Funded, not applied
Rank channels by relationships that actually funded and the revenue they earn.
Marketing attribution for business banks and credit unions
Match funded commercial relationships to the inquiries and campaigns that produced them, across a cycle that runs months and involves a relationship manager.
$660,000 55% of $1,200,000 paid
The blind spot
Application volume is easy to buy and mostly does not fund. The relationships that do are worth years of fee and deposit income, and application counts tell you nothing about which channel produces them.
What you get
Rank channels by relationships that actually funded and the revenue they earn.
An inquiry in March funded in September still traces to the campaign that produced it.
Only exact matches count automatically; anything weaker is flagged rather than assumed.
A worked example
Not impressions, not leads, not cost per click. Closed revenue, by the channel that produced it, for a period you choose — with the portion we could not trace shown rather than quietly shared out across your paid channels.
| Channel | Sales | Revenue | Share | % |
|---|---|---|---|---|
| Google Ads | 46 | $288,000 | 24% | |
| LinkedIn Ads | 31 | $228,000 | 19% | |
| Email marketing | 27 | $144,000 | 12% | |
| Direct / Unknown | 88 | $540,000 | 45% |
A meaningful share of commercial banking relationships still begin with a call to a branch, a conversation at a chamber event, or an introduction from an existing client. Digital attribution treats all of that as untracked, which means it treats most of the book as invisible.
Matching on the business contact rather than a browser session pulls those relationships back into the picture where a lead record exists for them, and leaves the genuinely untraceable ones in Direct / Unknown rather than crediting them to whichever campaign happened to be running.
A funded commercial relationship generates fee and deposit income for years. Judging acquisition spend on the first year systematically underprices whichever channel brings relationships that stay.
Because the match is on the client and there is no attribution window, running the report across several years credits later revenue back to the channel that produced the original inquiry. That is usually the analysis that justifies a materially larger acquisition budget.
A treasury campaign aimed at operating balances and a lending campaign aimed at owners looking for a term facility compete for the same marketing money and are judged against the same blended figure. They behave nothing alike. Deposit relationships open quickly, earn through balances and fees, and are sensitive to rate. Credit relationships take months, involve underwriting, produce one large number when they fund and produce nothing at all when they are declined halfway through. Averaging two funnels with those shapes produces a cost per relationship that belongs to neither of them.
A product column mapped as Product / service separates them in the revenue breakdown, with how much of each product traces to a channel. A channel producing a steady flow of small operating accounts can be the best source the bank has while looking mediocre next to a channel that happened to produce two funded facilities in the same quarter. Reading the two together is how a bank concludes that a campaign failed when it in fact succeeded precisely at the thing it was aimed at doing. The column costs one field at export and settles an argument the bank has been having every quarter.
It also puts the decline rate where it belongs. Applications that never fund appear as unmatched leads and cost nothing against your allowance, so a channel producing volume that underwriting rejects shows up as inquiry count with no revenue behind it. That is a genuine cost in credit analysis, staff time and an applicant's experience of the bank, and it is entirely invisible in a report that treats the application itself as the outcome being bought. A channel can therefore be expensive in a way that never appears on any marketing invoice at all.
The operating account is the beginning rather than the end. Merchant services, payroll, positive pay, lockbox, commercial cards, foreign exchange, an equipment facility two years later: most of the fee income a commercial relationship produces is sold by a relationship manager to a client the bank already has. None of it is attributed to anything, because by the time it happens the marketing that opened the door is several reporting cycles into the past. The result is that the most profitable part of the relationship is credited to nobody in particular.
Matching on the business contact means each of those later revenue lines credits the channel that produced the relationship in the first place. The acquisition question changes from what a funded account is worth in its first year into what the relationship has produced since it opened, and the answer usually justifies materially more spend on whichever channel brings clients who go on to take a second and a third product from the bank. It is a different budget conversation, and it starts from what the bank actually collected.
It exposes the reverse case as well, which banks rarely quantify. A channel can produce accounts that open, sit at a low balance and never take another product. On a funded-account count that channel performs well; on fee income across three years it performs badly. Both facts come out of the same two files, in the same report, and only one of them is currently on anybody's dashboard or in anybody's quarterly marketing review. Knowing which channels produce dormant relationships is worth as much as knowing which produce active ones.
Deposit gathering is rate-sensitive in a way that makes marketing measurement genuinely difficult. Move a rate and volume arrives, and whatever campaign was in market at the time is credited with a response the rate produced. Cut the rate and volume disappears while the campaign takes the blame. This is the specific measurement trap in commercial banking, and no attribution method resolves it on its own, including this one. What it does do is stop the report from quietly converting a treasury decision into a marketing conclusion, which is where most of the damage is done.
What helps is comparing the same period a year apart rather than consecutive months, ranking channels on revenue rather than on applications, and reading the relationship count beside the money. A rate-driven surge lifts every channel at once and appears as a level shift across the whole report. A channel that genuinely improved moves relative to the others, and a month-on-month comparison cannot tell those two situations apart at all. Reading the report the wrong way round here is the most expensive mistake available to a bank marketing team, because it usually ends with the wrong channel being cut.
Because there is no attribution window and nothing had to be running at the time, historical comparisons are available immediately rather than after a year of waiting. A bank can upload three years of funded relationships and lead exports on its first afternoon and look at how each channel behaved through a full rate cycle, which is a considerably better basis for setting a budget than the single quarter that has just finished. It is also the fastest way to find out whether the exercise tells the bank anything it did not already suspect.
Why it matters
"We generated 400 leads" invites an argument. "This channel closed $186,400 last quarter, here is the reconciliation" ends one. The teams that can show closed revenue by channel are the teams that get the next increase approved, because they are asking with evidence rather than with conviction.
Killing spend is politically harder than adding it, because someone always owns the channel being cut. A number that reconciles to the sales export takes the argument out of the room — you are not overruling a colleague's judgment, you are reading the same ledger they are.
Platform-reported conversions do not reconcile to revenue, and eventually someone in finance notices. Reporting built from your own closed-sales export starts from the number finance already trusts, which is why it holds up when it is checked.
Because this reconciles exports rather than tracking visitors, it works on months that have already closed. You are not instrumenting now to learn something in ninety days — you can answer for last quarter today, which is usually when the question is being asked.
Honest answers
The match needs a business contact detail, a revenue figure and a date — no account numbers, no balances, no statements. Data is encrypted, isolated per workspace, deletable in one click, and covered by a DPA.
Then Direct / Unknown will be large and that is the honest answer. Knowing referral is 45% of first-year revenue is a finding worth having; folding it into a paid channel would make every paid figure meaningless.
It does not need to. Any layout works — a contact detail, a revenue figure and a date is enough, and the mapping is confirmed once.
Pricing
The price here is the price on the invoice, plus any sales tax that applies — no per-call, per-minute or per-form fees. Enterprise usually fits business banking teams and credit unions — ten seats for the team and the highest monthly record allowance, since a year of closed deals is a lot of rows.
One business closing at volume
$499/mo
billed monthly
Questions
Anything else? Talk to us — a person answers, usually the same day.
Funded relationships: a business contact email or phone, first-year revenue or fee income, and the funding date.
Yes — run the report across a longer range and later revenue traces back to the channel that produced the original inquiry.
Yes, with a product column mapped as Product / service. Treasury, lending and deposit revenue then appear as separate lines, with how much of each traces to a channel.
Yes: a branch column mapped as Location, or a relationship-manager column mapped as Product / service (one extra breakdown per import). Either shows where marketing-sourced business is landing.
Encrypted in transit and at rest, isolated per workspace, deletable, and we act as a processor with a DPA. Only a contact detail, an amount and a date are needed.
No. Your existing lead exports work as the second file.
Usually marketing, an analytics lead and someone in the line of business. Enterprise includes ten sharing one record allowance.
Yes, and for a cycle this long that is the only honest way to evaluate it.
Yes, with a product column mapped as Product / service, and it is worth doing first. The two have different cycle lengths and revenue shapes, and seeing them as separate lines stops a few large facilities from passing for a channel's typical result.
No. Applications sit in the lead file and only funded rows in the revenue file are counted. A channel producing volume that underwriting declines therefore shows inquiry count with no revenue behind it.
Add the attendee or registration list to the lead file, with contact details and the event as the source. It then ranks on funded revenue beside the paid campaigns instead of being defended on attendance numbers and impressions.
Yes, as further revenue rows against the same business contact. They credit the channel that produced the relationship, and that is usually the analysis which justifies a larger acquisition budget.
Names are not required. A contact email or phone, an amount and a date is enough, and many banks export a contact detail with an internal reference rather than a full client record.
Three years is a reasonable starting point, because it usually spans a rate move in both directions. Nothing had to be running at the time for those periods to be analyzed now.
Nearby
Match funded loans, opened accounts and the balances behind them to the campaigns that produced the member.
See how it worksMatch bound policies and the commission they earned to the inquiries and campaigns that produced them, across renewal cycles measured in years.
See how it worksMatch activated accounts and the revenue they process to the campaigns that produced the signup — because a signup that never transacts is not a customer.
See how it worksWhere your sales already are
From the blog
Every attribution tool is built for businesses where the inquiry and the purchase happen in the same quarter. If yours does not, almost every default is wrong: the date ranges, the reporting cadence, the optimization signal and the patience of everyone involved.
Read the articleBefore you can argue about attribution you have to agree what a sale is, when it happened, and how much it was worth. Most businesses have never had that conversation, which is why the marketing number and the finance number never match and everyone assumes somebody is wrong.
Read the articlePixels were built for sales that finish in a browser. Most sales don't. Here's the method that works on exports you already have — and why the tools you're paying for structurally cannot do it.
Read the articleStart today
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