How would you measure the success of Charles Schwab's Intelligent Portfolios robo-advisor service?

Introduction

Measuring the success of Charles Schwab's Intelligent Portfolios robo-advisor service requires a comprehensive approach that considers multiple stakeholders and metrics. To effectively evaluate this product success metrics problem, I'll follow a structured framework covering core metrics, supporting indicators, and risk factors while considering all key stakeholders.

Step 1

Product Context

Charles Schwab's Intelligent Portfolios is a robo-advisor service that provides automated, algorithm-driven portfolio management with minimal human intervention. The key stakeholders include:

1. Investors (users): Seeking low-cost, diversified investment management
2. Charles Schwab: Aiming to expand market share and increase assets under management
3. Regulators: Ensuring compliance and consumer protection
4. Financial advisors: Potentially viewing the service as competition

User flow:

1. Sign-up and risk assessment: Users create an account and complete a questionnaire to determine their risk tolerance and investment goals.
2. Portfolio creation: The algorithm generates a diversified portfolio based on the user's profile.
3. Funding and investment: Users transfer funds, which are automatically invested according to the recommended allocation.
4. Ongoing management: The system monitors and rebalances the portfolio as needed, with users able to view performance and make adjustments.

Intelligent Portfolios fits into Schwab's broader strategy of offering diverse investment options to attract and retain clients across various segments. It competes with other robo-advisors like Betterment and Wealthfront, as well as traditional financial advisors.

Product Lifecycle Stage: Growth phase - The robo-advisor market is still expanding, with increasing adoption among younger and tech-savvy investors.