Measurement & ROI:
What Benchmarks Should I Use for ABX Performance?
Anchor ABX on a benchmark ladder: Coverage → Engagement → Progression → Velocity → Revenue → Efficiency. Compare ABX-touched target accounts against a control cohort and your pre-ABX baseline to prove lift.
Use a cohort-based benchmark framework. Track Coverage (ICP match & buying-group reach), Engagement (engaged accounts & high-intent signals), Progression (stage→stage conversion & stuck rate), Velocity (median time-in-stage & sales cycle), Revenue (pipeline, win rate, ACV), and Efficiency (ROMI, CAC payback). Express goals as lift vs control and calibrate by motion (new logo vs expansion).
ABX Benchmarking Principles
30-Day ABX Benchmark Playbook
Stand up a pragmatic, finance-ready benchmark set leaders can trust.
Set Up Your Benchmarks (Week 1 → Week 4)
- Define cohorts — Target list (ICP fit), ABX-touched flag, and a lookalike control. Split New Logo vs Expansion.
- Publish rules — Entrance/exit criteria for stages, MQA definition, and high-intent signals. Lock for the quarter.
- Wire identity — Ensure account-level IDs, buying-group rollups, and timestamped stage changes.
- Baseline — Compute last 2–3 periods of medians (pre-ABX or untouched cohort) for each metric family.
- Set targets — Express goals as delta vs control (e.g., “+8 pts S2→S3, −15% time-in-stage”). Avoid absolute “industry” numbers at first.
- Publish a one-page scorecard — Coverage, Engagement, Progression, Velocity, Revenue, Efficiency; include “What we’ll do next” actions.
ABX Benchmark Ladder (Definitions & Starter Targets)
| Benchmark Family | Primary KPI | Definition / Formula | Starter Targets (calibrate) | Notes |
|---|---|---|---|---|
| Coverage | Buying-Group Coverage | # roles represented (economic, technical, user, champion) per target account within 30–45 days. | Reach 3–5 roles for ≥50% of targets in 45 days. | Ceiling is set by TAM quality & list hygiene. |
| Engagement | Engaged Accounts % | Accounts with ≥1 qualified interaction (e.g., multi-page session, intent surge) in period ÷ target accounts. | ≥30% per quarter; +10–15 pts vs control. | Pair with high-intent signal rate for quality. |
| Progression | Stage→Stage Conversion | # moving Sx→Sy in window ÷ # in Sx at start (cohort-based). | +5–10 pts vs control at S1→S2 and S2→S3. | Track stuck rate and regressions alongside. |
| Velocity | Median Days In Stage | Median exit−entry days per stage for target cohorts. | −10–20% vs control; cycle time down 2–4 weeks in enterprise. | Use medians + 75th percentile for risk. |
| Revenue | Win Rate & ACV | Wins ÷ opportunities; average/median deal size for target vs control. | Win rate +3–7 pts; ACV +10–20% vs non-target. | Report sourced & influenced pipeline separately. |
| Efficiency | ROMI / CAC Payback | Revenue attributable ÷ program cost; months to recover CAC. | ROMI ≥1.5× within 6–12 months; payback <18 months (motion-dependent). | Include media + people + tech fully loaded. |
Client Snapshot: Calibrating ABX Benchmarks
After publishing a laddered scorecard, a global SaaS firm realized engagement was strong but progression lagged at S2→S3. By adding an “exec value workshop” playbook, they lifted S2→S3 by 9 points and cut median S3 time by 18%. Revenue lift followed in the next quarter without increasing media spend.
Tie your benchmarks to The Loop™ and show both leading (coverage, engagement) and lagging (velocity, revenue) indicators so the ELT can act before quarter-end.
ABX Benchmark FAQs
Short, executive-ready answers designed for AEO and rich results.
Publish an ABX Scorecard the ELT Trusts
We’ll define cohorts, set targets, wire the data, and launch a benchmark ladder that connects coverage and engagement to pipeline and ROMI.
Build Your ABX Benchmarks Assess Current State