profitable businesses with distinctive and compelling value propositions. These propositions can be structured by gifted salespeople in the course of a number of expensive personal visits. Or they can be developed more systematically in an exercise designed to define and serve unique and profitable customer segments.
Given that most banks lack a superabundance of gifted salespeople, the second approach would seem the more productive. Unfortunately, many segmentation efforts don't go beyond the use of simplistic five-digit standard industrial classification codes. This can fail because the codes describe the requirements of "average" firms, and no firm is really average; and because they generate a potpourri of segments, some of which are too small and others too large and unwieldy.
The answer is an approach that aggregates companies with similar behaviors and attractive profitability characteristics into an actionable number of segments. The key to successful segmentation is understanding that behavior is driven by needs -- a function of lifecycle position as well as industry -- and by attitudes -- what the decision maker wants in a banking relationship, for example, a detailed product catalogue versus synthesized information and advice.
With this approach, the bank has a better chance to develop killer value propositions. The issue: how to get the information needed to do this faster and more cost-effectively than via in-person calling or surveys that are limited in scope, inflexible, and, being one-way communication tools, ill-suited to reveal a prospect's thinking.
We have introduced an approach called Rapid Cycle Learning/Testing, or RCT, essentially an upgraded process that allows the bank to dramatically accelerate the pace of gathering information and testing the hypotheses needed to develop effective value propositions.
While suitable for many uses for example, customer retention -- one key application of RCT is as an upgraded market research tool. As such, the process uses interactive, phone-based dialogues to learn the characteristics that identify the needs and attitudes of profitable customers. In the course of these dialogues, the bank continually improves its "script," learning how best to engage, ask, assess, entice, and ultimately close with different customer types. All this is done in a rapid cycle that compresses months into a few weeks.
The power of RCT dialogues derives from their dynamic structure, with each customer response defining a subsequent, customizable branch of questioning that leads to enriched knowledge. This technique would be unmanageable in a traditional market research environment, but proprietary software guides the researcher through the discussion. This software also captures and saves each customer's unique response, which in turn is analyzed with other customer behavior data to improve targeting and determine more attractive value propositions aligned with the needs of other customer segments.
Many banks readily admit that only about 20% of their relationship managers sell effectively. Use of RCT would simplify the tasks and deepen the sales penetration of these winners, while at the same time greatly upgrading the performance of their less successful colleagues. Wherever tried, RCT has yielded more insights than traditional research methods, resulting in improved customer response levels. We believe it is essential to any institution aspiring to superior small-business returns.