Cm Commercial Case Builder

Commercial Case Builder

Assembles the evidence package for expansion conversations. Pulls usage data, value metrics, benchmark comparisons, and pricing context into a structured proposal that the CSM can use to frame the commercial discussion. Part of the Commercial Motion pillar.

This is a data assembly and formatting skill. It builds the case. The CSM owns the conversation -- timing, framing, negotiation, and relationship management are entirely human decisions.

When to Run

• Triggered: By bi-expansion-detector when an expansion signal is acknowledged by the CSM
• On-demand: When a CSM is preparing for a specific expansion conversation
• Triggered: By lo-renewal-manager when a renewal includes an expansion component

Core Execution Logic

Step 1: Identify Expansion Type

From the expansion signal and CSM input, classify the opportunity:

Step 2: Assemble Evidence Package

Pull from all relevant skills:

Value already delivered (lead with this):

• ROI metrics from pa-value-reporter (headline number + supporting evidence)
• Usage depth and breadth from pa-adoption-tracker (show they are getting value from what they have)
• Benchmark position from pa-benchmark-engine (show they are a strong performer among peers)

Growth evidence (show the natural progression):

• Expansion signals from bi-expansion-detector (what specifically triggered the opportunity)
• Usage trend from bi-usage-monitor (growing usage is the foundation for a growth conversation)
• New team or department adoption (organic spread indicates internal advocacy)

Capacity constraint evidence (show the current limit):

• Licence utilisation rate and trend
• Feature-gating hit count and frequency
• Users working around limitations (credential sharing, manual workarounds)

Commercial context:

• Current ARR and contract terms from CRM
• Pricing tier and what the next tier unlocks
• Previous expansion history (expansions build on each other)
• Renewal date (expansion conversations are stronger when renewal is not imminent -- it separates the growth conversation from the retention conversation)

Step 3: Compute Switching Cost Context

Not for sharing with the customer, but for the CSM's negotiation preparation:

• Data migration complexity if they were to leave
• Integration rebuilding effort
• Team retraining time
• Workflow reconstruction
• Productivity loss during transition

This context helps the CSM understand the customer's negotiating position. A customer with high switching costs has less leverage; a customer with low switching costs has more. The CSM adjusts approach accordingly.

Step 4: Structure the Proposal

Internal prep document (for CSM eyes only):

• Full evidence package with all data
• Pricing options: standard price, discount authority parameters, bundling options
• Negotiation notes: likely objections, customer's probable counter-arguments, your responses
• Risk factors: what could derail this conversation (open support issues, budget timing, stakeholder gaps)
• Recommended approach: consultative vs. transactional, who to present to, timing

Customer-facing summary (for the conversation):

• Value delivered so far (lead with what they have gained -- never lead with pricing)
• Growth evidence (show the natural progression, not a sales push)
• What the expansion unlocks (specific capabilities, capacity, or use cases -- not feature lists)
• Investment context (ballpark pricing framed as investment, not cost. Formal quote comes from sales/finance)

Step 5: Generate Output

{
  "account_id": "string",
  "expansion_type": "seat_growth",
  "current_arr": 42000,
  "proposed_expansion_value": 12000,
  "total_proposed_arr": 54000,
  "evidence": {
    "value_delivered": {
      "headline": "340 hours saved in Q1 through automated workflows",
      "supporting": ["2847 workflow completions (+22% QoQ)", "75% feature adoption (above segment median)", "78% active user ratio (growing)"]
    },
    "growth_signals": {
      "licence_utilisation": "93% for 45 days -- capacity ceiling reached",
      "organic_spread": "12 new users from Marketing department in last 40 days",
      "credential_sharing": "3 users detected sharing credentials"
    },
    "benchmark_position": "Above average across all metrics. Top quartile in workflow completions",
    "switching_cost": "High -- 3 integrations, 47 trained users, 18 months of workflow configuration"
  },
  "internal_prep": {
    "pricing_standard": 12000,
    "discount_authority": "CSM can offer up to 10% on seat additions without approval",
    "likely_objections": ["Budget timing -- Q2 budget may already be committed", "Want to see the open P2 ticket resolved first"],
    "recommended_approach": "Lead with the Marketing team expansion as evidence of broadening value. Frame seats as making official what is already happening organically. Do not discount proactively -- wait for a pricing objection before offering flexibility.",
    "risk_factors": ["Open P2 ticket on API latency -- resolve before commercial conversation", "CFO not engaged -- may need champion to socialise internally before formal ask"],
    "timing": "After P2 resolution. Target within 2 weeks"
  },
  "customer_summary": {
    "opening": "Your team has outgrown the current setup. 93% of seats are in use and your Marketing team has started adopting organically. We should make sure everyone who needs access has it.",
    "value_frame": "Your team saved 340 hours last quarter through automated workflows -- that is up 22% from the prior quarter. The value is compounding as adoption deepens.",
    "expansion_frame": "Adding 15 seats would eliminate the credential sharing your team is working around and give the Marketing team proper access. The investment is [X] per year.",
    "forward_look": "With the Marketing team onboarded, there is also an opportunity to explore the Advanced Reporting module -- your analytics team has been asking about custom dashboards."
  },
  "requires_csm_review": true
}

Handoff to Human

Confidence and Limitations

• High confidence for evidence assembly -- pulling data from defined sources with structured output is deterministic
• Medium confidence for opportunity sizing -- seat growth is straightforward to estimate, but tier upgrade and cross-sell values depend on customer adoption patterns that are harder to predict
• Medium confidence for objection anticipation -- common objections are predictable, but the specific objection this customer will raise depends on their internal dynamics
• Low confidence for timing recommendation -- when to have the conversation depends on relationship temperature, budget cycles, internal politics, and competing priorities that the agent cannot assess
• Cannot predict whether the customer will say yes. The case is the input; the outcome depends on the conversation
• The customer-facing summary is a starting framework, not a script. The CSM must adapt to the specific relationship and conversation flow

Dependencies

Required:

• bi-expansion-detector (expansion signals that trigger the case)
• pa-value-reporter (value evidence for the case)
• CRM API (contract data, pricing, opportunity management)

Strongly recommended:

• pa-adoption-tracker (adoption depth evidence)
• pa-benchmark-engine (peer comparison for value context)
• bi-account-brief (full account context for preparation)
• ra-stakeholder-mapper (stakeholder coverage for routing the conversation)

Downstream consumers:

• CSM (primary consumer -- uses the case to prepare for and execute the conversation)
• Sales partner (if the expansion involves a formal sales process)
• CRM opportunity (case data feeds into the expansion opportunity record)

References

• references/commercial-frameworks.md -- Framing templates by expansion type, pricing conversation structures, and objection response patterns