Modeling lifetime value when contracts, churn and tariffs all move independently

Most energy marketers still calculate LTVLTVLifetime Value: the total revenue (or profit) a customer generates throughout their entire relationship with your business.View full definition → as "average revenue times average tenure." That formula quietly assumes every customer behaves like the average customer. In energy retail, that assumption breaks fast, because three variables move independently: contract length, tariff type, and usage band. This lesson shows you how to model LTVLTVLifetime Value: the total revenue (or profit) a customer generates throughout their entire relationship with your business.View full definition → when they don't move together.

Why energy LTVLTVLifetime Value: the total revenue (or profit) a customer generates throughout their entire relationship with your business.View full definition → is harder than subscription LTVLTVLifetime Value: the total revenue (or profit) a customer generates throughout their entire relationship with your business.View full definition →

In a SaaS (Software as a Service) business, LTVLTVLifetime Value: the total revenue (or profit) a customer generates throughout their entire relationship with your business.View full definition → usually depends on one dominant lever: churn ratechurn rateChurn rate is the percentage of customers or revenue lost over a period. It measures how fast a business loses its existing customer base.View full definition →. Energy is messier because value per customer is a moving target, not a fixed subscription fee.

Three forces multiply against each other:

• Contract length: fixed-term deals (typically 12 to 24 months in the UK and much of continental Europe) versus rolling/variable contracts common in deregulated US states like Texas.
• Tariff type: fixed-rate (price locked for the term) versus standing/variable (price can move with wholesale market changes, subject to regulatory price caps in some markets, such as Ofgem's price cap in Great Britain).
• Usage band: low, medium, high consumption households, often segmented by annual kWh (kilowatt-hour) of electricity or therms/kWh of gas.

A customer's LTVLTVLifetime Value: the total revenue (or profit) a customer generates throughout their entire relationship with your business.View full definition → is not "revenue x tenure." It's closer to:

LTV = Σ (expected revenue in period t × probability of retention through t × gross margin) − acquisition and service costs

The complexity is that retention probability itself depends on contract length and tariff type, not just on generic "churn ratechurn rateChurn rate is the percentage of customers or revenue lost over a period. It measures how fast a business loses its existing customer base.View full definition →."

Building the model: three levers, not one

1. Contract length sets the churn clock

Fixed-term contracts create a predictable churn spike at renewal, called the "cliff edge." Retention is high and mechanical during the term (customers usually can't leave without an exit fee), then drops sharply at expiry.

Rolling/variable contracts spread churn more evenly across the year, driven by price comparison sites and switching campaigns rather than contract-end dates.

Modeling implication: don't apply one monthly churn ratechurn rateChurn rate is the percentage of customers or revenue lost over a period. It measures how fast a business loses its existing customer base.View full definition → to both. Model fixed-term customers with near-zero in-term churn plus a renewal-point churn probability (often 25 to 45% at first renewal in mature European retail markets, as an industry estimate for 2025 to 2026). Model rolling contracts with a constant monthly churn ratechurn rateChurn rate is the percentage of customers or revenue lost over a period. It measures how fast a business loses its existing customer base.View full definition → instead.

2. Tariff type changes both margin and stickiness

Fixed tariffs lock in a margin for the retailer but expose it to wholesale price risk if energy costs spike (as seen dramatically in Europe's 2022 gas crisis following the invasion of Ukraine, which pushed many suppliers into losses or insolvency).

Standing/variable tariffs pass more price risk to the customer, which is safer for the retailer's margin but tends to correlate with higher switching rates, since customers on variable rates are more price-sensitive and more likely to be actively comparing offers.

Modeling implication: apply a margin adjustment and a churn multiplier by tariff type. A reasonable planning assumption (estimate, not a universal constant): variable-tariff churn runs 1.3 to 1.8x fixed-tariff churn in competitive retail markets.

3. Usage band drives absolute value, not just percentage

A high-usage household (large home, electric heating, EV charging) generates more margin per year even at the same percentage margin, simply because the revenue base is bigger. Usage band also correlates with dual-fuel bundling: high-usage households are more likely to buy both gas and electricity from one supplier, which itself reduces churn (bundled customers switch less because there's more friction in leaving two contracts at once).

Worked example: dual-fuel vs single-fuel switcher

Assume simplified, illustrative figures (clearly estimates, for teaching purposes, not published market data):

Customer A: Dual-fuel, fixed 24-month tariff, medium usage

• Annual gross margingross marginGross margin is the share of revenue left after subtracting the direct cost of producing goods or services, expressed as a percentage of revenue.View full definition → per fuel: $180 (estimate)
• Two fuels: $360/year combined margin
• In-term monthly churn: near 0%
• Renewal-point churn probability: 35%
• Expected tenure beyond first term: roughly 1.5 additional terms on average given bundled stickiness

Customer B: Single-fuel (electricity only), rolling variable tariff, medium usage

• Annual gross margingross marginGross margin is the share of revenue left after subtracting the direct cost of producing goods or services, expressed as a percentage of revenue.View full definition →: $150 (estimate, lower because variable tariffs are typically priced thinner to stay competitive on comparison sites)
• Monthly churn ratechurn rateChurn rate is the percentage of customers or revenue lost over a period. It measures how fast a business loses its existing customer base.View full definition →: 3% (roughly 30% annual attrition, typical of price-comparison-driven markets)

Simple LTV approximation (undiscounted, for clarity):

Even with a smaller revenue gap than the opening claim suggested in raw dollar terms, Customer A delivers roughly 1.8x the LTVLTVLifetime Value: the total revenue (or profit) a customer generates throughout their entire relationship with your business.View full definition → of Customer B, driven almost entirely by retention structure, not usage or price. Add customer acquisition costcustomer acquisition costCustomer Acquisition Cost (CAC) is the total sales and marketing spend divided by the number of new customers gained in a period. It measures how efficiently you grow.View full definition → (CACCACCustomer Acquisition Cost (CAC) is the total sales and marketing spend divided by the number of new customers gained in a period. It measures how efficiently you grow.View full definition →), and the gap widens further: dual-fuel customers are frequently cheaper to acquire per unit of margin because bundled offers convert better in comparison-site funnels (a commonly cited industry pattern, treat as directional).

LTV:CAC sanity check: A healthy marketing-efficiency benchmark across subscription-like sectors, often cited as a general rule of thumb, is an LTVLTVLifetime Value: the total revenue (or profit) a customer generates throughout their entire relationship with your business.View full definition →:CACCACCustomer Acquisition Cost (CAC) is the total sales and marketing spend divided by the number of new customers gained in a period. It measures how efficiently you grow.View full definition → ratio of 3:1 or higher (see Bessemer's memo on SaaS metrics for the origin of this heuristic, though it's not energy-specific). If Customer A costs $150 to acquire, LTVLTVLifetime Value: the total revenue (or profit) a customer generates throughout their entire relationship with your business.View full definition →:CACCACCustomer Acquisition Cost (CAC) is the total sales and marketing spend divided by the number of new customers gained in a period. It measures how efficiently you grow.View full definition → = 6:1. If Customer B costs the same $150, LTVLTVLifetime Value: the total revenue (or profit) a customer generates throughout their entire relationship with your business.View full definition →:CACCACCustomer Acquisition Cost (CAC) is the total sales and marketing spend divided by the number of new customers gained in a period. It measures how efficiently you grow.View full definition → = 3.3:1, still viable, but far thinner.

Putting it into a simple cohort model

For a real model, don't collapse everything into one blended number. Build a small matrix: contract length x tariff type x usage band, and calculate LTVLTVLifetime Value: the total revenue (or profit) a customer generates throughout their entire relationship with your business.View full definition → per cell. A basic spreadsheet structure:

Segment: [Dual-fuel, Fixed-24mo, High-usage]
  Monthly margin = usage-based revenue × margin %
  Survival curve = 1.0 during term, then apply renewal churn %
  LTV = Σ (month 1..60) margin(t) × survival(t)
  Discount optional: apply monthly discount rate if comparing to CAC payback

Run this for each realistic segment (typically 8 to 16 cells for a mid-size retailer) rather than one company-wide average. This is the same logic used in European Commission energy retail market monitoring reports, which segment household customers by fuel type and contract status precisely because blended averages hide the real economics.

Where this changes marketing decisions

Once LTVLTVLifetime Value: the total revenue (or profit) a customer generates throughout their entire relationship with your business.View full definition → is segment-specific, three decisions shift:

• Acquisition budget allocation: shift spend toward channels that source dual-fuel, fixed-term sign-ups (often direct and price-comparison "bundle" placements) rather than single-fuel variable switchers, even if the latter has a lower headline CACCACCustomer Acquisition Cost (CAC) is the total sales and marketing spend divided by the number of new customers gained in a period. It measures how efficiently you grow.View full definition →.
• Retention timing: concentrate retention campaigns (renewal offers, loyalty tariffs) in the 60 to 90 days before contract-end for fixed-term customers, since that's where the churn cliff sits, not spread evenly across the year.
• Win-back economics: a lapsed dual-fuel customer is worth re-acquiring at a higher CACCACCustomer Acquisition Cost (CAC) is the total sales and marketing spend divided by the number of new customers gained in a period. It measures how efficiently you grow.View full definition → than a lapsed single-fuel customer, because their modeled is structurally higher.

Key Takeaways

• Energy LTVLTVLifetime Value: the total revenue (or profit) a customer generates throughout their entire relationship with your business.View full definition → cannot use a single blended churn ratechurn rateChurn rate is the percentage of customers or revenue lost over a period. It measures how fast a business loses its existing customer base.View full definition →: contract length (fixed-term vs rolling), tariff type (fixed vs standing/variable), and usage band all move independently and must be modeled as separate variables.
• Fixed-term contracts create a churn "cliff" at renewal (industry estimate: 25 to 45% churn at first renewal), while rolling contracts spread churn evenly month to month.
• Bundled dual-fuel customers typically show meaningfully higher LTV than single-fuel switchers, mainly through retention structure, not just revenue size.