As a business owner or marketer, you know that one of your most important goals is to attract new customers. Whether your target market is new customers, current customers, or referral sources who bring in valuable referrals, the key is understanding how long they stay with you. To do this, marketers first measure the lifetime value (LTV), which takes into consideration what they spend on repeat purchases and what they plan to spend on each future purchase. Not all customers are created equal, however. It’s important to remember that LTV is different for each customer and each type of customer.
What is LTV in the Real World?
LTV is a very important metric to understand your customers and figure out how to attract new ones. For example, if a new customer has a healthy LTV of $1,000 (future purchases), they will probably be very loyal to your business. On the other hand, if they have a poor LTV of just $100 (past purchases), it might be better for you to go after a different customer base—if that’s possible at all—because of the potential risks associated with this type of customer.
LTV and Marketing
It is important to note that LTV is not static; it changes throughout a customer’s life, which is where LTV prediction comes into play, most commonly employed through artificial intelligence (AI) and predictive analytics. With this technology, you can learn how customers behave, predict their future behavior, and even take actions based on this understanding. For example, you may be able to predict who might defect from your company and why. Or you can determine which customers are most likely to purchase something over time (e.g., annual or monthly subscriptions) or which sources of customer support are best for growth—a key component of Yield Management.
LTV is a key determinant in determining pricing strategies and goals, marketing costs budgets, product features, and planning (e.g., sales targets or margins). Knowing the LTV for each customer helps determine the ideal goal for long-term relationships with customers. For example, at first glance, an account with a healthy LTV of $1,000 might seem like it’s profitable. However, suppose the business owner can’t make back the cost of acquiring this customer on future purchases within a few months or less. In that case, that account could become unprofitable due to its low return on investment (ROI).
How to Use LTV
It is important to note that LTV is not a one-size-fits-all formula. Customer LTV has different factors that can make a difference, such as:
Likes, Dislikes, And Repetitions
At the beginning of a relationship, customers have emotional reactions about your business or products relative to other companies in their industry. This emotional reaction can lead to revenue over time. For example, a customer with a poor or medium LTV may give you five products at first and then go directly back to her local pizza restaurant once they run out of products to try from your business.
If you’re a startup, new to your industry, offering new or unique products is critical. For example, suppose you’re selling lawn care products that are less popular than other companies in the same industry. In that case, you may want to focus on customers with higher LTVs because they will most likely stay loyal to your company as its product offerings may grow over time. On the other hand, customers who like your business but don’t like your products (even if they are neutral about the product) are likely to churn when facing tough competition.
For instance, customers with a high LTV in a small market might be more loyal to your company for two reasons: because of your content and because you’re an underdog in a small market. In contrast, customers with low LTVs in larger markets may be loyal because they have never had access to your products before or have been fed up with all the competition.
Similarities And Differences
Some customers will become loyal to your business while others will not—this depends on when they originally started using your products. For example, suppose you sell some products that are similar to other popular brands. In that case, customer loyalty will probably come later once they run out of their initial supply and start shopping around for alternatives.
The above factors can make all the difference when predicting which customers are most likely to be profitable over time. For example, imagine a retailer who sells books. You might want to focus on customers with high LTVs for their library because they’ll likely use your product for years.
The Future of LTV
Despite popular belief, LTV is not a perfect science. Even though some online calculators and tools help you determine your customer LTV, there is no way to accurately predict how long it will take you to reach a certain profit level from each customer. However, with advanced technologies like AI and ML (machine learning) getting better every day (and more cost-efficient), there may be more precise ways for businesses to determine CRM (customer relationship management) and profitability over time.
How Businesses Can Use Machine Learning for LTV Calculations
The key to using machine learning for LTV calculations is anticipating how each customer might react to certain actions taken by your business over time. For example, if you want to determine the ideal LTV for a customer, you need to determine her LTV based on how frequently they purchase your products and which products they purchase. By doing this, you can calculate the ideal amount of money that your customer should spend on your product to make you a valuable income every month in exchange for how long they will buy from you.
Other factors that should be taken into account include regional differences and seasonal sales patterns, as well as how often customers buy from your business (i.e., frequency).
As mentioned throughout, LTV is one of the best ways to predict whether or not a customer will stick with your company in the long run. Despite there being other factors that can change depending upon each business, LTV remains the most accurate mechanism in the modern era for sustainable and safe business.