What is a Customer Lifetime Value (CLV)?
Customer lifetime value, or CLV, is a business metric that measures how much a business can plan to earn from the average customer over the course of the relationship. While an initial sale is easy to track and hits the books in real time, the CLV helps you more accurately forecast growth targets and potential for your business by understanding how much your customer will likely spend with you into the future.
Expected Customer Lifetime Value
When considering the expected customer lifetime value and the return on investment (ROI) associated with generating that customer, businesses that include the CLV rather than a one time purchase value understand a much more accurate revenue contribution number per customer. Using CLV paints a complete picture for businesses and helps them make more informed decisions on how to generate new customers and the spend involved in that process.
Equally as important, the tactics to increase expected customer lifetime value inherently increase customer loyalty and satisfaction. Every brand wants a dedicated community that continues to buy from them. In today’s hyper-connected world, every customer wants to feel known by the brands they shop with. By implementing personalized customer journeys brands can keep customers happy, loyal, and buying.
A recent Forrester report explains why CLV is now a “unifying metric” and plays a strategic role in helping firms “pivot toward becoming customer-obsessed”. Acknowledging that there are many ways to calculate expected customer lifetime value depending on business goals, industry, and analytical maturity, the report states that a CLV calculation allows a firm to focus on higher-cost acquisition efforts that include personalization.
Increasing Expected Customer Lifetime Value
Retention is critical to expected customer lifetime value. It will rest on providing a differentiated, personalized experience. A customer who chooses a new behavior such as curbside pickup will continue the behavior – and become a repeat customer – if presented with a seamless experience. A brand that devotes a bulk of its resources to acquiring a new customer by promoting a flashy new curbside pickup service, for example, will have a poor ROI if those customers leave after experiencing friction in the customer journey. According to research from Bain, in conjunction with Harvard Business Review, a 5 percent increase in retention produces anywhere from between 25 and 95 percent increase in profits, depending on industry, service or product. Yet at the same time, up to 80 percent of companies spend over 70 percent of their marketing budgets on lead gen, versus just 30 percent on retention.
The key to flipping this script is a digital-first retention marketing strategy based on a detailed understanding of an individual customer’s journey with a brand through all digital and physical touchpoints. At a macro level, churn is easy to understand – and predict. Poor quality, failed promises, a data or privacy breach, a poor UX, or hidden fees will all make customers flee for the exits. At a micro level, the key to retention for the digital-first customer is demonstrating a deep, personal understanding of likes, dislikes, preferences and behaviors and using this insight to minimize churn factors at the individual level.
A routine website visit, for instance, that displays images and products that are hyper-relevant to a customer’s intent will be more effective than the alternative – a static homepage the same for every visitor. Website personalization could fall under retention or acquisition depending on whether you’re targeting a known or an anonymous record, but the point is that this is the type of personalized experience that customers expect. In a recent Dynata survey, 70 percent of consumers said that they will only shop with brands that personally understand them. (In addition, 82 percent said they expect retailers to accommodate preferences and expectations.)
Personal understanding extends to more than just analyzing behaviors, likes and preferences for the purpose of presenting relevant content. Possible churn indicators could also relate to changes in a customer’s buying patterns like less frequent log-ons, negative feedback to a call center rep, not opening or clicking on an email, etc. Essentially, any and all customer data may provide important clues that a customer is about to leave, and empower a brand to proactively respond with a next-best action relevant for the customer at a slice in time of the individual customer journey.
Expected Customer Lifetime Value and Brand Loyalty
With a deepening trust customers are willing to share even more first-party data. A wealth of first-party customer data allows a brand to provide a relevant experience on any channel, in real time, that is always in the cadence of the customer journey. Every interaction with a customer is an opportunity for a brand to demonstrate that it values the relationship, as demonstrated by the experience it delivers in the moment of interaction.
The value extends beyond the personalization itself. It represents the brand, its products and services and the brand’s own values in terms of how it thinks about its customers. A personalized customer experience shows that a brand cares about managing a customer’s expectations through the collection of first-party customer data.
The brand’s bargain, in return, is improved expected customer lifetime value from customers who remain loyal to a known, trusted partner who seems to know exactly what they want, when they want it, and exhibit respect for them as an individual with unique traits.