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Asset-based lending · Ongoing
ABL Funding
+140%
Qualified leads, year over year
Case study · Ongoing

ABL Funding

Direct private real-estate lending · 9,000+ projects funded · 15+ years

140% more qualified leads, closing nearly 5× as often

We rebuilt a private real-estate lender's paid-search program around lead quality, not raw volume: qualified-lead volume more than doubled year over year, cost per qualified lead fell roughly 70%, and the share of qualified leads that actually closed climbed from 1% to a peak of 4.7%.

About ABL Funding

A business worth building around.

ABL Funding (Asset Based Lending) is a direct private real-estate lender based in Jersey City, financing residential real-estate investors across fix-and-flip, new-construction, bridge, and DSCR rental loans, from roughly $75K up to $50M. In 15-plus years it has funded more than 9,000 projects and earned repeat Inc. 5000 recognition. Because it lends its own capital rather than brokering deals out, it underwrites and funds in-house.

ABL serves a customer who comes back: the active real-estate investor financing deal after deal. That repeat-borrower base, a direct-lending model that controls its own underwriting and timelines, and what the firm bills as the only true zero-point program in hard-money lending make for durable, relationship-driven volume. Exactly the kind of business where better lead quality compounds into real funded loans.

What it produced

The receipts.

+140%
Qualified leads, year over year

A rebuilt, quality-first paid-search program more than doubled qualified-lead volume year over year.

1% → 4.7%
Qualified-lead close rate

The share of qualified leads that closed into funded loans climbed from 1% at kickoff to a peak of 4.7%. Nearly five times as many leads turning into business.

−70%
Cost per qualified lead

Cost per qualified lead fell roughly 70% as tracking, targeting, and bidding were rebuilt around lead quality.

The challenge

Where it started.

01.

The mandate.

ABL Funding doesn't need leads. It needs real-estate investors who fund. Private real-estate lending is a high-consideration, relationship-driven sale, and a “qualified lead” that never closes into a funded loan is just expensive noise. The program had to drive volume and quality at once: more qualified leads, and more of them actually closing.

02.

The constraint.

At kickoff, only about 1% of qualified leads were closing. The paid-search program had been optimized to lead volume and cost, so it efficiently bought leads that looked good on a form and funded nothing. Spend was chasing the wrong signal.

03.

What had to change.

We had to connect paid search to closed loans, not form-fills: feed real funding outcomes back into the platforms, and optimize toward the real-estate investors who actually close. Cheaper leads only matter if more of them fund.

How we engaged

What we did.

Quick winsIntegrationCompounding
01.Days 1–30

Quick wins.

We started by teaching the program what “good” means. The leads had been judged on volume and cost, so we redefined the target around the borrower who actually funds, wired CRM signal back into the ad platforms, and cut the spend chasing leads that never closed.

02.Days 30–90

Integration.

We rebuilt the program around lead quality: feeding closed-loan outcomes back to the platforms, restructuring campaigns around the investor segments that actually fund, and tightening keyword and audience targeting to the high-intent real-estate-investor profile. The bidding learned to value a lead that closes, not a lead that clicks.

03.Day 90+

Compounding.

The quality and the volume compounded together. Year over year, qualified leads grew 140%, cost per qualified lead fell about 70%, and the share of qualified leads that closed climbed from 1% to a peak of 4.7%. Nearly five times as many leads turning into funded business. All told, paid search has sourced tens of millions of dollars in closed loans for the program.

Capabilities exercised
  • Closed-loan optimization
  • CRM-integrated bidding
  • Lead-quality (not volume) targeting
  • Commercial lending
  • Paid search
  • B2B finance
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