What is Customer Value Maximization?
Customer Value Maximization is the set of techniques and actions used to entice customers to increase the frequency and amount of their transactions, and to increase the length of time they remain active customers of a business.
Once a company has acquired a new customer, the ultimate goal of marketing and retention efforts is to maximize the revenues that the customer generates for the company (assuming a stable relationship between revenue and profit). The three primary factors which contribute to the total revenues that any particular customer will generate are time (how long the customer remains an active customer), purchase frequency (how often the customer purchases something from a company) and monetary value of purchases (how much money the customer spends with the company). Thus, maximizing the value of the customer to the business means maximizing the time × purchase frequency × monetary value equation.
Customer LTV Excel Calculator Template
How to Achieve Customer Value Maximization
Providing customers with the products or services they seek, at competitive prices and with terrific customer service is obviously the best way to ensure that a customer remains with a company for the long term and continues to buy from it. However, there are always specific actions available to a company which will encourage customers to stick around longer and spend more. The challenge is knowing which actions to apply to which customers and when to do so for maximum results.
Optimove introduces customer value maximization modeling methods which are far more advanced and effective than anything else available, manual or automated. By combining a number of technologies into an integrated, closed-loop system, marketers enjoy a highly accurate customer value maximization machine in an easy-to-use Web application:
Optimove achieves market-leading customer value maximization modeling with the combination of the following capabilities:
- Customer segmentation – It is important to segment customers into small groups and address individual customers based on actual behaviors – instead of hard-coding any pre-conceived notions, making assumptions of what makes customers similar to one another or looking only at aggregated/averaged data (which hides important facts about individual customers).
- Tracking customers over time – It is critical to follow how customers move among different segments over time (i.e., dynamic segmentation), including customer lifecycle context and cohort analysis – instead of just determining in what segments customers are now without regard for how or when they arrived there.
- Accurate prediction of future customer behavior (e.g., convert, churn, spend more, spend less) – One should always use predictive customer behavior modeling techniques – instead of just looking in the rear-view mirror of historical data.
- Customer lifetime value (LTV) – Customer value maximization modeling should be based on the use of advanced calculations to determine the customer lifetime value (LTV) of every customer and to base decisions on it – instead of looking only at the short-term revenue that a customer may bring the company.
- Marketing action optimization – The marketer or retention expert should know, based on objective metrics, exactly what marketing actions to do now, for each customer, in order to maximize the long-term value of every customer – instead of trying to figure out what to do based on a dashboard or pile of reports.
One way to think of the difference between conventional approaches and the Optimove approach is that the former is like a customer snapshot whereas the latter is a customer animation. The animated view of the customer is far more revealing, allowing much more accurate customer behavior predictions and, thus, customer value maximization.
Customer Lifetime Value Excel Calculator
Download this Excel-based template for a fast and easy method to calculate your customers’ lifetime value.
Frequently Asked Questions
How does Optimove calculate customer lifetime value?
Optimove’s customer LTV forecasting technology combines two technologies:
Continual dynamic micro-segmentation – intelligently and automatically segments the entire customer base into a hierarchical structure of ever-smaller behavioral-demographic segments. This segmentation is dynamic and updated continually based on changes in the data.
Predictive behavior modeling – this mathematically intensive modeling is based on the fact that the behavior patterns of individual customers frequently change.
By merging the most exacting micro-segmentation available anywhere with a deep understanding of how customers move from one micro-segment to another over time—including the ability to predict those moves before they occur—an unprecedented degree of accuracy in customer LTV forecasting is attainable.
Does Optimove implement predictive analytics?
Absolutely! Optimove’s predictive behavior modeling applies mathematical, statistical and machine learning techniques to transactional, behavioral and demographic data in order to predict future customer behavior and value, including churn prediction, reactivation propensity, conversion likelihood and future value. Optimove maintains a sophisticated customer model, based on LTV forecasting and predictive micro-segmentation, that allows marketers to tailor their customer messaging and offers to individual customer personas. It also provides exciting new methods with which to explore the customer database, in order to find insights and opportunities marketers would not be able to find in any other way.
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Contact us today – or request a Web demo – to learn how you can use Optimove to predict customer behavior and easily maximize the impact of every marketing action in order to convert more customers, increase the spend of existing customers and reduce customer churn.
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