Research Study Enhancing Profitability with Advanced Analytics

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With operating margins in the double digits, asset managers may feel a lot less pressure to manage profitability than other industries grappling with razor-thin margins. But technological developments and demographic changes will have a profound impact on the future competitiveness of firms that don’t understand who their best customers are, how to retain them, and how to expand business with them.

Business analytics—specifically, client segmentation, advisor profitability analysis and predictive analytics—as well as a focus on individualized customer experience is foundational to the stability and success of asset managers. Whether a firm is in early or later stages in using advanced business analytics, it needs to ensure it is able to agilely respond to competitive forces in order to support profitable growth.

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Our latest research, Enhancing Profitability With Advanced Business Analytics, delves into the strategic imperative for asset managers to view business intelligence as a corporate asset, and use it to build more lasting, stable client relationships and growth. This report also includes:

  • Our DST Advisor Profitability Model to determine which clients you should attract, grow, and retain.
  • The Four Stages of Using Advanced Business Analytics to evaluate the stage your firm is in and maximize your strategy in each stage.
  • Recommendations for firms in early and later stages of using advanced business analytics.

Subscribers of this report also receive a personalized DST analyst presentation. Purchase the report today.

Primary Audience: Heads of Distribution, E-Business, Marketing, Strategy, and Business Intelligence

Methodology

DST analyzed survey results from a diverse set of 41 asset managers and insurers, and conducted interviews with firm executives and industry vendors.

Table of Contents

  • Executive Summary
  • What Firms in Initial Stages Should Do
  • What Firms in Later Stages Should Do
  • Using Analytics to Drive Profitability
  • Appendix
  • Methodology

List of Exhibits

  • Average Inflow
  • Formal Client Retention Goal
  • Stages of Using Advanced Business Analytics
  • Operating Margins Rise Despite Volatile Net Flows
  • 360 Degree Advisor Record
  • Team Size
  • Shared Business Analytics Functions
  • Top Reasons Why Firms Say That Assets and Clients Churn
  • Factors that Cause Advisors to Reduce Business With Firms
  • Sample Advisor Profitability Model (Abbreviated)
  • Monitored Website Activity
  • Marketing Click-through and Response
  • The Advisor Multi-factor Map
  • Sample Advisor Segmentation
  • Marketing Access to CRM System
  • Sales Team Access to CRM System
  • Business Analytics Access to CRM System
  • Use of Predictive Analytics
  • How Firms Use Predictive Analytics
  • Uplift Response Model
  • Diversification and Product Frequency Goals
  • Analyze Churn
  • Wholesaler Goals Aligned With Corporate Goals
  • Churn Indicators That Firms Monitor
  • Product Expectation Management
  • Using Content to Manage Product Expectations
  • How Firms Measure Client Retention Initiative Success
  • Client Retention
  • Sample Advisor Profitability Model (Full)

Report Details

  • 43 pages
  • Released 11/10/2014
  • Author: Julia Binder

categories: advanced analytics, predictive analytics, data science, business analytics





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