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Company Overview A growth-focused fintech empowering investment managers with scalable, innovative solutions.
Industry Finance
Headquartered NA
JUMP TO SECTION
1. introduction 2. the challenge 3. our solution 4. the impact

Introduction

In fintech, Assets Under Management (AUM) isn’t just a data point. It determines deal size, sales motion, compliance complexity, and long-term revenue potential.

But here’s the problem most fintech teams quietly deal with:

The data they need to segment and prioritize accounts simply doesn’t exist in their CRM.

Our client needed to segment accounts into:

  • $1M–$50M

  • $50M–$100M

  • $100M+

 

Not just for reporting, but for revenue execution.

Without accurate AUM segmentation, their sales and marketing teams were operating without clarity.

The challenge

The client faced three core issues:

  1. No enrichment provider reliably offered up-to-date AUM data.

  2. Financial figures were buried in press releases, websites, and financial articles.

  3. Manual research at scale would cost time, headcount, and momentum.

This meant:

  • High-AUM firms weren’t prioritized properly
  • Messaging wasn’t aligned to firm maturity
  • Outbound lacked personalization depth
  • Sales cycles risked being misaligned with account size

 

The real loss wasn't lost data - it was opportunity.

Our solution

We redefined enrichment from static database lookup to dynamic AI-powered research.

Step 1: Data Activation

  • Pulled accounts from HubSpot into Clay

  • Enriched company domains

  • Prepared accounts for AI-driven research

 

Step 2: AI-Based Financial Discovery

Using a natural-language prompt:

“Find the most recent Assets Under Management (AUM) for this company from reliable public sources.”

Clay automatically searched:

  • Company websites

  • Press releases

  • Financial news articles

  • LinkedIn pages

  • Industry databases

 

Instead of relying on pre-packaged data, the system researched each company individually.

Step 3: Structured Intelligence

Clay returned:

  • AUM value
  • Source context
  • Reasoning
  • Confidence score
  • This ensured accuracy, transparency, and auditability.

 

Step 4: Automated Revenue Segmentation

Accounts were automatically categorized into AUM tiers and synced back to HubSpot.

From there:

  • Marketing launched segmented campaigns
  • Sales prioritized high-value accounts
  • Messaging aligned with firm size and sophistication


This made way for clarity and stopped the inevitable guesswork that comes with lack of visible data.

The impact

This wasn’t just enrichment.

It transformed revenue execution.

Revenue Prioritization Became Data-Driven

  • High-AUM firms were surfaced immediately.

  • Sales focused energy where revenue potential was highest.

 

Outbound Became Contextual

  • Messaging shifted from generic fintech outreach to AUM-aware personalization.

  • That changes response rates.

 

Strategic Segmentation Was Unlocked

The team could now:

  • Build tier-specific campaigns

  • Create differentiated value propositions

  • Forecast pipeline by asset tier

  • Align enterprise vs mid-market sales motions

 

CRM Readiness Accelerated

  • ~80% reduction in manual research time

  • Faster campaign launch cycles

  • Scalable enrichment workflows

  • What once required manual analyst effort became automated.

 

Why This Was Important

In fintech, segmentation precision directly impacts:

  • Average deal size

  • Sales efficiency

  • Pipeline quality

  • Customer lifetime value

 

By operationalizing AUM segmentation, the client:

  • Increased targeting accuracy

  • Reduced wasted sales effort

  • Improved personalization depth

  • Strengthened alignment between marketing and sales

 

This helped them clean their data which enabled them to create an advantage in how they go to market.