Grigoriy Misilyuk
Karolina BendrykCustomer acquisition may be an extremely challenging task. It requires a lot of money and effort. Instead, many companies focus on keeping the existing ones. This approach brings us to the concept of customer lifetime value (CLV). This notion has become one of the most important metrics for modern businesses. CLV proves to be especially relevant in domains like SaaS, eCommerce, subscription services, and digital platforms.
An efficient approach to tracking CLV metrics is the way to understand the profitability of a specific customer. This allows you to measure the impact of your campaigns on clients and establish the most profitable approaches. These are the methodologies focused on revenue generation rather than mere client retention.
Keep reading to get a substantial and detailed breakdown of the following questions:
What is CLV
How to calculate it using different models
How to interpret the numbers
Practical ways to increase CLV
How CLV fits into a broader business strategy.
What is customer lifetime value (CLV)?
To start off, let's clarify what is the lifetime value of each customer. Overall, this notion refers to the total value that a customer brings to the business over the entire duration of your relationship with them. The key point about this notion is that it answers the key question:
“How much is one customer really worth to us over time?”
Overall, customer lifetime value models account for the following:
Repeat transactions
Retention duration
Average spend
Profit margins (in advanced models).
Instead of optimizing for one-off conversions, CLV encourages you to:
Invest in retention and loyalty
Improve customer experience
Balance acquisition costs against long-term returns.
While many businesses keep wondering what is CLV in marketing, its understanding actually helps companies spend marketing budgets more efficiently. A clear vision of CLV also helps businesses scale more predictably and ensure stronger customer relationships, which also translates into enhanced marketing efficiency.
Customer lifetime value formula — the core approaches
There is no single “perfect” CLV formula. The right approach depends on:
Your business model
Data availability
Decision-making needs
Below, we present the most popular formulas applied for customer lifetime value analysis.
Basic CLV formula (simple model)
This formula looks as follows:
CLV = Average Purchase Value × Purchase Frequency × Customer Lifespan
Example:
Average order value = $50
Average purchases per year = 4
Average customer lifespan = 3 years
CLV = 50 × 4 × 3 = $600
This approach is especially useful to early-stage businesses that need quick estimations or just don't have much historical data.
The main drawbacks of this formula:
It ignores costs and profit margins
It fails to consider shifts in customer behavior.
Profit-based CLV formula (more accurate model)
This model focuses on profit, not just revenue.
CLV = (Average Purchase Value × Purchase Frequency × Gross Margin) × Customer Lifespan
Example:
Average order value = $80
Purchases per year = 5
Gross margin = 60%
Customer lifespan = 4 years
CLV = (80 × 5 × 0.6) × 4 = $960
This formula will fit businesses that are focused on real business value and want to align their estimations with financial planning. In fact, many specialists cite it as a perfect fit for budget planning, forecasting, and business intelligence.
Subscription CLV formula (for SaaS & memberships)
Subscription businesses rely heavily on retention, making CLV especially critical.
CLV = Average Monthly Revenue per User (ARPU) ÷ Churn Rate
Example:
ARPU = $40/month
Monthly churn rate = 5% (0.05)
CLV = 40 ÷ 0.05 = $800
This formula is associated with several critical insights. It helps businesses recognize the situations when small churn reductions dramatically increase CLV. In addition, such an approach proves that retention often matters more than acquisition volume.
Predictive CLV models
How to measure customer lifetime value? That's when predictive CLV approaches break in. They are based on using historical behavior and probability to estimate future value.
Expected value CLV formula (simplified concept)
CLV = Σ (Expected Revenue × Probability of Retention) − Costs
In practice, this often involves:
Machine learning models
Cohort analysis
Survival analysis
Example:
A predictive model may show:
Customer Segment A: CLV = $1,200
Customer Segment B: CLV = $300
This allows you to:
Prioritize high-value segments
Personalize offers
Optimize acquisition channels
Predictive CLV is especially relevant to cases that involve large customer bases or systems with rich behavioral data. In addition, it facilitates long-term optimization goals.
Regardless of the case, testing of different approaches and experimentation with formula combinations is useful for getting the most relevant metrics.
How to interpret CLV results
CLV analysis is not just about retrieving useful numbers. It is about using comparison and context for finding the most precise interpretations.
Here are some examples of meaningful interpretations:
When your reports show that lifetime value is high and acquisition costs stay low, it means that your company can grow without strain. You earn more from each user over time. That’s what scalable growth actually looks like.
Low lifetime value paired with high acquisition cost is a warning sign. You’re paying too much to bring customers in. They don’t stay long enough. Or they don’t spend enough to justify the effort. In the long run, this model burns money.
If lifetime value increases over time, that’s usually good news. Customers are sticking around longer. Or they’re buying more. Sometimes both.
CLV vs CAC (customer acquisition cost)
As can be understood from the previous chapter, CLV is typically analyzed in combination with CAC (Customer Acquisition Cost).
A commonly accepted benchmark looks as follows:
CLV: CAC ≥ 3: 1
This means that if you spend $100 to acquire a customer, you should aim to earn at least $300 in lifetime value.
If you spend $100 to acquire a customer, you should aim to earn at least $300 in lifetime value.
What does clv stand for? It is all about understanding the value of each customer, which helps companies build a strategic compass. By optimizing the lifetime value of your clients, you can make smarter decisions across different dimensions of client interactions. By applying lifetime value analysis in combination with other formulas, you can come up with a clearer roadmap for your marketing and advertising practices.
Vlad Isaiko, CTO at TeqBlaze
How to Increase Customer Lifetime Value
Improving CLV doesn’t always mean raising prices. Often, it’s about gradual improvement over time. You can use the following practices to get a higher lifetime value of a customer.
Improve onboarding
Onboarding shouldn’t feel like homework. Creativity is everything for this stage of interacting with the customer. You should understand that clear expectation matters more than polished tutorials — people don’t need promises, they need to know what will actually happen next and how soon it will pay off.
Increase purchase frequency
People rarely buy more just because you ask them to. They buy more when it feels natural. Loyalty programs work best when they don’t scream “loyalty program,” but subtly reward habits users already have. Personalized recommendations should feel like good timing, not tracking. And reminders — whether by email or in-app — shouldn’t sound like nudges from a sales team, but like a quiet tap on the shoulder saying, “Hey, this might be useful right now.” When frequency grows organically, it doesn’t feel like selling at all — it feels like momentum.
Upsell and cross-sell strategically
It is vital to take a smart approach to your selling strategy. This involves bundling complementary products and focusing on the relevance of your messages. The key point is that you should not build your CLV model on pressure. Instead, focus on positive reinforcement and engagement.
Reduce churn
It is important to analyze early churn signals. By collecting feedback and using it for planning, you can define the most efficient plans for reducing churn. Also, engage customers by providing proactive support, which also delivers a positive impact on churn rates.
Deliver a personalized experience
Tailor user experience to the needs and interests of particular clients. To organize this, segment users by behavior and work on tailored content and offers. Also, make sure to reward long-term customers to show them that you cherish loyalty.
How to use CLV in business strategy
One can find customer lifetime value examples for different domains. Let's explore the most efficient ways of implementing CLV into decision-making across different departments.
Marketing
Allocate budget toward high-CLV channels
Stop optimizing for cheap but low-value leads
Sales
Focus on customer quality, not volume
Adjust incentives based on lifetime value
Product
Build features that increase retention
Focus on ensuring long-term engagement rather than short-term usage
Finance
Achieve greater accuracy in revenue forecasting
Justify higher acquisition spend when CLV supports it
Final thoughts
Customer Lifetime Value is more than a metric — it’s a mindset.
By understanding how much your customers are truly worth:
You spend smart
Retain longer
Grow sustainably.
Regardless of the customer lifetime value analysis approach you choose, CLV is a crucial aspect of your strategic planning. It is an excellent way to establish both proactive and reactive practices for long-term growth.
Whether you use a simple formula or a predictive customer lifetime value model, CLV helps you move from transactional thinking to long-term growth. To measure it efficiently, rely on top-notch adtech solutions, such as the ones provided by TeqBlaze.
FAQ
How often should I recalculate customer lifetime value (CLV)?
There are several practical approaches that actually work.
In practice:
Quarterly works well for most stable businesses
Monthly makes sense for SaaS, subscriptions, or fast-moving markets
After major changes (pricing, churn, acquisition channels), it is a must
Think of CLV as a living metric. If your product or customer behavior shifts, your CLV should be allowed to shift with it.
Can CLV be negative — and what does it mean?
Yes, a negative CLV usually means:
You spend more to acquire or serve a customer than you earn back
Discounts, support costs, or churn are eating all the margin
Early-stage growth is masking long-term inefficiency
It’s not a failure — it’s a signal. Negative CLV tells you where the business is leaking value.
What is a “good” CLV-to-CAC ratio?
A widely accepted benchmark in customer lifetime value analytics is 3:1. Meanwhile, there are other options:
2:1 may be acceptable during aggressive growth
4:1 or higher often signals under-investment in acquisition
The “right” ratio varies by industry, margins, and growth stage
Use the ratio as a compass, not a rulebook.
Does CLV work for one-time purchase businesses?
Absolutely — but client lifetime value needs a broader definition here.
For one-time purchase models, CLV often includes:
Repeat purchases over longer cycles
Cross-sell or upsell opportunities
Referrals and indirect value
Even if customers don’t buy often, their relationship with your brand still has measurable value.
What’s the quickest way to increase CLV?
Counterintuitively, it’s rarely about selling more — it’s about losing fewer customers.
Fast achievement of a high CLV score usually comes from:
Reducing early churn
Improving onboarding
Making the second purchase easier than the first
Retention compounds quietly, but powerfully.
What’s the difference between historical CLV and predictive CLV?
The difference is perspective.
Historical CLV looks backward — what customers have already done
Predictive CLV looks forward — what they are likely to do next
Historical CLV is simpler and safer. Predictive CLV is messier, but far more useful for planning and segmentation.
Why does my CLV change significantly when I update just one metric?
Because CLV is a multiplier, not a standalone number.
Small changes in:
Retention rate
Average order value
Purchase frequency
can cascade through the formula and dramatically shift the result.
