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Case study · From the Pluris libraryReceipt no. 3765
What sucked

Everything the brokerage knew about its ultra-high-net-worth clients, who they were, what they wanted, and what they would actually buy, lived scattered across individual brokers' email and text threads.

There was no automated way to capture or centralize it, so marketing and outreach ran on gut feel and memory. When a high-value property came up, no one could systematically say which clients would want it; they guessed.

Real EstateSales & Revenue4–8 weeks
What they built

OutcomeCatalyst built automated ingestion for the brokerage that continuously pulls every broker's emails and texts into one centralized client-intelligence brain, capturing each client's interests, history, and buying signals. With that shared store in place, the firm can match a specific property to the exact buyers most likely to want it rather than relying on individual memory.

What changed
~7% sales lift

Targeting went from guesswork to precision and sales rose about 7%, on a book of tens of millions in transactions, a large absolute revenue gain from a single data-driven change.

Guesswork to precision targeting

The firm can match a specific property to the exact buyers most likely to want it, instead of marketing on instinct.

One client-intelligence brain

Broker emails and texts are continuously captured into a single centralized store of client interests, history, and buying signals.

Time to results
4–8 weeks
Company size
1-50 people
Project cost
$25K – $100K
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Who did it
Zach Shapiro
OutcomeCatalyst

Vetted by Pluris.