Maximize Customer Value, the Smart Way

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.

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 value maximization modeling is based on the gathering and segmentation of data as a means for creating personalized communications with customers to increase engagement and loyalty. These are the pillars of every value maximization strategy:

1. 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).
2. 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.
3. 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.
4. 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.
5. 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.

Optimove integrates all these elements into its Science-First Relationship Marketing Hub. 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. By basing your customer marketing on these pillars you’ll be sure that your customer interactions are poised to achieve maximum results.