Done-for-you offer · Fractional CMO with AI Swarm · drivers-analysis skill · 3RD 7-SKILL BUNDLE
Completions builds drivers analysis — 🎯 3RD 7-SKILL BUNDLE IN ARC + 🎯 7-skill tier 3 archetypes + 🎯 Causal -explanation reporting sub-axis
You operate 50-1,500 locations × per-outcome per-driver causal-analysis dependency. Per-outcome per-driver drivers analysis without governance fragments per -outcome per-driver hypothesis + inference + counterfactual + ranking + narrative. Completions builds the drivers-analysis 7-skill bundle on the rollup -reporting agent end-to-end. 🎯 3RD 7-SKILL BUNDLE IN ARC (outcome-metric-capture + driver-hypothesis -generation + causal-inference + counterfactual -modeling + driver-ranking + narrative-explanation + attestation — 7-skill bundle now CONFIRMED-recurring at 3 instances). 🎯 7-skill tier 3 archetypes (3RD distinct archetype: causal-analysis archetype, joins data-fabric + consumer-loyalty-pre-emit). 🎯 Causal-explanation reporting sub-axis (reporting now 2-axis sub-axis -taxonomy in catalog: descriptive-summary + causal -explanation). You keep every artifact.
Published September 24, 2026
Frequently asked
What does "Completions builds drivers analysis — 3RD 7-SKILL BUNDLE IN ARC + 7-skill tier 3 archetypes + Causal-explanation reporting sub-axis" actually deliver?
Completions builds and operates per-outcome per-driver outcome-metric-capture + driver-hypothesis-generation + causal-inference + counterfactual-modeling + driver-ranking + narrative-explanation + attestation across the rollup-reporting agent. Per-outcome per-driver outcome-metric-capture (skill 1) captures per-outcome per-driver outcome-metric across 50-1,500 locations × per-outcome per-driver 15+ outcome-metrics (per-outcome per-driver revenue-uplift + per-outcome per-driver new-customer-acquisition-rate + per-outcome per-driver LTV-uplift + per-outcome per-driver retention-rate + per-outcome per-driver per-location-rank + per-outcome per-driver same-store-sales-growth + per-outcome per-driver marketing-attributed-revenue-growth + per-outcome per-driver ROAS-change + per-outcome per-driver CAC-change + per-outcome per-driver CAC-payback-change + per-outcome per-driver churn-rate-change + per-outcome per-driver foot-traffic-uplift + per-outcome per-driver phone-call-uplift + per-outcome per-driver review-volume-uplift + per-outcome per-driver review-rating-uplift). Per-outcome per-driver driver-hypothesis-generation (skill 2) generates per-outcome per-driver hypothesis-set across per-outcome per-driver driver-categories (per-outcome per-driver campaign-driver + per-outcome per-driver creative-driver + per-outcome per-driver bidding-driver + per-outcome per-driver channel-mix-driver + per-outcome per-driver promo-driver + per-outcome per-driver pricing-driver + per-outcome per-driver location-operations-driver + per-outcome per-driver staffing-driver + per-outcome per-driver seasonality-driver + per-outcome per-driver competitive-driver + per-outcome per-driver weather-driver + per-outcome per-driver macro-driver). Per-outcome per-driver causal-inference (skill 3) runs per-outcome per-driver causal-inference (per-outcome per-driver geo-experiment + per-outcome per-driver synthetic-control + per-outcome per-driver difference-in-differences + per-outcome per-driver interrupted-time-series + per-outcome per-driver propensity-score-matching + per-outcome per-driver instrumental-variable + per-outcome per-driver regression-discontinuity). Per-outcome per-driver counterfactual-modeling (skill 4) models per-outcome per-driver counterfactual (per-outcome per-driver what-if-no-campaign + per-outcome per-driver what-if-no-promo + per-outcome per-driver what-if-no-channel + per-outcome per-driver what-if-no-staffing-change + per-outcome per-driver what-if-no-competitive-action) with per-outcome per-driver confidence-interval + per-outcome per-driver sensitivity-analysis. Per-outcome per-driver driver-ranking (skill 5) ranks per-outcome per-driver drivers by per-outcome per-driver causal-contribution-weight + per-outcome per-driver confidence + per-outcome per-driver actionability + per-outcome per-driver per-stakeholder-relevance. Per-outcome per-driver narrative-explanation (skill 6) generates per-outcome per-driver narrative-explanation (per-outcome per-driver headline-summary + per-outcome per-driver what-drove-it + per-outcome per-driver why-it-drove-it + per-outcome per-driver per-stakeholder-implication + per-outcome per-driver next-best-action + per-outcome per-driver counterfactual-cite + per-outcome per-driver confidence-cite + per-outcome per-driver methodology-cite). Per-outcome per-driver attestation (skill 7) emits per-outcome per-driver attestation-record with attestor-identity + attestation-timestamp + WORM-storage-attestation + chain-of-custody-record + per-vertical compliance overlay. 🎯 3RD 7-SKILL BUNDLE IN ARC — extends prior 1st 7-skill bundle at #524 + 2nd at #530 by adding the 3RD 7-skill bundle (outcome-metric-capture + driver-hypothesis-generation + causal-inference + counterfactual-modeling + driver-ranking + narrative-explanation + attestation) on the rollup-reporting agent; cumulative 7-skill bundle count in the catalog reaches 3 with this skill; 3RD 7-SKILL BUNDLE IN ARC marks 7-skill bundle as a CONFIRMED-recurring canonical-bundle-size at 3 instances (no longer 2 archetypes). 🎯 7-skill tier 3 archetypes — extends prior 7-skill tier 2 archetypes (per #530) by adding the 3RD distinct archetype: causal-analysis archetype (vs #524 data-fabric archetype + #530 consumer-loyalty-pre-emit archetype); 7-skill bundle now has 3 confirmed archetypes (data-fabric + consumer-loyalty-pre-emit + causal-analysis); 7-skill tier 3 archetypes marks 7-skill bundle as a topology-diverse canonical-bundle-size at 3 distinct archetypes. 🎯 Causal-explanation reporting sub-axis — extends prior reporting sub-axis taxonomy by adding the Causal-explanation reporting sub-axis where rollup-reporting now hosts both descriptive-summary (per #537 monthly-executive-summary-drafting) + causal-explanation (this skill); cumulative reporting sub-axis count reaches 2 with this skill (descriptive-summary + causal-explanation); Causal-explanation reporting sub-axis marks reporting as a 2-axis sub-axis-taxonomy in the catalog. Per-outcome per-driver compliance overlay (per-vertical SEC-Reg-FD + per-vertical SOX + per-vertical PE/LP-investor-reporting-policy + per-vertical attorney-client-privileged-redaction + per-vertical material-non-public-information-handling + per-vertical FTC-substantiation-policy + per-vertical statistical-methodology-disclosure). Operator team owns the per-outcome per-driver outcome-metric-capture + driver-hypothesis-generation + causal-inference + counterfactual-modeling + driver-ranking + narrative-explanation + attestation registries + audit trail. Completions owns the swarm orchestration on the rollup-reporting agent.
Why does in-house drivers analysis break at multi-outcome multi-driver scale?
In-house operation fails on seven axes: (1) per-outcome per-driver outcome-metric-capture across 15+ outcome-metrics requires data-engineering capacity unstaffable by internal teams; (2) per-outcome per-driver driver-hypothesis-generation across 12 driver-categories requires hypothesis-engineering capacity; (3) per-outcome per-driver causal-inference across 7 inference-methods requires causal-inference-engineering capacity; (4) per-outcome per-driver counterfactual-modeling with confidence-interval + sensitivity-analysis requires modeling-engineering capacity; (5) per-outcome per-driver driver-ranking across 4 ranking-dimensions requires ranking-engineering capacity; (6) per-outcome per-driver narrative-explanation across 8 narrative-elements with methodology-cite requires content-engineering capacity; (7) per-outcome per-driver attestation with WORM-storage + chain-of-custody + 7-vertical compliance overlay requires audit-engineering capacity. 3RD 7-SKILL BUNDLE IN ARC + 7-skill tier 3 archetypes + Causal-explanation reporting sub-axis architecture coordination requires orchestration capacity at the 7-skill bundle tier. Completions absorbs all seven axes under one Tier 3 Fractional CMO with AI Swarm engagement.
What does the engagement look like across Tier 1 to Tier 2 to Tier 3?
Tier 1 AI Readiness Assessment ($10k, 2-3 weeks, diagnostic): audits seven axes. Tier 2 AI Swarm Setup Sprint ($25-50k, 4-8 weeks): builds 7-skill bundle on rollup-reporting agent — completing the 3RD 7-SKILL BUNDLE IN ARC + 7-skill tier 3 archetypes + Causal-explanation reporting sub-axis architecture. Tier 3 Fractional CMO with AI Swarm ($15-25k/month, 6-month minimum, 1-2 days/wk embedded): continues operating end-to-end + cross-agent swarm coordination.
Who owns the registries?
Operator owns 100% of every artifact: 7 registries (in operator data infrastructure), 7-skill bundle model code (operator-owned + operator-data-engineering-team-aligned + operator-analytics-engineering-team-aligned), per-vertical compliance overlay (rule library in operator repo with attorney-approved updates), causal-inference methodology library, LLM prompts, audit trail. Completions owns the orchestration knowledge.
What KPIs will Completions commit to on Tier 3 engagement?
Typical Tier 3 commitments: (1) per-outcome per-driver outcome-metric-capture coverage at 99-percent target across 15+ outcome-metrics; (2) per-outcome per-driver driver-hypothesis-generation coverage at 95-percent target across 12 driver-categories; (3) per-outcome per-driver causal-inference methodology pass-rate at 99-percent target across 7 inference-methods with peer-review attestation; (4) per-outcome per-driver counterfactual-modeling accuracy at 80-percent target with 90-percent confidence-interval; (5) per-outcome per-driver driver-ranking precision at 85-percent target across 4 ranking-dimensions; (6) per-outcome per-driver narrative-explanation completeness at 99-percent target across 8 narrative-elements with methodology-cite; (7) per-outcome per-driver attestation persistence at 100-percent target with WORM-storage.
How does engagement end and what is the operator transition path?
Tier 3 engagements are 6-month minimum with 90-day notice. At engagement end, Completions transitions back to operator in-house in 30-60 days: operating-playbook hand-off + in-house staff training + 7 registries hand-off + 7-skill bundle model code hand-off + per-vertical compliance overlay rule library hand-off + causal-inference methodology library hand-off + LLM prompts hand-off + audit trail hand-off; Completions credentials revoke immediately.
Engage Completions
Start with the AI Readiness Assessment (Tier 1, 2-3 weeks, $10k). Hand off to Tier 2 ($25-50k, 4-8 weeks). Continue under Tier 3 Fractional CMO with AI Swarm ($15-25k/month, 6-month minimum, 1-2 days/wk embedded).