Judged against the delivery schedule
Homes hand over in phases and the spend follows them. Matching leases to the inquiry date shows which channel carried which phase.
Marketing attribution for Build-to-Rent Communities
Match signed leases and the rent they earn to the campaigns running during a delivery-driven lease-up window.
$3,828,000 66% of $5,800,000 paid
The blind spot
Lease-up compresses a year of marketing spend into a few months against a handover schedule, and the reporting only ever shows tours.
What you get
Homes hand over in phases and the spend follows them. Matching leases to the inquiry date shows which channel carried which phase.
A twelve-month lease with a renewal is the outcome. The report ranks channels on rent billed rather than leases counted.
Exact matches only count automatically, the one weaker link type is flagged and reversible, and the unattributed share is stated rather than absorbed.
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 | 52 | $1,508,000 | 26% | |
| Listing syndication | 44 | $1,276,000 | 22% | |
| Meta Ads | 24 | $696,000 | 12% | |
| Locator and broker | 12 | $348,000 | 6% | |
| Direct / Unknown | 68 | $1,972,000 | 34% |
A build-to-rent community does not lease gradually. Homes deliver in phases, the interest reserve runs to a schedule, and the marketing budget is front-loaded into the months either side of each handover. Days to stabilization is the number the capital partner watches.
That makes channel performance a timing question as much as a volume one. A channel that produces leases four weeks after the click is worth more during lease-up than one that produces the same leases at twelve weeks, and no tour-count report can tell them apart.
Matching signed leases back to the inquiry date puts the lag on the page. Two channels with identical cost per lease and different time to lease are not, in a lease-up, equally good.
Inquiries arrive before homes exist. They sit on a waitlist through construction, and a meaningful share of the first phase's leases come from people who registered months earlier in response to an advertisement nobody is still running.
Because the match is on the renter rather than a session, a waitlist registration in March and a lease in June are one record. The pre-delivery spend gets credited for what it actually produced instead of being written off as brand.
Build-to-rent competes with the rental house down the road far more than with the apartment block in town. Renters come looking for three bedrooms, a garage and a specific school catchment, and they search that way: a suburb, a school, a number of bedrooms. Demand is therefore drawn a ZIP code at a time, and two communities twenty miles apart in the same metropolitan area can respond quite differently to identical campaigns. The renter is comparing a specific house against another specific house, not a brand against a brand, and the media has to be bought that way.
Scattered-site portfolios make this sharper still. A horizontal community with two hundred homes on one site behaves like a property; a scattered portfolio of houses across six suburbs behaves like six small properties that happen to share a manager. Reporting them as one number produces an average that describes no individual home and no individual market. One manager with six sets of local competitors, six sets of comparable rents and six different sources of demand is not a portfolio in any sense the reporting recognizes. It is six problems sharing a spreadsheet.
A community or submarket column mapped as Location is what makes the report operational. It shows each catchment's leased revenue and how much of it traces to a channel, so a catchment whose leases sit mostly in Direct / Unknown is visibly one the current sources are not reaching, and the manager can see which locations are carrying the portfolio's leasing performance. It does not rank channels within each catchment, but without the column the totals are accurate and almost impossible to act on, which is the usual failure mode of portfolio-level reporting. It is worth adding before the first export rather than after it.
A large share of build-to-rent demand comes from households who could buy but have decided not to, or cannot quite yet. That makes the segment unusually sensitive to things no marketing team controls: what a mortgage costs this quarter, what deposits look like, whether the local sale market has stalled. Inquiry volume can double or halve for reasons that have nothing to do with the campaigns running underneath it. A campaign that looks transformational in one quarter can be doing nothing more than standing in the path of demand that changed direction for entirely external reasons.
The consequence is that year-on-year channel comparisons made on lead volume are almost meaningless here. A source can look transformed in a quarter when all that changed was the alternative. Judging campaigns on signed leases and rent billed at least anchors the comparison to an outcome, and comparing the same weeks across two years rather than consecutive months removes some of the noise. It does not remove the effect, and nothing can. What it does is stop a market movement being recorded as a marketing achievement and budgeted against next year.
It also changes what the unattributed share means. When conditions push people toward renting, a good deal of demand arrives directly and would have arrived whatever ran. Reporting that honestly as Direct rather than distributing it across the paid channels is the difference between knowing the market did the work and believing the media did. That distinction is the whole reason the unattributed bucket is never redistributed: a Direct share that grows in a hard sales market is information, and spreading it across the paid channels would destroy it.
A typical community has a developer who built it, a third-party manager who operates it, and a capital partner who wants to know how the lease-up is going. The signed leases live in the manager's property system. The marketing spend lives with an agency or the developer's own team. The performance narrative that reaches the capital partner is assembled by hand from both, monthly, by somebody with other work to do. Each of the three has a different question, a different timescale and a different system, and none of them owns the reconciliation.
Nothing in that arrangement is unusual and all of it works against measurement. The manager has no particular interest in campaign performance, the agency has no access to lease data, and the reconciliation only happens when somebody asks for it. Meanwhile the decisions that matter most — whether to keep spending into phase two — are taken on the basis of the last verbal update. It is not that anybody is obstructing the work. It is that the work belongs to nobody, which in practice means it happens late, by hand, and only when somebody senior asks for it.
Because the inputs are two CSV exports, the arrangement stops mattering. The manager runs a signed-lease export, the agency supplies its inquiry data, and either can be invited into the same workspace without either giving up access to their own systems. Nobody integrates anything, and the resulting ranking is one both parties can inspect line by line rather than dispute. Disagreements after that are about what the numbers mean rather than about where they came from, which is a considerably more productive argument to be having during a lease-up.
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
Add the syndication inquiries to the lead file, tagged with each feed, and they rank on revenue beside paid search. They may win; it is still worth the evidence.
Good. A signed-lease export from it with a contact detail, an amount and a date is the file.
And the next community will be leased up on what you learn from this one, which is exactly the argument for measuring it properly.
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 build-to-rent and single-family rental community operators — 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.
Signed leases or billed rent: a resident email or phone, the amount, and a date.
No; the report does not compute time from inquiry to lease. It credits each lease to the earliest inquiry however long ago it was, so a long lease-up does not lose its channel.
Yes — later rent credits the channel that produced the original resident.
Yes: map a phase or building column as Product / service and each shows as its own line.
Yes: a community column mapped as Location shows each community's revenue and how much of it traces to a channel.
Yes. They are often the best lead file a lease-up has.
No. Where you already run call tracking, the caller's number is a clean key and raises the match rate, but it is not required — a lead export from your ad platforms is enough to start.
Yes — resident records are encrypted both in transit and at rest, kept inside your own workspace, and removable on request. A DPA is available.
Yes: a community or submarket column mapped as Location. A scattered portfolio behaves like several small properties, and a single blended figure across them describes none of the individual markets.
It distorts lead counts more than revenue. Compare the same weeks across two years rather than consecutive months, and judge sources on signed leases rather than on inquiries received.
They run the export, or are invited into the workspace directly. Neither party has to grant access to their own systems, because the inputs are two CSV files rather than an integration.
Yes, in one workspace, with seats and roles deciding who can import and who can only read. It may be the first time the inquiry data and the lease data have been in the same place without somebody assembling a slide by hand.
Yes, if they are in the export as rows against the same resident. They credit whichever source produced that household, which is the honest treatment of ancillary income.
Usually that conditions were pushing households toward renting anyway. It is reported as Direct rather than shared out, so you can tell market movement from campaign performance.
Nearby
Match signed leases and the rent they earn to the listings, portals and campaigns that produced the resident.
See how it worksOne season decides the year. Match signed beds and the rent they earn to the campaigns that produced the inquiry.
See how it worksMatch signed doors and the recurring fees they earn to the campaigns that produced the owner.
See how it worksWhere your sales already are
Match signed leases and the rent they earn over a tenancy to the campaigns and calls that produced the resident.
What to exportExport signed leases and billed rent, and rank every demand source on the money rather than on the leads it delivered.
What to exportExport signed leases from Rent Manager, upload the inquiries beside them, and rank listing sites and campaigns on leases rather than on leads.
What to exportExport management fees from Propertyware, upload your owner lead sources, and rank marketing on the doors it actually won.
What to exportExport executed leases from MRI, upload the sources that produced the inquiries, and rank marketing on lease value.
What to exportExport executed leases from Entrata, upload the sources behind them, and rank on effective lease value rather than on leads.
What to exportFrom 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 articleA multi-location business that reports one national attribution number is hiding its most important finding. The same campaign performs differently in every market, and the aggregate is an average of things that should never have been averaged.
Read the articleFirst touch, last touch, linear, time decay, U-shaped, data-driven. Six ways to divide a number that nobody has verified. Here is what each model is actually claiming, when the choice genuinely matters, and why arguing about it before you can match a sale is arguing about the wrong thing.
Read the articleStart today
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