While traditional wallet-based segmentation approaches have historically been the norm in the wealth management industry, future long-term profitability will be driven by a firm’s ability to adapt its segmentation model to the evolving needs of its clients, according to a whitepaper released by SEI.
"SEI Insights: Can Segmentation Lead to Sustainable Profits?" explores the benefits of enhancing current segmentation models to incorporate investors’ behavior patterns. The paper concludes that unified technology platforms, which enable flexible model-based portfolio construction and provide advisors with varied tools, offer wealth managers the resources necessary to develop and execute more effective segmentation strategies.
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Al Chiaradonna, senior vice president, SEI Wealth Platform, said: "It’s clear that wealth management firms become more profitable as they evolve with and ahead of their customers, and enhanced client segmentation strategies have been found to help drive this evolution and profitability. We’ve also found that achieving this will hinge on a firm’s ability to develop a technological environment that can collect, manage, and analyze vital client data. With this improved data, firms can better understand the modern segmentation of their clients and prospects and ultimately target them more effectively."
The paper examines how the wealth management industry traditionally segmented individuals en masse, using three static dimensions: amount of wealth, source of wealth, and age of wealth. While this approach worked successfully for many years, wealth management clients’ needs and values have evolved.
The paper reveals that a dynamic segmentation style has recently emerged, which considers not only an investor’s amount of wealth but also incorporates an individual’s behavior patterns. Capturing behavioral insights can enable wealth managers to anticipate future demand and develop value-based solutions.
For this new behavior-based segmentation to be effective, wealth managers need to collect and maintain client data to properly understand their clients’ needs.
Chiaradonna added: "We’re seeing a lot of wealth managers struggling with segmentation and looking for immediate solutions. Current segmentation based on wallet-share has caused a significant strain on resources, as firms tend to focus on providing their wealthiest clients highly customized solutions. This greatly limits how many clients a wealth manager can adequately serve. But, trend analysis and data collection make it possible to identify, for example, that the needs of a mass-affluent client are not that different than those of an ultra-high-net-worth client. A unified platform allows you to segment clients based on similar goals, many times resulting in the ability to better service existing clients, while freeing up resources to acquire new business."
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By GlobalDataThe paper explores how this challenge and trend is not unique to the wealth management industry and examines segmentation process improvements within the car insurance industry, which centered on using enhanced data to better understand customers.
For decades, the insurance industry based its premiums on basic factors often sourced by brokers, but this approach increasingly mismatched clients and products and ignored many who did not fit into strict segmentation models.
Insurers instead began to assess clients based on behavior patterns and, using enhanced technology, collected and analyzed client data. Through this strategy, insurers discovered a way to identify other drivers with similar behavior patterns and target them more effectively.
Traditionally, the wealth industry has focused on the ultra-high-net-worth (UHNW) segment. The paper reveals an opportunity for wealth management firms to create a unique client experience for the high-net-worth (HNW) and, largely untapped, mass-affluent segment of investors.
Firms that upgrade their technology solutions and, in turn, segmentation strategies will find themselves with greater revenue margins than firms that focus solely on the UHNW segment.
