Independent advisors know that data and analytics can drive business results, but most do not take full advantage of their potential. Analytics can improve a RIA's practice efficiency, marketing return on investment (ROI) and profitability. And yet, most advisors hardly scratch the surface in how they use their own data.

There are different types of analytics, each with their own level of usefulness. They are: Descriptive (What happened?), Diagnostic (Why did it happen?), Predictive (What will happen?) and Prescriptive (What should I do?). Descriptive metrics are usually viewed in hindsight and vary in usefulness for forecasting or predictive purposes. Independent advisors use them for basic measures such as assets under management (AUM), firm revenue, number of clients and so forth.

A much smaller percentage of advisors invest time in diagnostic analytics, and when they do, it is typically for one-off analyses versus continuous learning. Predictive and prescriptive analyses often use a combination of technology and tools, business rules, and data input sets including historical, transactional, real time and big data. 

These analyses can have a powerful impact. For example, RIAs can forecast future business development success based on planned marketing activities, and then run these through an optimization model. Similarly, an advisor might employ machine learning to identify and predict future client behavior from past behavior and manage their client relationships accordingly. But because of their complexity, these analyses are rarely—if ever—used by advisors today.

Advanced Data Analytics: Client Service And Marketing

When CRMs are used for client service purposes, advisors can pull reports on the number and types of client touches for a specified population. Initially these reports are descriptive analyses based on hindsight. Studying time since last contact, number and types of client contacts, and similar measures gives RIA principals quantifiable metrics for benchmarking against internal goals.

Over time, advisors can use these reports to diagnose trends and prescribe changes to improve their client communications. Client segmentation analyses and other analytical tools can help advisors identify patterns of client behavior—at different times of the year, following major headline news, at different ages and life events—predict future client actions, and recommend relevant outreach. For example, a pattern of increased inbound inquiries following major news events may prompt advisors to actively reach out to the whole client segment sensitive to the news cycle.

Advisors can also stratify clients by age groups using CRMs' native descriptive reporting capabilities. They can then layer on predictive analysis by combining the CRM report with RMD calculations and assumptions to forecast the rate at which AUM will run off. This information can be the foundation for prescriptive analysis to determine the rate at which new AUM needs to be replenished to maintain firm revenues. All of this data can inform the firm's marketing and business development strategy moving forward.

Social Media Can Take Marketing Analytics To The Next Level

An elite group of RIAs is employing highly sophisticated analytics to target new prospects, including tapping into the analytical powerhouse that is Facebook. For more than five years, Facebook has partnered with data brokers to acquire user data, including income, credit card activities and other financial information. This makes Facebook advertising an incredibly powerful tool for targeting very specific market segments.

First « 1 2 3 » Next