Papago Vans
Data request · Internal

Prepared for ownership · Papago Vans

Replace the guesses
with your numbers.

The Papago Collection pro forma currently rests on two figures Papago supplied and about a dozen I built from industry ranges. It is directionally useful and it is not good enough to decide on. Everything below already exists somewhere in the business. Handing it over turns a model into a plan, and it is the fastest thing anyone can do to make the marketing work real.

Answer them right hereEvery question below has an answer box under it. Type whatever you have and it saves as you go. Partial answers are useful, so is marking something as not existing. This page is behind a login, so only you see it.
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The eleven that unlock everything else

If nothing else on this page happens, these eleven still answer the questions that matter. Raw exports are better than summaries. A messy spreadsheet beats a clean report, because the outliers are where the answers live.

01

Which price is actually current

A single authoritative price list for all five tiers with the effective date, plus the date of every price change over the last 24 months. Five minutes of somebody's time.
Papago is publishing three different prices for the same van right now. The build tiers hub quotes El Capitan at $96,466, the tier page says $127,395, and the FAQ carries a third Rainier figure again. Nothing downstream can be modeled until somebody says which list is real, and no revenue projection means anything without the dates the prices changed.
Likely source · Whoever sets pricing, plus the website team
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02

Job cost detail, last 20 completed builds

Contract price, final invoiced price, and cost broken into chassis, materials, outside services and labor hours. One row per build.
Replaces every margin number in the pro forma. Right now $41,000 gross profit per custom van is inferred from industry ranges, not from Papago's books.
Likely source · Accounting system job costing, or the job folders
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03

Shop hours by phase, same 20 builds

Hours logged against design, sourcing, rough-in, cabinetry, electrical and plumbing, finish, QC and rework. Separated, not just a total.
Settles the 50% production-time claim, which is the single load-bearing assumption in the whole proposal. If it is really 25%, converting bays loses money.
Likely source · Time tracking, shop travelers, or payroll allocation
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04

The 2025 scoreboard

For calendar 2025: vans sold, meaning signed contract with a deposit taken. Vans delivered, meaning handed to a customer. Average sale price. Total revenue. Backlog on January 1 and December 31. Cancellations and refunded deposits.
Sold against delivered is the cleanest test of whether capacity or demand is the real constraint. Sold above delivered means the queue is growing and Papago Collection is the release valve. Delivered above sold means demand is the ceiling and adding throughput just builds inventory. Average sale price and revenue also put a range behind the $190,000 the entire model rests on.
Likely source · Contracts, the delivery log, and the P&L
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05

Layout and option selections, every build ever

Floor plan, bed configuration, galley, bath, electrical package, and the specific major components chosen. Fridge, inverter, battery, heater, AC, seating.
Tells us what the three fixed plans should actually be. The lineup has to come from build history, not a whiteboard.
Likely source · Build sheets, CAD files, or the sales configurator
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06

Change order log by build

Count, dollar value, hours added, calendar days added, and what triggered each one.
Quantifies the cost of full customization. This is the number that proves Papago Collection's margin advantage is real rather than asserted.
Likely source · Contracts and job files
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07

Lead volume and source, 2025, through to close

Total leads for the year broken out by source: organic search, paid search, paid social, referral, repeat customer, trade show and events, direct, partner, and unattributed. Then quotes issued, deals closed, sales cycle length, and on every lost deal both a reason code and, critically, the name of who we lost it to. Monthly if it exists, with 2024 alongside for trend.
The only half of this the capacity model cannot solve. Papago Collection needs roughly double the buyers and nothing so far proves they exist. The competitor names on lost deals matter more than any other field here: they decide whether the Boho analysis is a priority or a distraction, and whether Papago is actually losing to other custom shops, to factory Class B units, or to people deciding to buy nothing at all. Those are three different problems with three different fixes.
Likely source · HubSpot. Audit this myself first rather than asking for it.
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08

Marketing and advertising spend, 2025, by channel

Every dollar, split out. Paid search, paid social, trade shows and events, print, sponsorships, influencer and content, website and tooling, and any agency or contractor fees. Media spend separated from fees.
Paired with 2025 units sold and revenue, this produces cost per sale and marketing as a percent of revenue. Those are the two numbers I will be measured against and neither one exists today. It also shows which channels have already been paid for and tested.
Likely source · P&L detail, ad platform billing, and card statements
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09

Warranty claims and service calls, 2025

Every claim and service visit for the year, tied back to the build it came from. What failed, which component or system, labor hours to resolve, parts cost, in or out of warranty, and days from delivery to first claim.
Warranty scales with van count, not revenue. Papago Collection doubles the units, so this is the cost line that grows against the proposal and the pro forma currently ignores it entirely. Tied back to layouts it also shows which configurations warrantied cleanest, which should drive the three-plan lineup more than any other input.
Likely source · Service records, the warranty log, or the techs' job tickets
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10

Are we tracking lost deals, and why we lose them?

Get into HubSpot and find out. Is there a closed-lost reason property. Is there a competitor field. Are either of them actually populated, or blank on most records. Same question for lead source attribution and lifecycle stages. This one is mine to answer, not ownership's.
Half the items above assume the data exists somewhere. For anything sales-side it lives in HubSpot or it does not exist at all. Closed-lost reason and competitor are the two most commonly ignored properties in any CRM, because a rep closing out a deal has no incentive to fill them in. If they are blank, the honest answer is that the history is gone and no amount of asking recovers it. The fix then is to make both fields required and start capturing from day one, which takes about an hour to configure and produces a usable quarter of data before any budget conversation.
Likely source · HubSpot itself, once I have a login
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11

Which customers are unhappy, and what do we already know?

A named list of customers who have complained publicly, or who service knows are unhappy, with the status of each one. What is still open, who owns it, what was promised and when. Ask for this before naming anything specific, because what gets volunteered unprompted is itself part of the answer.
There is a live thread on r/VanLife naming several owners. It was posted in January, went quiet for five months, restarted in late August and had a new comment on 11 September. Two prospects say in it that unanswered emails sent them to another builder, and one names a competitor fifteen minutes away as the better choice. There is no reply from Papago anywhere in it. If this list comes back thorough, we inherit a problem already being worked and the job is to finish it and make the recovery visible. If it comes back short or blank, the finding is not that some customers are unhappy, it is that nobody is watching, and that is a week-one fix that costs nothing.
Likely source · Service department, ownership, and whoever fielded the calls
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Items 01 and 10 need nobody's permission. Do those first. One is a five-minute question about which price list is real, the other is an hour inside HubSpot finding out whether we have been tracking lost deals at all. After those, if only one of the rest is possible, make it number three. Shop hours by phase decides whether Papago Collection builds in half the time. That single assumption is the difference between converting a bay being worth $114,000 a year and being worth less than nothing. Every other number on the pro forma moves a result. This one decides whether there is a proposal at all.

The full list

Everything worth asking for

P1 blocks the model. P2 sharpens it. P3 is useful later. Nothing here needs to be compiled or prettied up first.

Unit economics

Data pointPriorityWhat it answers
Contract price and final invoiced price per buildP1Real average ring-up, and how far final lands from contract
Average sale price and total revenue, 2025P1Puts a range behind the $190,000 the model rests on
Authoritative current price list, all five tiersP1Three conflicting prices are live on the site today
Price change history with effective dates, 24 monthsP1Which revenue belongs to which price. No trend is readable without it
Whether any quotes were honored at the stale lower pricesP1Margin already given away, and whether it is still happening
Chassis purchase price by configurationP1Confirms or corrects the $62,000 assumption
Chassis lead time, order to deliveryP1Sizes the working capital float
Materials cost per buildP1Replaces the $45,000 estimate
Outside services and subcontract costP2Hidden COGS the model currently ignores
Loaded labor rate by roleP1Converts shop hours into dollars
Warranty and service cost per delivered unitP1Scales with van count, not revenue. Grows against Papago Collection.
Warranty claims and service calls by build, 2025P1Which layouts and components actually hold up in the field
Most frequent failure points by component or systemP1What to engineer out of the fixed plans before building 72 of them
Days from delivery to first claimP2Whether failures are build quality or wear

Production and capacity

Data pointPriorityWhat it answers
Number of build bays or stationsP1The whole model is denominated in bays. Mine is inferred.
Headcount by role, and who is billableP1Separates direct labor from overhead
Calendar days: deposit, design approved, build start, deliveryP1Confirms the 4 to 5 month design queue
Units delivered by month, last 24 monthsP1Tests whether 24 per 8 months is typical or a good stretch
Units sold by month, last 24 monthsP1Paired with deliveries, shows whether the backlog is growing or shrinking
Rework hours per buildP2The cost of custom, stated in hours
Bay utilization or idle timeP2Whether capacity is really the constraint

Demand and pricing

Data pointPriorityWhat it answers
Signed backlog and deposit scheduleP1How much runway exists before new demand is needed
Backlog on Jan 1 and Dec 31, 2025P1The year's net change in queue depth, in one number
Cancellations and refunded deposits, 24 monthsP1What the long wait actually costs in lost signed revenue
Lead volume by month and source, 2025 and 2024P1Demand baseline, and which channels already produce buyers
Lead to quote and quote to close rate by sourceP1Which channels send real buyers versus tire kickers
Share of leads with no known sourceP1How much of the picture attribution is currently missing
Repeat and referral share of total leadsP2How much volume is earned rather than bought
Lost deal reasons, codedP1Tells us whether price or timeline is losing deals
Who we lost each deal to, by name, 2025P1Whether Boho and the other shops are real rivals or background noise
Lost to a competitor vs lost to no decisionP1Usually the largest bucket is no decision. A completely different fix.
Lost to a custom shop vs a factory Class BP1Losing to a Revel is a positioning problem. Losing to Boho is a local fight.
Any deal lost where Papago was never quotedP2Deals lost before a conversation started, which is a marketing failure, not a sales one
Any discounting historyP2Real price realization versus list
Buyer geographyP2Where delivery logistics and ad spend should point
Waitlist or unconverted inquiry volumeP2Latent demand that a published price might convert

Financial context

Data pointPriorityWhat it answers
P&L, last three fiscal yearsP1Connects this model to the actual business
Monthly fixed overheadP1Turns gross profit into operating income
How chassis are financedP1Floor plan, cash, or customer deposit changes the cash ask entirely
Deposit structure and payment milestonesP2Cash timing across a build
Appetite for working capitalP2Sets the ceiling on batch size

Marketing baseline

Data pointPriorityWhat it answers
Named list of publicly unhappy customers, with case statusP1A live Reddit thread names several. Whether we already know is the real question
Who owns responding to public complaints, and in what toneP1Currently unanswered, which means the decision is being made by default
Total 2025 spend by channel, media separated from feesP1Cost per sale and marketing as a percent of revenue, my two baseline numbers
Trade show and event spend, 2025P1Usually the largest line in this category and the hardest to attribute
Agency, contractor and freelance feesP2What is already committed before any new spend
Website traffic and conversionP1Baseline before anything changes
CRM and attribution setup, if anyP1Whether results will be measurable at all
Cost per lead and cost per sale, if knownP2What a Papago Collection buyer can cost to acquire
Past campaign resultsP3What has already been tried

Ask for the export, not the summary. The outliers are where the answers live, and summaries are built to hide them.

How to make the ask

How to ask

Four notes that make this land

Do this

  • Ask for raw exportsA CSV out of the accounting system beats a report someone built by hand. Hand-built reports round, average and quietly drop the builds that went badly, which are the most informative ones.
  • Ask per build, not in aggregateAn average gross margin hides the spread. Twenty individual builds show whether custom margin is consistently 22% or swings from 8% to 35% depending on how the change orders went.
  • Name who likely has itJob cost and P&L sit with whoever does the books. Hours and layouts sit with the shop. Leads sit with sales. Asking three people for three things lands better than asking one person for twenty.
  • Say what each one unlocksNobody enjoys a data request. People will dig for a number if they know it decides something. The third column of every table above exists for exactly that.

Expect this

  • Some of it will not existSmall builders often do not track hours by phase. If that is the case, say so early and set up tracking on the next three builds rather than reconstructing the past.
  • Some of it will be wrongJob costing in a custom shop is frequently approximate. Sanity-check any per-unit margin against total P&L gross profit divided by units delivered.
  • HubSpot may not have been logging lossesClosed-lost reason and competitor are the two most commonly ignored properties in any CRM, because a rep closing a deal has no incentive to fill them in. Audit this before asking anyone for the report. If the fields are blank, the honest answer is that the history does not exist and no amount of asking recovers it.
  • If it is not there, start MondayRequired closed-lost reason and a competitor picklist on the deal record costs nothing and takes an hour to configure. A quarter of real data beats a year of reconstructed guesses, and it is the cheapest thing in this entire document to begin collecting.
  • Asking is itself a signalA marketing hire who opens with a job-cost request rather than a logo refresh tends to get taken seriously by an owner. That is worth something on its own.
What happens once this arrives. Item 01 settles which price list is real, which everything else is denominated in. Items 02 and 06 rebuild the cost stack and produce a real gross profit per van for both lines. Item 03 confirms or kills the 50% build-time assumption and sizes the bays properly. Item 04 says whether capacity or demand is the binding constraint, which is the question everything else hangs on. Item 05 selects the three plans from build history. Items 07 and 08 set the demand and spend baseline, so the extra buyers Papago Collection needs become a target with a cost per sale attached instead of a hope, and the competitor names on lost deals say which rivals actually cost us money. Item 09 adds the cost that grows against all of it, and tells us which layouts to standardize on. Item 10 is the reality check on the whole exercise, because anything sales-side is only answerable if HubSpot was recording it in the first place. At that point the pro forma stops being a concept and becomes a forecast anyone can hold a plan against.