Ideally, all firms would have the capability to allocate customer investments in real time, but business face constraints:
- They operate in a limited resources environment and need to maintain fiscal responsibility.
- Not every prospect can be converted and not every customer can be retained.
- Many companies allow multiple silos within an organization to establish their own customer strategies and measure different things.
The solution to these challenges is customer portfolio optimization.
Portfolio optimization is the process of choosing the optimal allocation of various assets held in a portfolio. Modern portfolio theory, fathered by Harry Markowitz, Ph.D. University of Chicago, in the 1950s, assumes that an investor wants to maximize a portfolio's expected return contingent on any given amount of risk. Portfolios that achieve such a balance are known as efficient portfolios; they achieve a higher expected return by taking on more risk. Thus investors are faced with a trade-off between risk and expected return. This risk-expected return relationship of efficient portfolios is graphically represented by a curve known as the efficient frontier.
Similarly, customer portfolio optimization is this process applied to a group of customers and prospects. Marketers determine the investment to sell, market, and service in order to acquire, grow, retain, or reactivate a given customer or segment based upon the expected return. When these customers or segments are aggregated, a customer portfolio is created. The expected return is the calculated lifetime value for a given customer.
The goal of customer portfolio optimization is to generate a return from a given portfolio of customers that lies upon the Efficient Frontier curve for a given risk level (e.g. investment, long term relationship, etc.) In other words, we aim to maximize the value of a customer portfolio for a given investment risk or determine the investment and allocation required to maximize overall customer portfolio value.
Customer investment here includes acquisition cost (how much it costs to acquire a given customer) as well as cost to serve (the expense related to serving a customer). Investment allocation answers these questions:
- What media, channels, and touch-points should be leveraged? How much emphasis should be placed on digital versus other/analog touch-points?
- What is the “risk” of a given investment in customers? Investment in customer acquisition may be riskier than investment in expanding existing relationships.
Customer portfolio optimization should be one of the primary organizing constructs around which marketing and financial models are based. Thus, it is a component that is an oftentimes overlooked but critical to maximizing the value (both profit and shareholder) of an organization.
For more information on how Merkle can help you leverage customer portfolio optimization to better execute your customer strategy and maximize customer value please contact Dave Nash, Senior Director-Customer Strategy Services, at [email protected]