing Hub × Salesforce | 30.0% | $1,800 |
| Clari × Gong | 23.8% | $1,200 |
| Apollo.io × ZoomInfo | 20.5% | $2,400 |
| Outreach × Salesloft | 18.7% | $1,200 |
| Apollo.io × Outreach | 17.8% | $1,200 |
| Linear × Notion | 15.2% | $960 |
| Clearbit × ZoomInfo | 14.0% | $3,600 |
| Chorus × Gong | 13.0% | $1,200 |
| HubSpot × Marketo | 0.8% | $6,000 |
| HubSpot Marketing Hub × Marketo | 11.9% | $17,280 |
| HubSpot × Mailchimp | 11.8% | $1,200 |
| 6sense × ZoomInfo | 11.5% | $15,600 |
Where does your stack land?
Paste your GTM tools and see your tool count, spend per employee, AI-native score, and overlaps against the peers in your exact motion and team-size cohort — plus the specific tools to cut. Free; no signup to view results.
Modeled, not surveyed: every number here comes from running 100,000 synthetic stacks through the production scoring engine. Synthetic inputs, real engine, reproducible (seed 42). Full methodology and reproducibility contract at /methodology. Refreshed quarterly; this is the Q2 2026 cut (methodology v1.1.0).