The Ultimate Guide to Customer Lifetime Value

What is customer lifetime value? Customer lifetime value (CLV) is a metric that measures the total revenue a business can expect from a single customer over their entire relationship.

It’s one of the single most important metrics you can track. And for customer experience (CX) professionals and marketers, it’s an absolutely fundamental “North Star” key performance indicator (KPI).

Succinctly put, customer lifetime value helps you identify how much an existing customer is worth to your brand, from a topline perspective. It guides decisions such as:

• Which customers should I invest in acquiring and how much can I spend to do so?
• Which customers should I invest in retaining and how much should I spend to do so?
• Are my offerings and customer experiences succeeding in driving customer loyalty?
• What is the health of my overall marketing, CX, sales, product, and brand strategy & execution?

In this article, we’ll explore how to calculate CLV, why it matters, and strategies to improve it.

Key Takeaways

• Customer Lifetime Value (CLV) measures the total profit expected from a customer throughout their relationship, with key indicators like average order value and purchase frequency being important to help with the calculation.
• In a privacy-first world and the growth of first-party data, balancing Customer Acquisition Cost (CAC) and CLV has become critical for sustainable growth — reducing CAC while increasing CLV with existing customers helps boost profitability.
• Enhancing CLV can be achieved through improved customer experience, effective loyalty programs, and personalized marketing efforts, which all contribute to retention and customer satisfaction.

Understanding Customer Lifetime Value

Understanding CLV is important for making better decisions about marketing, retention, and profitability.
To explain why customer lifetime value is more important than ever, it first makes sense to talk a little bit about customer acquisition and customer acquisition costs (CAC).

Twenty years ago, customer acquisition via digital marketing was a young industry. Marketing efforts were trying to determine on how to make it effective—but remained largely focused on traditional mass media and direct marketing techniques to deliver results.

By about 10 years ago, advances in technology and best practices (in the form of ad tech, display advertising, programmatic marketing, and more) caused digital acquisition marketing to take off. Savvy marketers could cost-effectively acquire customers using targeting and analytics techniques never before seen. It was an exciting time with lots of opportunities, and the most forward-thinking brands seized on it to acquire a whole new crop of customers at a relatively low cost. Customer acquisition was everything.

Today, digital marketing is the premier mode of acquisition for consumer-facing businesses as well as many B2B businesses, especially those who classify themselves as B2B2C and B2SMB. Digital advertising has converged on a handful of major platforms holding near-monopolies (or perhaps real monopolies). Most notable among these are Facebook and Google. At the same time, competition for new eyeballs and new prospective customers on these platforms is intense.

As a result, acquisition costs have been rising at a staggering rate of 25% per year. Today, customer acquisition is extremely expensive.

Compounding the challenge is a steady decline in the quality of acquired customers, which has also been occurring over the last 20 years—driving customer lifetime value lower. With CAC exceeding LTV, the industry is now experiencing an unsustainable experience gap—where the quality of customer experience is insufficient to cement enough customer loyalty to overcome acquisition cost.

Increasing customer acquisition costs along with flat or declining customer lifetime value has given rise to an “experience gap.” Leading brands are using customer-centric strategies to close that gap and increase customer lifetime value.

Why CLV Matters

With the costs of digital marketing out of control, hemming in CAC is difficult. It now costs 5 times more to attract new customers than it does to nurture existing ones. Yet a 5% increase in customer retention can boost profits by 25% to 95%.

So the pendulum has swung to focusing on long-term customer lifetime value. Retaining customers and making them more valuable is now the fastest and most efficient path to growing revenue—driving the initiation of customer-centric transformations across leading brands in nearly every industry. And making measuring, predicting, and growing customer lifetime value more important than ever before.

How To Calculate Customer Lifetime Value

There are a number of approaches to calculating customer lifetime value. Each has its merits based on the way your business operates and the data you have available. The intent of this piece isn’t to go deep into calculation approaches, but rather to work at the conceptual level. So let’s take one of the simplest expressions of customer lifetime value:

Customer lifetime value = average order value (AOV) * # of purchases each year * # years in the customer relationship

Say you sell auto insurance. If the average annual policy costs $1,427, the average customer renews once per year and stays with your brand for an average of 6 years, then your customer lifetime value is $8,562.

You can further segment your CLV calculation to handle how it changes across different types of policies and customers. For instance, you may find that CLV is higher for luxury vehicle owners, high-risk drivers, or policies that use an agreed value method for paying out losses.

If you’re good at segmentation (demographic, transactional or behavioral segmentation), calculating customer lifetime value in this way can tell you how you’re performing overall and in each of your segments, right now. And by linking that performance to the past marketing programs, experiences, and interactions by customer segment, you can understand how your prior strategies, decisions, and actions have impacted customer lifetime value. This is great for knowing where you stand across all your high value customer segments, and why. This type of CLV analysis is sometimes called descriptive (what happened?) and diagnostic (why did it happen?).

While descriptive and diagnostic analysis of CLV is foundationally important, it doesn’t do a lot to help you figure out how to improve your customer lifetime value. For instance, the CLV formula we used above becomes problematic when you take the analysis down to the individual customer. That’s because the customer you’re looking at is still in the middle of their relationship with you—so you’re missing data for the “# of years in the customer relationship part of the formula.”

That’s why the real key to mastering customer lifetime value is based on forward-looking analysis. You need predictive and prescriptive analytics, down to the most granular customer level, all of which then drives customer experience actions taken by your business.

Predicting Customer Lifetime Value

How do you go from understanding “who was my best customer?” to “who will be my best customer?” One technique, known as lookalike modeling, can be especially powerful. In lookalike modeling, you use analytics to identify specific traits and behaviors of your existing and past “most valuable” customers. This can be done through traditional analytics, or with augmentation from AI and machine learning. Then, you use further analytics and AI to identify those traits—and early signals of similar behaviors—in prospective and existing customers, scoring them for the likelihood to become a customer with high customer lifetime value.

These insights are the key to efficiently spending acquisition and customer retention dollars, driving down CAC, increasing CLV, and giving your business a tremendous competitive edge.

Here’s one example: as a result of a series of analytics conducted by ActionIQ and our clients, we discovered that customers who make purchases in more than one channel tend to be significantly more valuable than those who purchase in one channel only. In fact, multichannel customers deliver:

• 2x average annual revenue than other types of loyal customers
• 130% higher annual gross margin than other types of loyal customers
• 50% more brand loyalty, with greater purchase frequency year after year

With this knowledge in hand, our clients then asked “what if I could drive just a 1% increase in my cross channel shopping segment?” The answer: millions in annual incremental revenue. Many of our unique customers went on to build analytics that identify likely cross-channel shoppers and then launched personalized, targeted campaigns and journeys to convert the behavior.

Increasing Customer Lifetime Value

In the previous example, we described how you can increase overall customer lifetime value by targeting, acquiring, and nurturing a high value customer base that is likely to become your most loyal customers.

But what are some of the other ways you can raise loyal customer lifetime value? Here are a few that comprise part of an overall customer-centric marketing strategy:

Increase customer satisfaction. There’s a direct correlation between customer satisfaction and revenue. Focusing on NPS scores, for instance, will boost CLV.

Key Takeaways

• Enhancing Customer Experience. Customers who have a positive experience with your brand will appreciate and be more responsive to offers.
• Implementing loyalty programs. Loyalty programs offer insights into offline purchase behavior and allow you to reward and more personally communicate to better retain customers.
• Personalizing Marketing Efforts. Communications and offers that take into account your customer’s past relationship and current needs are instrumental to cementing a loyal customer.
• Retention Campaigns. Spotting churn signals early and targeting customers with personalized retention campaigns can reduce churn rate and be a big boost to CLV.

Enhancing Customer Experience

Customer experience includes all interactions between a customer and a brand. Providing omnichannel support enhances retention by meeting customers on their preferred platforms. Streamlining the onboarding process can significantly reduce churn.

Personalization and conveying extra value during onboarding are crucial for effective communication. Offering benefits like free expedited shipping and exclusive access helps maintain customer loyalty. Implementing a customer experience management program is vital for monitoring interactions and enhancing loyalty.

Social media significantly impacts customer opinions based on response speed and thoroughness. Ensuring no pain points and maintaining product quality are critical for addressing challenges to customer satisfaction and customer lifetime value.

Implementing Loyalty Programs

A loyalty program encourages customers to return by offering discounts and benefits to promote repeat business. The aim is to keep customers engaged and reward frequent purchases. Loyalty programs can take various forms, such as loyalty cards, apps, or points systems.

Loyalty programs that reward frequent purchases sustain customer engagement. Incorporating refer-a-friend strategies can motivate existing customers and loyal customers to promote your brand. These programs increase the return rate by incentivizing repeat visits.

Examples of customer loyalty programs include airline frequent flyer programs and restaurant punch cards. Implementing such programs can significantly enhance CLV by fostering customer trust and increasing purchase frequency.

Personalizing Marketing Efforts

Using customer data allows businesses to tailor marketing messages, effectively increasing engagement. Personalized in-app messages can enhance user experience and encourage upgrades. Personalization in marketing helps brands connect more effectively with high-value customers by delivering relevant messages that resonate with their interests.

A Customer Data Platform (CDP) enables personalized marketing campaigns based on complete customer profiles. Leveraging customer data allows businesses to create targeted marketing efforts that resonate with different segments, boosting engagement and retention.

Personalizing marketing efforts improves customer experience and helps businesses focus on their most valuable customers, leading to higher CLV.

Retention Campaigns

Retention campaigns help businesses spot churn signals early, like reduced engagement or a drop in purchase frequency. By analyzing customer data, teams can proactively engage at-risk customers with personalized retention campaigns. These campaigns might include tailored offers, relevant content, or special incentives that resonate with the customer’s preferences and history, all aimed at catching back their interest. Not only can this reduce churn rates, but it also maximizes Customer Lifetime Value (CLV) by keeping valuable customers engaged and loyal over time.

Modern Tech for Increasing Lifetime Customer Value

The brands who are most successful at increasing lifetime customer value don’t look at any of the above initiatives as individual campaigns, however. They are part of a much larger marketing strategy to put the customer at the center of everything they do. Achieving this means making an organization-wide commitment to transform your people, process, and technology.

Leveraging technology can significantly enhance CLV calculation accuracy. This section will explore the roles of Customer Data Platforms (CDPs) and AI and Predictive Analytics in improving CLV measurement.

Customer Data Platforms (CDPs)

CDPs serve as a central resource for collecting and organizing customer information from various sources. CDPs consolidate data, providing a comprehensive view of customer interactions.

Utilizing CDPs enhances the ability to analyze and improve CLV by providing holistic insights. Centralizing customer data helps businesses better understand their customers and tailor strategies accordingly.

AI and Predictive Analytics

Artificial intelligence helps organize, manage, and activate data related to customer lifetime value. Modern AI tools assist in CLV tracking by reducing tedious tasks for marketing teams.

Machine learning algorithms can identify patterns in customer behavior, enhancing prediction accuracy and focusing marketing efforts. AI technologies are increasingly used to improve the precision of CLV forecasts, enabling businesses to make more informed decisions.

How ActionIQ Helps Brands Drive Customer Lifetime Value

At ActionIQ, we deliver that technology. And we help with the people and process part, too. ActionIQ’s leading customer data platform (CDP) is designed to help you increase your entire company’s focus on the customer. With a CDP like ActionIQ’s you can:

• Empower all your teams with the analytics and tools they need to understand customer lifetime value, and the strategies they can use to improve it
• Orchestrate authentic existing customer experiences, across all channels tailored to your (potential) best customers’ traits
• Bring together all your customer data, providing your CX professionals (including marketing, service, and sales) with governed access to everything you know about your customers

Real-World Examples of Brands Driving CLV With a CDP

Brands that are executing loyalty programs to increase customer lifetime value are seeing huge results. Below, see two stories from brands who increased loyalty and other key goals with a Customer Data Platform.

How Autodesk Increased Customer Loyalty and a 35% Lift in Renewal Rate

It’s crucial to build on your existing relationships to increase customer lifetime value and maximize the deals you’ve already closed, but if your customer churn rate is high, you’ll be too busy chasing new leads and replacing lost business. So how do you reduce churn?

Thankfully customer data platforms are here to save the day. Not only can your CDP help you recognize churn risks, you can use it to take action on customer insights and deliver personalized experiences that inspire long-term loyalty.

One ActionIQ customer achieved a 35% lift in renewal rate by using their CDP’s lookalike modeling to predict churn risk and proactively engage customers.

Autodesk embarked on a major, multi-year journey from a licensing model to a subscription model. To ensure success, the company needed to create more direct relationships with its customers. While Autodesk had multiple systems it used to interact with customers, the data within them was stored in different places, making it difficult to harness all of it efficiently to create personalized, impactful experiences.

For example, the post-purchase campaigns employed by Autodesk took a one-size-fits-all approach. As a result, users and administrators received the same onboarding messages at the
same time, no matter where they stood in the adoption cycle.

Minimizing your customer churn rate means understanding who your customers are and tailoring your business strategy to suit their wants and needs. That requires a user-friendly customer data platform technology that empowers your business users to quickly and easily access customer data and activate it on all the channels where your customer can be found.

How Lifecycle Marketing Boosted The Washington Post’s Resubscribe Rate by 38%

With their customer 360 built on ActionIQ, The Washington Post launched a strategic lead nurturing program in early 2023 designed to support their goals for the year, designed to engage visitors by instilling daily habits and presenting with offers at the right time to drive conversions.

Their strategy is to deliver relevant content into the hands of new subscribers, to build habits that keep The Post top of mind for readers — with the right offer, at the right time, with a cohesive message across owned channels.

For example, they promote geo-relevant content based on a reader’s location to convert leads, while promoting diversified content to show readers content beyond politics and cross-sell stories.

Rather than letting unsubscribed readers go, The Post designed a strategy to bring those readers back into the fold with seven touchpoints across thirty days, using their behavior and smart offers, powered by ActionIQ. These offers are unique based on quintile, subscriber rate, geo-location and more so no reader is left behind — a journey that generated big results.

Start Boosting Customer Lifetime Value Today

ActionIQ’s technology and experienced team can help deliver in your strategy to grow customer lifetime value to achieve a lasting competitive advantage. For a complimentary consultation with one of our top experts, we invite you to contact ActionIQ today.

Frequently Asked Questions

What is Customer Lifetime Value (CLV)?

Customer Lifetime Value (CLV) is the total profit a business predicts it will earn from a single customer throughout their entire relationship. It’s a key metric for understanding how much to invest in acquiring and retaining customers.

Why is CLV important for businesses?

CLV is crucial for businesses because it enables them to make better decisions, enhance customer experiences, and refine marketing strategies by recognizing the long-term value of their customers. Understanding CLV can significantly drive growth and profitability.

How is CLV calculated?

To calculate CLV, simply multiply your Average Order Value by Purchase Frequency and Customer Lifespan. It’s a straightforward way to understand the value each customer brings to your business!

What are the key metrics for calculating CLV?

To calculate Customer Lifetime Value (CLV), focus on Average Order Value (AOV), Purchase Frequency Rate, and Customer Lifespan. These metrics help you understand the total value a customer brings over their relationship with your business.

How can businesses improve their CLV?

To boost your customer lifetime value, focus on enhancing the customer experience, rolling out effective loyalty programs, and personalizing your marketing efforts. These strategies can really make a difference!