A Simple Guide for Customer Lifetime Value

Do you know 76% of companies take Customer Lifetime Value as a crucial part of their business? If your business is not a part of this 76%, you are not considering the CLV as your tool to gain customers and let go of profits. Studies reveal that it is 5x - 25x expensive to acquire a new customer as compared to retaining the old one. For this reason, many small and big business owners spend time and resources to retain their existing customers. One of the best ways to retain your customers and avoid scrambling for new business is by measuring the Customer Lifetime Value. When you calculate the CLV, it helps you to retain valuable customers and generate more revenue over time. Keep reading to learn more about improving your business with CLV.

What is a Customer Lifetime Value

Customer Lifetime Value (or CLV) is the total worth of a single customer to the business throughout their business relationship. However, many confuse CLV with CSAT or NPS (Net Promoter Score), which measures customer satisfaction and loyalty rates. Calculating the CLV will help business owners allocate their resources, time, and effort in the right direction. For instance, a business owner will understand how much he needs to spend to acquire and/or retain new customers.

Calculating CLV helps you to know the probability of the customer spending money on buying your services or products. Furthermore, it reveals how much a customer can spend on the company in his entire lifetime. As a business owner, spending your resources wisely while targeting customers is vital. The customer lifetime value will help you to analyze the customer segments that contribute more to your business. This, in turn, will ensure you get the maximum benefit from your resources.

What are the methods of predicting Customer Lifetime Value

There are two simple methods by which you can determine the customer's lifetime value. These include:

Historical method

The historical method to determine CLV is based on the experience of your business with a particular customer. That is why this model evaluates customer value through past data. The average order value is used to determine if the customer will keep on doing business with your company in the future. However, one thing to remember in the case of historical models is that the model is not efficient enough to predict customer pattern changes. For example, the model will not work accurately if an inactive customer starts buying your products or suddenly, an active customer stops buying.

Predictive method

The predictive method is used to evaluate the future buying habits of existing customers. The model's evaluation is based on how much a customer can spend in the future. Therefore, when a company uses the model, they can easily find out the products and customers that are more valuable. However, predictive models are a little more complicated than historical models, but you can rely on the accurate results it offers.

Due to fluctuations in customer interest in products and services, it is vital to have in-depth knowledge about the customer's lifetime value. Though both methods work to predict the value of a customer, it is crucial to choose the method wisely. First, you need to understand your business needs and preferences and then select the method that serves you with the best results.

Simple way to calculate Customer Lifetime Value

Analyzing the customer lifetime value of the financial project is one of the best ways to make informed decisions. Calculation of CLV can help you understand which customer segment is more profitable than others and which customer is worth targeting. If you are looking to calculate the CLV, you must multiply customer value and average customer lifespan. The result you get after multiplication will directly contribute to the CLV.

Let us look at the simple formula. Then, you can easily calculate the customer's lifetime value.

To calculate the customer lifetime value, you need to use two metrics:

• Customer value, and
• Average customer lifespan.

Formula to calculate CLV

Customer Lifetime Value = Customer Value x Average Customer Lifespan

‍Where,

• Average Order Value = Total Sales / Order Count
• Purchase Frequency = Total Orders / Total Customers
• Customer Value = Average Order Value x Purchase Frequency
• Average Customer Lifespan = Average Number of Days between the first and the last order of a customer.

This will help you to get proper knowledge about how valuable a particular customer or customer segment is for your business.

Calculating Customer Lifetime Value using MS Excel

Calculating CLV using MS Excel is simple. Here are two approaches you can use.

Method 1:

CLV = Frequency x time x gross margin

‍Where,

• Frequency of customer purchases,
• An estimated period when he is expected to be loyal to a Brand,
• Gross margin = Net Sales Revenue - Cost of Goods.

Method 2:

CLTV = Cumulative Net Present Value / New Customers Gained

‍Where,

• Acquisition Cost per Customer = Total marketing costs across all channels / Number of new customers gained.
• Average Orders Per Year = Number of orders serviced / Number of new customers gained
• Average Order Size = Total revenue generated in a particular year / Number of orders serviced
• Total Cost = Total marketing costs across all channels + Cost of Goods
• Gross Profit = Total revenue generated in a particular year – Total Cost
• Assuming a Discount Rate that is a standard in the specific industry, we arrive at Discount Rate.
• Net Present Value = Discount Rate x Gross Profit
• Cumulative Net Present Value = Net Present Value 1 + Net Present Value 2 + Net Present Value 3

A company may sell its products and services in multiple countries via eCommerce platforms. Each country has different marketing platforms, payment gateways, inventories, logistic channels, and target audiences. Hence, businesses are bound to use several tools and applications for each job.

‍Profits/Losses = Sales – Expenses

‍The sales data will come from eCommerce sites for a simple profit calculation. To calculate Expenses, you need to factor in

• Marketing costs coming from platforms like Google AdWords, Facebook Ads, etc.,
• Purchasing stock which might come from inventory management platforms like Olabi,
• All other expenses occurred from accounting software like FreshBooks.

And there will be different data silos for each country. Thus, you must pull all these data from multiple platforms for each country separately in excel. Then, analyze all this data with the expense data and calculate profits. It involves a lot of working hours which cost money, and there is usually a time lag involved, which reduces the accuracy of the analysis and its effectiveness as the data is not analyzed in real-time. Understanding metrics like eCommerce customer lifetime value also depends on having timely and accurate data consolidated in one place. Thus, it becomes necessary to consolidate all the data in a data warehouse. Daton is fully managed, eCommerce-focused data pipeline that seamlessly extracts relevant data from many data sources for consolidation into a data warehouse of your choice for more effective analysis.

Calculating Customer Lifetime Value using Google Analytics

To calculate the CLV in Google Analytics, you need to-

• Sign into your Google Analytics account
• Click on Audience
• Get the Lifetime Value Report

Google Analytics will determine lifetime values for people acquired through different channels and mediums, like social, email, and paid search. In addition, there will be data by page views, goals, events, and trends after customer acquisition. As a result, it will be easier to identify the sources driving the most valuable traffic and corresponding marketing investments that truly deliver good ROI (return on investment). Hence, this Lifetime Value report facilitates business owners to acquire data to understand how helpful certain users and customers are to their businesses based on their lifetime performance.

Factors Influencing Customer Lifetime Value

Several operational and behavioral levers determine how CLV moves over time. Understanding and controlling them separates high-performing brands from those guessing at ROI.

1. Average Order Value (AOV)

Higher basket sizes increase CLV instantly, but only if margins hold. Saras Pulse connects order-level sales, discounts, and COGS, helping teams test pricing, bundling, or cross-sell tactics that lift AOV without crushing contribution margin.

2. Purchase Frequency

Repeat orders compound LTV. Saras Pulse’s cohort dashboards visualize purchase cadence and rebill percentage, revealing when engagement drops and which campaigns reignite activity.

3. Customer Retention Rate / Lifespan

Every extra month a customer stays active improves payback. Subscription and churn analytics in Pulse track cancellation reasons, retention by SKU, and at-risk cohorts, enabling proactive win-back flows.

4. Customer Satisfaction & Experience

Fulfillment delays and poor support quietly erode CLV. Pulse integrates shipping, CSAT, and ticket data so teams can tie operational pain points directly to churn or lifetime spend.

5. Loyalty Programs & Engagement

Tiered rewards, referrals, and exclusive access extend loyalty loops. Pulse measures the revenue and margin lift per loyalty tier, linking engagement data from CRM and campaign tools to purchase outcomes.

6. Customer Acquisition Cost (CAC)

High CLV means little if CAC balloons. With Saras Pulse’s attribution dashboards, marketers can compare CAC-to-LTV ratios by channel, creative, or geography, ensuring growth stays ROI-positive.

Perfect — you’re right. The seven strategies section needs more substance — more why it matters, how to execute, and what to measure — not just quick bullets.

Below is the rewritten and expanded version of Part 2, with richer context, verified logic (no filler stats), and a consistent “data-as-ROI / attribution clarity” tone.

Why is Customer Lifetime Value important for your business growth

In short, yes. As it determines the value of the customers associated with your business, CLV plays a significant role in business growth. CLV will help you analyze which products you should sell, how you should serve your customers, and how you can optimize your business. Analyzing these conditions will help you improve the customer lifecycle with your business and the bottom line of your business. It allows you to double your sales, increase profits and boost the return on investment. Still on the fence about why you need to measure CLV for your business?

Impacts your Profitability

Measuring CLV can directly impact the profitability of your business. This is so because acquiring new customers is more expensive than retaining the existing ones. When you acquire a new customer, you need to pay the cost of the acquisition every time. This, in turn, lowers your profit and reduces the sale margin. On the contrary, when an existing customer buys your product, you do not have to pay for anything. Thus, your business will get the entire profit from the sale, which contributes to high ROI.

Keeps your Cash Flow Steady

Another important reason for CLV is that your business will get a steady cash flow. No matter the circumstances, your loyal customers will shop from your business. Knowing that a part of the money will come into your business helps you cover up your due payments and maintain a steady cash flow.

Boost Customer Loyalty

CLV is one of the most important ways to keep your customer happy and satisfied. This is because CLV helps the business owner to understand the customer journey and improve it to retain customers. When you know where your potential customers are churning, it helps you to optimize and personalize the experience given to them. When you let your customers enjoy shopping with your business, they will come back.

Effective Marketing Strategies

Business owners can use CLV as their segmentation strategy. The analysis of CLV helps you to identify the customers that bring profit to your business. Once you understand the business value that each potential prospect brings, it assists you in personalizing customers' experience and improving resource usage. With CLV, you will get an idea about how to use different strategies to turn your low-level and mid-level customers into long-term loyal people.

As per the study by Signal mind, the profitability of the sales made by a new customer is around 5-20%. On the other hand, the profit is 60-70% when an existing customer shops for your products. This drastic difference in profitability proves the total value of CLV for your business. When you retain customers with the help of marketing strategies, tailor-made solutions, and personalized customer service, the advantage directly shows up in your business's bottom line. So, regardless of whether you are a small-scale business or own a large enterprise, calculate customer lifetime value to improve your business.

What Is a Good Customer Lifetime Value

There isn’t a single “good” CLV number; what matters is the ratio between CLV and CAC, and how that ratio evolves as you scale.

A strong benchmark for sustainable growth is when:

• Your LTV:CAC ratio consistently exceeds 3:1,

• You achieve payback within 90–120 days, and

• Your contribution-margin CLV (not gross revenue CLV) grows faster than top-line sales.

CLV should rise faster than CAC as your data systems mature.

Saras Pulse makes that progression visible by tying together marketing, sales, and retention data in one place. Operators can track how campaign-level CAC translates to lifetime profitability and identify which channels or cohorts deliver true margin-positive growth.

How do different teams find Customer Lifetime Value useful?

Calculating and monitoring customer lifetime value is essential for every business. It helps to identify high-value customers for companies to focus on and enhance revenue coming from these customers by providing them with facilities like better deals, offers, and better customer support to increase their sales further. Let us see how teams in a company find CLV helpful:

Administration

CLV comes into play while calculating future projections when a business is considering expansion. A Healthy CLV indicates a decent assured company and better ROIs (return on investment), indicating the best time to expand sustainably, helping the CXOs take the right call.

Marketing

The goal of determining lifetime value for any marketer is to ensure that the marketing campaigns are profitable. CLV indicates probable ROIs of a marketing campaign. It helps Marketers optimize budgets in each campaign and clarifies how much to invest in which customer segment.

For instance, a marketing manager is planning a paid campaign on Google. She estimates the number of clicks the ad will generate within a particular timeframe based on keyword trends. She also has an idea estimates the bounce rates on her landing page and the number of leads generated from those clicks. This will help her clarify the number of customers she can expect from this Google Campaign. Now using CLV, she can get a projection of the expected revenue/profits that will be generated from this campaign, enabling her to easily calculate ROI, optimize her budgets accordingly, and set benchmarks for each campaign.

Production

CLV calculations are essential to the production team as well. For example, a Dropping CLV trend after a change in production materials might indicate a quality issue. But, again, businesses can do cost-cutting and improve margins if CLV is unaffected.

Logistics

The shipping team can evaluate the efficiency of each shipping partner by the CLV of their serviced customers. CLV can decrease due to

• Delayed product delivery,
• Damaged products,
• Poor packaging,
• Poor return policy,
• Lack of proper shipment tracking.

Sales

Understanding a Customer’s CLV is an essential insight for Sales Teams. The sales pitch would be different for a high-valued client.

For example, a sales manager would look to include many value-added services to clients with high CLV to maximize their revenue. While with clients with lower CLV, the sales pitch would be more in tune with retaining the customer and offering them offers and discounts.

Customer Support

CLV is the most important for customer support teams. Since CLV increases with returning customers, that happens when customers are satisfied. CLV can measure Customer Support Efficiency and help identify high-value clients so businesses can provide more focused and prioritized support. For example, a customer support manager can look at the CLV trends of customers serviced by an executive to judge their efficiency. He can identify High-Value Clients & allocate the best executives to handle them.

Related Read: Amazon Customer Lifetime Value

Limitations of Customer Lifetime Value

Customer Lifetime Value (CLV) is a powerful metric, but it’s not perfect. DTC eCommerce brands often over-rely on static or incomplete models that paint a distorted picture of profitability.

Here’s what usually goes wrong and how to fix it.

Blind spots in attribution:

Most CLV models still depend on last-click data, ignoring the multi-touch journey that drives real conversions.

How to Fix: Use unified attribution models to connect first-party, paid, and partner channels. Saras Pulse lets teams toggle between first-touch, last-touch, and multi-touch views, revealing which channels truly shape high-LTV cohorts.

Static snapshots, no behavioral depth:

‍Traditional CLV assumes every customer behaves the same after purchase. Reality: purchase frequency and churn vary by segment.

How to Fix: Replace static averages with dynamic cohort analysis. Saras Pulse tracks rebill percentage, repeat rate, and churn at cohort level, so retention plays are based on live data, and not last quarter’s assumptions.

Margin-blind calculations:

‍CLV without contribution margin is just math. Gross revenue will not show you the exact profit.

How to fix: Tie CLV to unit economics. Pulse’s SKU- and cart-level contribution-margin dashboards expose which products and channels actually make money after discounts, shipping, and returns.

Poor data hygiene:

Duplicate customers and mismatched orders can skew lifetime value.

How to Fix: Saras Daton pipelines feeding Saras Pulse clean and normalize data across Shopify, Amazon, Meta, and CRM sources, creating a single source of truth for lifetime analysis.

Ignoring external factors:

Promotions, delivery delays, or product issues distort real value.

How to fix: Integrate fulfillment and CX metrics into CLV views. Pulse merges shipping SLAs, CSAT, and review data to correlate experience quality with spend and retention.

When these gaps close, CLV stops being a vanity metric and becomes a profitability compass.

7 Strategies to Improve Customer Lifetime Value

CLV isn’t driven by loyalty programs or email flows alone. It’s a reflection of how well you understand and act on your customer data. Here’s how high-performing brands actually move the needle.

1. Launch Personalized Loyalty Programs

Loyalty only works when it’s rooted in behavior, not blanket discounts. The goal is to reward profitable engagement; i.e., customers who buy more frequently, with better margin profiles.

• Use tiered programs to differentiate high-value customers from occasional buyers.

• Reward behaviors that deepen relationship value (referrals, subscriptions, reviews, etc.) instead of purely transactional incentives.

• Use Saras Pulse’s cohort and contribution-margin data to validate whether loyalty members deliver higher AOV or repeat frequency, not just more orders.

2. Proactively Reduce Churn with Predictive Analytics

Most churn happens quietly; between inactivity and actual unsubscribe. By combining transaction recency, support tickets, and fulfillment data, you can detect at-risk customers before they lapse.

• Track early warning signals such as declining purchase intervals, negative CSAT, or increased refund rates.

• Segment at-risk cohorts by reason (e.g., price fatigue vs. product dissatisfaction).

• You can use Saras Pulse’s churn diagnostics dashboards to model how these signals impact retention and lifetime contribution.

When teams can visualize churn probability by segment, win-back campaigns become surgical instead of random.

3. Enhance the Post-Purchase Experience

Most brands obsess over conversion and forget that the real LTV engine starts after the sale. Post-purchase experience drives second-order revenue, referrals, and reviews — the backbone of organic growth.

• Map the full post-purchase funnel — shipping, delivery, onboarding, product setup, and follow-ups.

• Integrate logistics and CX data so you can track how delays or fulfillment errors affect repeat purchase rates.

• Saras Pulse combines fulfillment SLAs, shipment timelines, and feedback ratings to expose weak points in the customer journey.

4. Use Customer Segmentation for Targeted Marketing

Segmentation turns raw data into precision marketing. Instead of treating all buyers equally, focus on value cohorts — customers whose contribution margin justifies deeper engagement.

• Create segments based on recency, frequency, monetary value, and acquisition channel.

• Use Pulse’s Customer 360 to overlay marketing data (campaigns, offers, messaging) on purchase patterns.

• This enables you to tailor creatives and timing — for example, sending win-back offers only to customers with proven high LTV profiles.

With data clarity, personalization becomes ROI-driven, and not just an automation exercise.

5. Provide Omnichannel Support

Today’s customer might complain on Instagram, reorder via email, and request a return through chat; all within 24 hours. Each of these touchpoints influences perceived value and retention.

• Centralize customer interactions across all platforms to maintain context.

• Use Saras Pulse’s unified CX datasets to connect support outcomes (resolution time, sentiment) with repurchase rates.

• Identify which channels drive the fastest resolution and the highest retention lift.

Brands that maintain continuity across support channels consistently see higher loyalty; not because they reply faster, but because they remember context.

6. Remove Friction from the Onboarding Journey

The first experience sets the tone for the entire relationship. When onboarding feels effortless, conversion-to-retention rates skyrocket.

• Analyze the first 30–60 days after purchase: unboxing feedback, product usage, and early cancellation trends.

• Saras Pulse tracks subscription churn and return reasons by SKU, helping teams see where friction actually exists — confusing product setup, missing information, or poor initial engagement.

• Addressing these early pain points typically boosts repeat order probability far more than adding discounts later.

For SaaS or subscription models, a frictionless start is often the most decisive LTV driver.

7. Transform Unhappy Customers into Advocates

No brand escapes unhappy customers; the question is how you respond. Negative experiences, when handled transparently, can convert into long-term advocacy.

• Use feedback loops: connect support tickets, CSAT, and purchase history to identify high-value detractors.

• Prioritize outreach to those customers before they churn.

• Pulse integrates review data, support interactions, and order history, showing how issue resolution affects subsequent spend or referrals.

Turning one frustrated repeat buyer into an advocate often generates more lifetime revenue than acquiring five new low-value customers.

Conclusion

If you are a business owner looking to get business insight to improve profitability, you must focus on calculating customer lifetime value. Business owners who wish to scale their business in the hyper-competitive world should consider CLV while mapping out the marketing strategy. Having the necessary knowledge about your products and customers can help you outrank your rivals and stay ahead by retaining customers. The sooner you understand the benefits of CLV for your business, the better it will be to hedge against the competition.

Calculating CLV requires pulling data from multiple reports—a manual, error-prone, and time-intensive process. That’s where Saras Analytics comes in. With our eCommerce-focused data pipeline, Daton, and advanced ML/AI solutions, you get accurate data exactly when you need it. Paired with Pulse, our analytics platform, you can unlock cohort analysis, CLTV insights, RFM segmentation, and product-level profitability in a single dashboard. Talk to our data consultants today and discover how reporting can be transformed into a strategic growth engine with a 360° view.