The Funding-Floor Metrics That Actually Predict Revenue
Dial counts feel productive. These conversion ratios and timing measures tell you where next month's fundings will come from, and where they are leaking.
A floor can hit every activity target for a month and still fund less than the month before. The dial count was up, talk time looked healthy, the leaderboard was full of green, and yet the funded column did not move. The activity was real. It just was not the activity that turns into revenue.
Funding revenue is the end of a chain: leads become conversations, conversations become applications, applications become complete files, files become submissions, submissions become approvals, approvals become fundings. Each link has its own conversion rate and its own speed. The metrics worth tracking are the ones that measure those links, because they tell you where to intervene. The rest is decoration.
Pre-flight summary
- Revenue is a chain; measure the conversion of each link.
- Contact rate is the earliest predictor and depends on speed and attempts.
- App-to-submission is often the biggest silent leak.
- Read approval rate and approval-to-fund together to find coaching targets.
- Use median time in stage to catch slowdowns early.
Leg 01Think in ratios between steps
Raw counts tell you how busy people were. Ratios between consecutive steps tell you how well the work converted. If you only track one thing per broker, track the conversion from each stage to the next, because a weak link shows up there long before it shows up in revenue.
Say two brokers each submit twelve files in a month. One got there from thirty applications, the other from fifteen. The second broker is either qualifying better or collecting documents more effectively, and the first broker is losing half their applications somewhere. That is a coaching conversation you would never have from submission counts alone.
Leg 02Contact rate: the first leak
Contact rate is the share of new leads that result in a real two-way conversation. It is the earliest predictor in the chain, and it is affected by things you control: how fast you call after a lead arrives, how many attempts you make, which times of day you dial, whether you text as well as call, and whether your caller ID is recognised as local.
Measure it per lead source as well as per broker. A source with a consistently poor contact rate may be the problem rather than the people dialing it. FundPilot logs every call, text and outcome to the deal, so contact rate can be calculated from the records themselves instead of from brokers' self-reported tallies.
Leg 03App-to-submission: where files go to die
Application-to-submission rate measures how many signed applications become complete files sent to lenders. On many floors this is the biggest silent leak. Merchants sign an application on the phone, promise to send statements tonight, and disappear.
A low rate here usually points to collection friction or weak qualification. Either the merchant did not really intend to proceed, or sending documents was harder than it should be. Fixes include a simple branded portal for uploads, a polite reminder sequence, and asking for statements during the first call while the merchant is engaged.
A signed application without statements is a promise, not a deal. Track how many promises your floor keeps.
Leg 04Approval rate and approval-to-fund
Approval rate is the share of submitted files that receive at least one offer. If it is low, look at file quality and lender matching before you blame the market. Files sent to funders whose guidelines they clearly do not meet waste everyone's time and wear down lender relationships.
Approval-to-fund rate measures how many approved deals actually close. A low number here is often about presentation and trust: the merchant was surprised by the remittance, did not understand the cost, or was already talking to someone else. It can also reveal stipulation problems, such as verification calls that are not scheduled promptly.
Look at the two numbers together. A broker with a high approval rate and a poor approval-to-fund rate is probably building good files but presenting offers poorly, which is a very specific thing to coach.
Leg 05Time in stage: the speed metric
Conversion tells you how many deals survive each step. Time in stage tells you how long they take. In business funding, speed matters because merchants who need capital often talk to several providers, and a file that sits for days loses to one that moves.
Track the median time each deal spends in each stage, not the average, which a few very old deals can distort. Watch for stages where time is creeping up week over week. That is usually an early warning of a capacity problem, such as a single processor overwhelmed by submissions.
- Lead created to first contact
- First contact to signed application
- Application to complete documents
- Submission to first lender response
- Offer presented to contracts signed
- Contracts signed to funded
Leg 06Vanity metrics to retire
Some numbers are easy to measure and feel motivating but predict very little on their own. Keep them as diagnostic background if you like, but stop running the floor on them.
Retiring a metric from the leaderboard is not the same as ignoring it. Dial count still matters when contact rate drops and you need to know whether effort fell or effectiveness did. It just should not be the headline.
- Total dials without contact rate beside them
- Talk time, which rewards long calls rather than productive ones
- Submission count without approval rate, which rewards sending weak files everywhere
- Pipeline value based on requested amounts rather than realistic offers
- Number of lenders submitted to per deal, which can encourage shotgunning
Questions from the floor
How often should I review these metrics?
Look at time-in-stage exceptions daily, because they drive action on specific deals. Review conversion ratios weekly, by broker and by lead source, since daily numbers are too small to be meaningful. Monthly, compare trends and decide on bigger changes, such as reallocating lead spend or changing your document collection process. Avoid reacting to a single bad week.
What sample size do I need before trusting a broker's conversion rate?
There is no magic number, but a handful of deals tells you very little. A broker who converts two of three applications is not necessarily better than one who converts eight of fifteen. Look at rates over a longer window, compare them with the floor's overall pattern, and treat small samples as a reason to listen to recordings rather than as a verdict.
Should brokers see their own metrics?
Yes. Brokers improve faster when they can see their own conversion ratios and time in stage, ideally on a personal view that compares them with their own past performance. Be careful with public rankings on conversion metrics, since small samples can make good brokers look bad for a week and push people toward gaming the numbers.
How do I calculate these without a data analyst?
If stages are event-based and every deal records its stage changes with dates, most of these metrics fall out of the CRM directly. In FundPilot you can ask the AI assistant questions such as how many applications from last month reached submission, and it answers from live CRM data. The key requirement is consistent stage use, not a separate reporting team.
General information only — not legal, tax or financial advice. Rules for telemarketing, texting, recording, disclosures and data retention vary and change; confirm current requirements with qualified counsel.
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