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For a business to set sales and customer acquisition targets, understand what it needs to reach them, and set its marketing and sales budgets, it needs to be able to assess the long-term value of its customers. Calculating the customer lifetime value (CLV) shows businesses how much revenue they can expect to receive from a customer over their total lifetime as a customer.
What is Customer Lifetime Value (CLV)?
Customer lifetime value (CLV) is the total amount of revenue or revenue a business can expect to generate throughout the customer lifecycle.
It measures both the value of repeat purchases from existing customers and how much new customers are worth to the company.
CLV looks at all elements of customer purchasing behaviors, including spending levels, frequency, and churn rate.
The customer lifetime value calculation also accounts for the cost of obtaining and servicing customers, as well as sales and other revenue that customers generate over their relationship with a business.
Customer lifetime value (CLV) provides businesses with a comprehensive understanding of the long-term value of their customers.
This information can be used to set sales, marketing, and customer service objectives and budgets that are tailored for each customer segment or individual customer.
- CLV: The abbreviated term for “customer lifetime value.”
Factors that Affect Customer Lifetime Value
Numerous factors can impact CLV, and small changes to any of them can make significant differences in the overall calculation.
- Product/Service Quality: High-quality offerings will produce happier customers who are more likely to stay loyal over time. This leads to higher repeat purchases and increased loyalty—both elements that increase CLV.
- Customer Acquisition Cost (CAC): Companies must find ways to reduce their CAC in order to increase CLV, as it will take time for any new customers to start generating revenue.
- Retention Rate: When organizations can retain their customers, they spend more money over time, increasing lifetime value. They also advocate for the brand and help bring in new customers, which brings in more customers.
- Customer Churn: Customers who stop doing business with or buying from a company earlier than expected lead to lower CLV. Organizations must find ways to reduce their churn rate to maximize CLV.
- Brand Loyalty: Building brand loyalty is key to increasing CLV since loyal customers tend to generate more revenue than those who are not loyal to one particular company or brand.
- Customer Experience: PwC’s Future of CX report revealed that a single, unsatisfactory experience can be enough to send one-third of customers away from even their favorite brands. And 92% will completely abandon any company after two or three negative interactions. To retain customers (and therefore increase CLV), brands must provide excellent customer experiences.
Most of these factors are qualitative, but they can still be measured and reported with quantitative metrics.
Advantages of Addressing Customer Lifetime Value
Customer lifetime value (CLV) is an important metric that is related to both customer retention and customer acquisition costs. Increased prices can lead to higher CLV if customers perceive the value of the product or service to be worth the cost.
When organizations take CLV into consideration, they can make informed changes to their sales, marketing, and customer service strategies. By using CLV to guide budget allocation and resource management decisions, they can focus their efforts on initiatives that attract and retain the highest-value customers.
With a clear understanding of the CLV, organizations can set objectives and goals that are tailored to each individual or group of customers. This increases the likelihood of achieving tangible returns on investment (ROI) in marketing campaigns, product offerings, and customer service strategies. Ultimately, CLV allows organizations to make data-driven decisions that lead to increased customer satisfaction, loyalty, and revenue.
Challenges of Customer Lifetime Value
With so many moving elements that impact CLV, managing the customer lifecycle poses several major challenges for businesses.
CLV requires large amounts of customer data, collected and aggregated from numerous sources. This can be both costly to collect and cumbersome to manage.
Making sense of all the data collected is just as much of a challenge. Organizations must be able to measure and interpret it in order to gain actionable insights that can inform their strategies.
Estimating Future Revenue
Predicting future revenue based on past performance is difficult, and predictions can be inaccurate. This makes it difficult to accurately gauge the potential profitability of a customer.
Every organization does business differently, and “value” is a bit ambiguous. In addition to financial value, there is also intangible value (such as loyalty and advocacy), which is hard to measure but translates to increased value in the customers who provide it.
Increasing prices can increase CLV, but businesses also need to keep their pricing competitive to attract and retain customers. They must also offer unique features, services, and experiences that attract customers and promote loyalty over the long term.
Making Informed Business Decisions
Even with the right data, the ability to make sense of it, and the right pricing strategy, organizations still need to ensure that they make informed decisions about their customers.
This requires a holistic understanding of customer behavior, preferences, and needs. And it goes beyond understanding customer lifetime value in financial terms.
Placing Value on the Metric
CLV isn’t the only metric to track. Some businesses are successful, but only make a few sales to each customer. As such, they may not have a high CLV, but they can still be profitable.
Organizations should place value on CLV, but also look at other metrics that can provide valuable insight into their operations and customer relationships.
Measuring CLV is not as difficult as it looks. But it does require a comprehensive approach that takes into account the whole customer journey and the organization’s data.
Customer Lifetime Value Formula
While there is no universal formula to calculate CLV, the following formula provides a basic approach to estimating customer value:
Start by calculating the average order value.
Average Order Value = Total Revenue ÷ Number of Orders
Then, calculate the purchase frequency rate.
Average Purchase Frequency Rate = Total Number of Orders ÷ Number of Customers
Now, you can calculate customer value.
Customer Value = Average Order Value x Average Purchase Frequency Rate
Finally, determine the CLV.
Customer Lifetime Value = Customer Value x Average Customer Lifespan
Metrics That Impact CLV
Since revenue sits at the top of the CLV formula, customer lifetime value is heavily influenced by the same elements that impact revenue. This includes several factors, both quantifiable and qualitative.
Quantifiable metrics include:
- Purchase frequency
- Average order value (AOV) or average deal size
- Customer acquisition cost (CAC)
- Churn rate
- Customer retention rate
- Gross margin
- Cost of goods sold (COGS)
Qualitative metrics include:
- Brand perception and sentiment
- Customer satisfaction
- Customer loyalty
- Customer engagement and experience
With so many different pieces, measuring CLV can sometimes be tricky. But each of these factors is actually somewhat easy to track with the right software.
Customer Lifetime Value Models
There are two primary models for measuring customer lifetime value: predictive and historical.
Predictive Customer Lifetime Value
Predictive CLV models use predictive analytics to forecast future customer lifetime value. Predictive models allow organizations to analyze data and predict customer behavior based on past performance.
The predictive CLV model is most useful when businesses need to decide whether to acquire a customer or allocate more resources to an existing one. This is typically done at scale (i.e., on a segment-by-segment basis) rather than individually.
Some CRM software and marketing automation tools include predictive CLV modeling capabilities.
Historical Customer Lifetime Value
The historical model uses past customer performance data to measure customer lifetime value. It allows organizations to identify patterns in customer behavior, such as how often they purchase or the average amount they spend.
By tracking metrics like purchase frequency and average order value, businesses can get a better understanding of their customers and make decisions accordingly.
The historical customer lifetime value is considerably easier to measure. And since it relies on existing customer data, it is more accessible to all organizations.
However, its limitation is that it can’t predict future customer behavior as well as an analytics engine can.
Ways to Boost Customer Lifetime Value
Customer lifetime value is rooted in revenue, which customers are the primary source of. Boosting CLV is all about finding ways to drive revenue growth through the customer.
1. Improve the customer experience.
Creating a better customer experience is the most effective way to improve CLV because it improves customer retention while also driving increased customer spending.
Rather than improving the amount of revenue over a time period or the purchase frequency, positive customer experiences do both.
A third (and less commonly discussed) benefit of a great customer experience is the ability to increase word-of-mouth referrals. 72% of customers will share a positive experience with six or more peers, and 13% will do so with 15 or more.
New revenue from referrals can be directly attributed to the customer who referred them to the business, increasing CLV.
2. Offer personalized discounts and promotions.
Sales discounts encourage existing customers to purchase more, while promotions (like referral programs) can bring in new customers.
By using customer data to personalize discounts and promotions, businesses are able to provide a better experience for them while also driving revenue growth.
Organizations incentivize early payments with dynamic discounting, reward loyalty through personalized offers, or offer free shipping on certain products or orders above a certain amount.
3. Switch to a recurring revenue model.
The best revenue is predictable revenue — it’s what allows businesses to forecast their future performance accurately.
A subscription-based, recurring revenue model helps organizations generate predictable income month after month by charging customers on an ongoing basis.
Subscription models are also beneficial because they encourage customers to stick around—customers who sign up for a subscription plan are more likely to remain loyal and less likely to churn
If possible, companies should also provide the option for an annual subscription, as annual recurring revenue guarantees income for an entire year and is more cost-effective for long-term customers.
4. Increase customer loyalty and engagement.
In a recent KMPG survey, nearly all respondents (96%) acknowledged that customer loyalty programs should be improved, while 75% expressed they would switch companies if presented with more valuable rewards.
One of the best ways to improve loyalty is to focus on customer engagement—a key driver of loyalty.
There are several ways sales, marketing, and customer success teams can improve customer engagement:
- Engaging target customers through email
- Providing helpful content and marketing messages
- Talking to customers on social media
- Offering personalized incentives and rewards
- Sponsoring events (e.g., webinars, summits)
- Asking for customer feedback and opinions via surveys
The residual impact of these efforts is an increase in the average revenue per customer, which leads to a higher CLV.
5. Upsell and cross-sell more effectively.
Increasing the average order value is one of the quickest and most effective ways to increase CLV.
An upsell strategy many companies use is to offer customers a more expensive version of their product. They may also offer a low-cost, limited-time version of a product with the intention of converting them to a more feature-rich version.
6. Develop better customer segmentation strategies.
Customer segmentation is the process of grouping customers into distinct groups based on shared attributes or preferences that can be used to target them with relevant marketing messages or offers.
By segmenting customers according to their needs, businesses can better tailor their products and services to meet each group’s individual needs, resulting in greater retention.
7. Leverage AI and predictive analytics to understand customer behavior.
Companies that have the budget for robust, AI-driven analytics software should strongly consider buying software that helps them gain further insights into customer behavior.
They can use this data can be used to inform marketing efforts, optimize sales processes, identify high-value customers, and build more personalized relationships with customers.
Using Sales Technology to Improve CLV
Digital sales transformation is all about using technology to grow revenue, increase retention, and improve the customer experience through better targeting, sales efficiency, personalization, and accurate reporting.
By investing in the following sales technology, businesses can quickly and easily identify potential opportunities to reach out to customers and engage with them on a more meaningful level.
Configure, Price Quote (CPQ)
CPQ software helps streamline the quoting and ordering process by automating complex pricing rules, managing discounting policies, and offering upsells and cross-sells.
Most CPQ platforms offer automated proposal generation capabilities, insights from CRM that improve targeting accuracy, and data-driven analytics to help with forecasting.
For customers, the most critical benefit of CPQ is the streamlined buying experience. Rather than waiting days or weeks for a proposal, buyers can receive a personalized one in minutes.
Digital Sales Room
A digital sales room centralizes communication between buyers, stakeholders, and sellers.
Emailing back and forth, waiting days for replies, and having difficulty getting different decision-makers on the same page are all issues that a digital sales room can solve.
The platform also allows sellers to provide customers with real-time notifications and messages, which helps increase buyer engagement and improves the likelihood of closing the deal.
Subscription management systems make it easier for companies to manage their customer base.
They can handle payment processing, automate renewals and upgrades, and provide customers with an easy way to view and modify their subscription details in one place.
This makes it easy for them to pay for the product, change their plan, or upgrade to a more comprehensive version with less friction.
Billing software helps companies track and manage their customer accounts.
It can be used to automate billing processes, store customer data securely, generate invoices, process payments, and provide customers with visibility into their purchase history.
Removing the error-prone aspects of billing ensures accuracy (e.g., customers won’t be double-charged or overcharged), which builds trust and loyalty. It also makes it easier to accept multiple forms of payment, ensuring they won’t leave for another company that accepts their preferred method.
People Also Ask
What is the opportunity-to-cash process?
The opportunity-to-cash process can be broken down into four key steps: opportunity identification, opportunity capture, opportunity validation, and opportunity conversion.
At the first step of opportunity identification, businesses must identify potential opportunities and how they can be maximized for their benefit. This includes analyzing customer data to identify trends in purchasing behavior and evaluating the potential for new products or services that may interest customers. Once an opportunity has been identified, businesses must then capture it through effective marketing strategies such as targeted campaigns or promotional activities.
The next step in the opportunity to cash process is validating the opportunity by assessing factors such as customer demand, pricing, and potential competition. Validation also involves researching competitors’ offers and analyzing how they position their offerings compared to similar products or services other businesses offer. Finally, businesses must convert their opportunity into actual cash flow by negotiating deals with customers and collecting timely payments.
Overall, understanding how the opportunity-to-cash cycle works helps businesses maximize their profits while minimizing risks associated with uncertain outcomes of sales cycles. Knowing which steps are involved in this process also helps them develop better strategies for capturing opportunities before others do and quickly converting them into actual cash payments.
What is the difference between order-to-cash and opportunity-to-cash?
The primary difference between order-to-cash and opportunity-to-cash is the scope of activities being measured. Order-to-cash covers the entire process from a customer placing an order through to the payment being received, while opportunity-to-cash measures progress from lead generation or opportunity identification, through to payment.
The order-to-cash process can involve many different activities, such as creating quotes, negotiating prices, issuing invoices, and collecting payments. This is the traditional sales cycle and business model used by most companies. Opportunity-to-cash focuses on understanding how prospective customers are identified, qualified, and then closed into customers who will make purchases. The opportunity-to-cash cycle also includes activities such as forecasting sales opportunities based on past performance and market conditions, as well as tracking lead conversion rates and win rates.
By understanding both cycles, it is possible to gain deeper insights into customer behavior which can be used to improve sales strategies and processes, resulting in increased overall efficiency. For example, if a company has a high opportunity-to-cash ratio but a low order-to-cash ratio then this could indicate opportunities for upselling after the initial purchase has been made. Understanding the differences between these two cycles can ultimately help businesses optimize their resources for maximum return on investment.
How are PIM and PxM related?
PIM focuses on managing product data such as descriptions, images, prices, etc., while PxM is more focused on delivering a complete customer experience from product discovery to purchase. The PIM system manages product content across multiple channels, while the PxM system provides an integrated customer experience that includes product selection, customization, pricing, payment, and delivery.