At a high level, an effective MOM is made up of three parts:

Integrated consumer data: Collecting data isn’t the issue—companies have plenty of it. It’s not uncommon, for example, for marketing, customer care, transaction/order, technology, and store operations to all have distinct sets of data on a single consumer in multiple databases and tables. The challenge is weaving all the available data into an accurate and complete profile of the individual consumer. Failing at that can blunt the impact of even the most ambitious data-collection efforts.

Decision making: With a complete customer profile in hand, companies can “score” customers based on specific criteria of value-creation potential, allowing marketers to prioritize which messages, offers, and experiences to deliver at which points in the decision journey. A set of business rules and regression models, increasingly based on machine learning, helps to prioritize and match specific messages, offers, and experiences to specific customer scores.

Distribution platforms: Marketing-technology platforms are the last mile of the process. They integrate the customer scores and use them as triggers to deliver the right message to the right person across all addressable channels. Equally important, the platforms track the responses, conversion, and value created so that the MOM can learn and adjust.