Until relatively recently, FSIs have been more concerned with cost justifying their investments in CRM-related technology than they have been with measuring the success of their implementations. As more institutions have moved beyond project initiation, developing metrics for accurately measuring CRM success need to be defined. This Research Note looks at the pitfalls of some commonly used measures of CRM efficacy and creates a prototype "balanced scorecard" for measuring CRM success.
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Highlights
The business case or justification for CRM projects is typically a mix of “hard” and “soft” benefits. Once an organization has some experience running newly implemented CRM technologies, it must figure out how to determine whether the implementation has been successful. The metrics used for investing in CRM projects are often very different from the metrics that should be used to evaluate a project’s success.
CRM is a difficult concept to define, and it means different things to different people and different organizations. Each organization needs to define its CRM strategy clearly so that it can later evaluate the accomplishments of the strategy. Since every financial services institution (FSI) defines and implements CRM uniquely, no one set of metrics will provide a fair evaluation for every institution. As FSIs enunciate their CRM strategies and goals, each institution should also establish its customized criteria for measuring success.
The metaphor of a balanced scorecard may represent the best approach for FSIs wishing to evaluate their CRM efforts. As each FSI states its definition of CRM, it will find itself enumerating several factors of success. FSIs will also find that the success factors will require a balancing for a multivariate measurement. Focusing on a single success variable will provide a skewed view of the CRM initiative.
The CRM metrics proposed within this TowerGroup Research Note are appropriate for all facets of the financial services industry. Industry-specific or firm-specific customization is valid, of course, but the metrics proposed here are meant to represent a “core” grouping.
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