The 20 Most Common FINTRX AI Prompts Used by Distribution Teams

To understand how distribution teams are actually using AI in practice, we analyzed the most common FINTRX AI prompts run over the past month. The goal was not just to measure usage volume, but to identify consistent behavioral patterns in how firms are applying AI to advisor targeting and engagement.

•  AI Analyst prompts used to research RIAs, family offices, portfolios, and key decision makers in real time
•  AI Elements prompts used to generate structured intelligence fields that power segmentation, scoring, and prioritization

The 20 prompts below represent the most common ways FINTRX users operationalized AI last month. Each prompt has been generalized from real usage patterns, with all firm names, individuals, and securities removed.

The 10 Most Common AI Analyst Prompts

These prompts show how distribution and capital raising teams use FINTRX AI Analyst to accelerate advisor research, meeting preparation, and personalized outreach at scale.

1. Summarize this firm’s investment strategy, portfolio allocations, and key focus areas.
Distribution teams use this prompt to quickly understand how a firm invests and what types of strategies are most relevant before outreach or meetings.

2. Show me this firm’s portfolio holdings and recent allocation trends.
Users analyze holdings data and allocation shifts to identify positioning angles, competitive exposure, and timely outreach opportunities.

3. Who are the key decision makers on the investment team at this firm?
This prompt surfaces the most relevant investment professionals and clarifies who influences allocation and product selection decisions.

4. Build a meeting prep brief with everything I should know about this firm.
Teams use AI to generate comprehensive pre-meeting intelligence briefs, replacing hours of manual research with a concise, actionable summary.

5. Find the best path to engage this firm and which contacts to prioritize.
Rather than guessing coverage strategy, users rely on AI to map engagement paths and identify the highest-impact contacts to approach first.

6. Analyze this firm’s allocation preferences and identify where our strategy fits.
This prompt connects real portfolio behavior to product positioning, helping teams align conversations with how the firm actually allocates capital.

7. Draft a personalized outreach email based on this firm’s investment profile.
AI-driven personalization enables tailored messaging grounded in actual holdings, strategy focus, and allocation behavior.

8. Identify firms similar to this one based on investment approach and client profile.
Lookalike prospecting allows teams to expand pipeline by targeting firms that resemble existing high-value clients.

9. What key insights or recent changes should I know before engaging this firm?
Users request quick summaries of recent developments, allocation shifts, and positioning insights to sharpen outreach relevance.

10. Provide a high-level overview of this firm including structure, strategy, and focus.
This prompt delivers fast, reliable firm intelligence that replaces fragmented research across multiple sources.

The 10 Most Common AI Elements Prompts

While AI Analyst focuses on real-time research and insights, AI Elements prompts are used to generate repeatable intelligence attributes that can be applied across the entire FINTRX dataset.

These prompts do more than answer questions. They create structured, filterable signals that support segmentation, prioritization, ETF targeting, and product fit analysis. Distribution and capital markets teams use them to score prospects, flag high-potential firms, analyze competitive ETF exposure, and tailor outreach based on actual portfolio behavior.

The prompts below represent the most common ways FINTRX users operationalize AI Elements to build proprietary intelligence aligned with their distribution strategy.

11. Rank each firm from 1–5 based on how well our strategy aligns with their current portfolio and investment approach.
Generates a quantified product fit score grounded in real holdings and allocation behavior, helping teams prioritize firms where their strategy is most relevant

12. Categorize each firm by its primary client segment, such as high-net-worth, ultra-high-net-worth, or institutional.
Enables segmentation of the advisor universe by end-client focus, supporting more precise targeting and messaging

13. Flag firms that have a history of adopting new ETF products shortly after launch.
Identifies early adopters that consistently incorporate new ETFs, helping issuers focus on firms most likely to evaluate and allocate to new strategies

14. Generate a structured strategic profile summarizing how each firm invests, grows, and allocates capital.
Creates a holistic intelligence snapshot that synthesizes investment approach, business momentum, and allocation tendencies into a single actionable profile

15. List the top ETF providers this firm currently favors—how heavily are they weighted?
Reveals competitive provider exposure and concentration, highlighting where incumbent ETF issuers dominate and where displacement opportunities may exist

16. Identify this firm’s primary investment focus and preferred asset classes.
Clarifies core allocation orientation so distribution teams can quickly assess product relevance and mandate alignment

17. By looking at my ETF lineup, provide an analysis of each competing fund and rank by total AUM high to low.
Generates a competitive ETF landscape view, helping teams understand relative scale, positioning, and peer competition

18. Flag firms that invest in [INSERT LIST OF ETFS].
Builds a targeted universe of firms already allocating to specific ETFs, enabling focused prospecting based on demonstrated product interest

19. Identify the single best point of contact at each of these firms for ETF outreach.
Prioritizes the most relevant investment decision maker, streamlining engagement and reducing time spent navigating complex firm structures

20. Score each firm on preference for active ETFs versus passive index ETFs based on holdings.
Quantifies each firm’s active versus passive ETF bias, helping issuers tailor positioning and outreach based on observed allocation patterns

What These Prompts Reveal About Modern Distribution Workflows

Across both AI Analyst and AI Elements usage, several consistent themes emerge that define how leading asset managers and ETF issuers are evolving their prospecting strategies.

→ Research is becoming real time and automated. Teams are moving away from static lists and manual research toward dynamic intelligence generated instantly through natural language prompts.

→ Personalization is now scalable. By grounding outreach in actual portfolio holdings, allocation trends, and firm strategy, distribution professionals can tailor engagement across thousands of advisors with precision.

→ Prospecting is shifting from reactive to predictive. Instead of asking which firms exist, users are asking which firms are most likely to allocate, adopt new products, or engage based on their historical behavior and growth signals.

→ AI is being used not just to retrieve data, but to create new intelligence. The rise of AI Elements prompts shows that advanced distribution teams are building proprietary data attributes that reflect their own targeting strategy, effectively transforming FINTRX into a customized growth intelligence engine.

From Data Access to Actionable Intelligence

The most common prompts used by FINTRX users highlight a broader shift across asset management and capital raising. Competitive advantage is no longer determined solely by access to data, but by the ability to convert that data into timely, actionable insight.

AI Analyst accelerates advisor research, meeting preparation, and personalized engagement. AI Elements enables firms to create custom intelligence fields aligned with their product strategy, ideal client profile, and distribution goals.

Together, these capabilities move distribution teams beyond static databases and into an AI-powered workflow where every prospect interaction is informed by real, contextual intelligence. For asset managers competing for allocations and mindshare in an increasingly crowded ETF and private wealth market, that shift is quickly becoming a defining advantage.

Want to try out these AI prompts or create some of your own? Request a FINTRX trial and start leveraging AI to optimize your distribution strategy.