Clari vs Gong for Commercial Capital & Debt Advisory

Say a broker takes in fifteen financing requests in a month. Historically, maybe three or four produce a signed term sheet, and one or two actually fund. If your pipeline report counts all fifteen as open opportunities, your forecast will consistently overstate volume by a wide margin, and your close rate against that inflated number will look far worse than the brokerage's actual performance.

The fix is a stage gate: a request only enters real pipeline once a lender has issued a term sheet, not when the borrower first calls. Everything before that point is intake, not pipeline, and should be tracked separately as a lead funnel rather than forecasted revenue.

Clari's governance model works well once you've defined term sheet issuance as the entry point to real pipeline, since that's the moment a lender has put real underwriting behind the deal rather than a borrower simply asking around. From there, Clari can track funded-versus-committed volume and flag any term sheet sitting unfunded past a normal closing timeline, which is often the first sign a deal is falling apart on the lender's side rather than the broker's.

That rollup also helps reconcile production across originators, since a brokerage running several originators needs one consistent definition of pipeline, not each originator's individual optimism about which requests will land.

Gong can add value analyzing borrower and lender negotiation calls, particularly around term negotiation where tone and objection-handling genuinely matter. The catch is the same one that shows up across this whole category: a lot of broker-borrower and broker-lender communication happens over email or an unrecorded call, especially with lenders who have their own compliance restrictions on recorded lines.

Before evaluating Gong, audit how much of your actual deal conversation happens somewhere recordable. If most of the real negotiation happens over email exchanges of term sheet redlines, Gong has little to analyze regardless of how good the underlying technology is.

A borrower shopping the same financing request to three brokers simultaneously is a market reality no software fixes directly. What you can do is track your win rate against shopped versus exclusive mandates separately, since those are fundamentally different conversion rates, and blending them produces a forecast that's wrong for both categories. An exclusive mandate closes at a meaningfully higher rate than a shopped request, and treating them the same in your pipeline model understates the value of relationships that produce exclusivity.

Over time, that split also gives leadership a real argument for investing in the relationships that produce exclusive mandates in the first place, since the forecast itself starts showing which referral sources and repeat borrowers are worth the extra attention.

Confirm that originators will consistently log whether a mandate is exclusive or shopped, since that distinction has to come from a human before either tool can report on it. Ask how much of your negotiation activity happens on recordable lines before evaluating Gong. And decide whether term sheet issuance is a clean enough gate for your business, or whether certain loan types need a different stage definition, such as construction lending where the term sheet is only the start of a much longer underwriting process.

Before rollout, check these points with your originators:

• Confirm originators will consistently log whether a mandate is exclusive or shopped, since that distinction has to come from a person.
• Ask how much negotiation activity happens on recordable lines before you evaluate Gong.
• Decide whether term sheet issuance is a clean enough gate for your business, or whether certain loan types need different treatment.
• Track intake volume separately from forecasted pipeline so leadership can compare conversion rates cleanly.

Not every issued term sheet funds. A lender can walk away after further underwriting turns up a problem with the collateral or the borrower's financials, and that failure mode is different from a request that never got a term sheet at all. Track term-sheet-to-funded conversion as its own metric, separate from request-to-term-sheet conversion, since a brokerage with a strong front-end conversion rate but a weak back-end one has a different problem, likely underwriting quality on the lender relationships being used, than one struggling to get term sheets issued in the first place.