Expansion Revenue Intelligence Command Center
An installed-base growth console that scores expansion readiness, selects the right upsell motion, and models expected ARR, margin, SLA, and payback.
The problem
Expansion revenue is often hidden in scattered CSM notes, usage dashboards, renewal timing, and sales intuition. Teams know some accounts are ready, but the readiness signal is rarely operationalized.
The thesis
Expansion becomes repeatable when account readiness, offer fit, margin, pursuit cost, SLA, and payback are evaluated before the team chooses pursue, nurture, or defer.
System flow
Step 1
Account-base inputs
Maintain editable ARR, seats, usage growth, PQS, support health, renewal timing, sponsors, and expansion signals.
Step 2
Readiness scorer
Classify accounts by readiness and infer the strongest motion from seat, usage, product, and commercial signals.
Step 3
Offer recommender
Map account signals to seat expansion, feature upgrade, usage commit, or services attach offers.
Step 4
ARR economics
Persist expected expansion ARR, margin, pursuit cost, payback, SLA fit, decision band, and audit event.
Case-study artifacts
Expected ARR
Expansion motions are modeled as incremental ARR by account.
Readiness
Signals combine into inspectable expansion readiness scores.
Payback
Pursuit decisions respect margin, SLA, and payback thresholds.
Decision frame 1
Input
Editable ARR, seats, usage growth, product qualification, support health, renewal timing, sponsor status, offers, and policy.
Decision frame 2
Decision
Score readiness and select seat expansion, feature upgrade, usage commit, or services attach.
Decision frame 3
Output
Expected ARR, margin, pursuit cost, payback, decision band, and audit event.
Evidence links
Shows the command-center framing and operating sequence.
Shows editable accounts, offers, and policy thresholds.
Shows run controls, KPI output, and the pipeline board.
Shows account-base signal table with readiness scores.
Shows expected ARR, margin, payback, and account recommendations.
Guardrails
Offers below policy margin are deferred.
Pursuit recommendations require gross-profit payback above threshold.
High-readiness opportunities must fit the pursuit SLA window.
System architecture
1. Account-base inputs
Maintain editable ARR, seats, usage growth, PQS, support health, renewal timing, sponsors, and expansion signals.
2. Readiness scorer
Classify accounts by readiness and infer the strongest motion from seat, usage, product, and commercial signals.
3. Offer recommender
Map account signals to seat expansion, feature upgrade, usage commit, or services attach offers.
4. ARR economics
Persist expected expansion ARR, margin, pursuit cost, payback, SLA fit, decision band, and audit event.
KPI callouts
Readiness score
Each account is scored using utilization, growth, PQS, support health, timing, and signals.
Expected ARR
Runs model expected expansion ARR by account and offer.
Decision lane
Policy checks turn readiness into pipeline action.
Commercial framing
The system makes expansion less anecdotal by converting installed-base signals into an accountable pipeline with offer fit, margin, and payback attached.
What I built
I built the expansion schema, editable account/offer/policy inputs, readiness scoring engine, run endpoint, pipeline board, account recommendations, output economics, audit trail, and docs.