Customer Lifetime Value Model
Operations & HR Finance
Quick Answer
Enter LTV and CAC data segmented by customer type or channel. Paste into Claude or ChatGPT. Get a segmented LTV analysis with resource allocation recommendations and growth strategy implications.
What You Get
A segmented LTV model covering LTV by customer segment, channel, and product tier, comparison of LTV/CAC across segments, resource allocation recommendations based on segment profitability, and growth strategy implications.
Who Is This For
Revenue operations teams optimizing customer acquisition strategy, CFOs presenting customer economics to investors, and founders deciding which customer segments to prioritize.
About This Template
A single blended LTV number hides the variation that matters. Your enterprise customers may have 10x the LTV of your SMB customers. Customers from your partner channel may have lower CAC and higher LTV than paid acquisition customers. This template guides revenue and finance teams through building a segmented LTV model, then uses AI to produce analysis of LTV by segment, the implications for resource allocation, and recommendations for focusing growth on the highest-value customer types.
Fill In Your Details
Your company name
e.g. Enterprise: $3500 ARPU, 0.5% monthly churn, $8500 CAC, 75% gross margin
e.g. Mid-market: $850 ARPU, 1.8% monthly churn, $2200 CAC, 75% gross margin
e.g. SMB: $199 ARPU, 4.5% monthly churn, $380 CAC, 75% gross margin
e.g. 5% enterprise, 30% mid-market, 65% SMB by customer count
e.g. sales team can close 8 enterprise or 40 SMB per month, not both at full capacity
Gather these details then use them to fill in the prompt below.
AI Prompts
Generate segmented LTV model
Paste this prompt into Claude or ChatGPT with your segment data filled in.
You are a revenue operations analyst building a segmented customer LTV model. Using the data below, produce a comprehensive LTV analysis by segment. Company: [company_name] Segment 1: [segment_1] Segment 2: [segment_2] Segment 3: [segment_3] Current mix: [current_mix] Growth constraints: [growth_capacity] For each segment calculate: - LTV using (ARPU x Gross Margin) divided by Monthly Churn - LTV/CAC ratio - CAC payback period - Annual gross profit contribution per customer Then produce: 1. Segment Comparison Table — all metrics side by side 2. Revenue Mix Analysis — what percentage of total LTV comes from each segment 3. Highest Value Segment — which segment creates the most value per customer and per dollar of CAC 4. Resource Allocation Recommendation — how to allocate sales and marketing investment given the LTV/CAC data 5. Mix Shift Opportunity — what happens to total company LTV if the customer mix shifts toward higher-LTV segments 6. Growth Strategy Implications — specific recommendations for customer acquisition strategy based on the analysis
Sample Output
This is an example of what AI produces when you use this template.
Segment Comparison Table
Enterprise: LTV $525,000 (($3,500 x 75%) / 0.5%), CAC $8,500, LTV/CAC 61.8x, Payback 3.2 months. Mid-market: LTV $35,417 (($850 x 75%) / 1.8%), CAC $2,200, LTV/CAC 16.1x, Payback 3.5 months. SMB: LTV $3,317 (($199 x 75%) / 4.5%), CAC $380, LTV/CAC 8.7x, Payback 2.6 months. All three segments have healthy LTV/CAC ratios above 3x. Enterprise is 158x more valuable per customer than SMB.
Resource Allocation Recommendation
Despite enterprise customers being 158x more valuable per customer, the SMB segment should not be abandoned — its 8.7x LTV/CAC is healthy and the 2.6-month payback is the fastest of all three segments. The optimal allocation is: concentrate 60 percent of sales capacity on mid-market (best balance of LTV/CAC and volume), allocate 30 percent to enterprise (highest absolute LTV, justifies the longer sales cycle), and let SMB grow primarily through self-serve and product-led motions with minimal direct sales investment. The current 65 percent SMB mix by customer count is likely creating a services burden that exceeds their LTV contribution — analyze support ticket volume and CS time by segment to confirm.