One repeatable motion, tested as discrete hypotheses #
This is the front end (Step 1: Scope) of the Scope → Source → Secure motion. It is deliberately scoped down to what can be tested this fall, with resource needs and hire triggers tied to demand signals rather than the calendar.
1. The logic chain ("if this, then this… then profit") #
Trusted channels put us in front of co-op / building decision makers at low acquisition cost.
Screening (channel signal on owner interest + public-data economics incl. J-51 windfall + BEPS/LL97 compliance pressure) tells us which buildings are worth approaching and gives them a "why now."
Those decision makers say yes to Scope — commit $500 (paid, or line-itemed into their 2027 budget). ← sign of life
We deliver a refined Scope output remotely (no site visit) at a low, repeatable unit cost.
The Scope output gives them the confidence to pull through to Source (managed procurement) — where the real transaction-fee revenue sits.
Repeat → a repeatable sales motion → back-end transaction revenue.
The fall test isolates steps 3–5. Steps 1–2 are validated as a by-product (does the channel actually produce qualified yeses?). Steps beyond 5 (feasibility study, yes-to-construction) are named below but not tested this fall.
Each is written as a belief with a precise success threshold, a cheapest-first test, and a clear pass/fail signal. Tagged by risk type (Desirable → Feasible → Viable, tested in that order) and by priority on the assumptions map. See Figure 1 for where each sits.
TEST FIRST — top-right quadrant (Important, little/no evidence) #
H1 — Willingness to pay for Scope (Desirability + Viability)
We believe we can get 100 channel-referred decision makers to say yes to Scope in 2026 — "yes" = $500 paid now or line-itemed into their 2027 budget.
Cheap signal: Aurora PM customers (Akam, Elliman, Lovett, etc.) put the $500 line into N 2027 building budgets as an opt-in.
Stronger signal: board signs proposal and $500 collected.
Pass: 100 yeses. Fail: materially short of 100.
This hypothesis is only about demand — will they part with money. Whether we can actually produce the Scope, and whether $500 covers its cost, are H5.
H2 — Pull-through to Source (Desirability)
We believe that ≥[10%] of decision makers who receive a delivered Scope will tell us they want to proceed to the next step of an on-site feasibility study (Source / bid).
Test: structured "what next?" capture at Scope delivery for every one of the ~50 outputs.
Pass: pull-through at/above target. Fail: they take the Scope and stop — Scope is a nice PDF, not a funnel.
This is the difference between "someone was polite and paid $500" and "there is real demand pulling us toward the revenue." Together with H5's Source economics, it decides whether Scope-as-loss-leader is worth it.
We believe we can collect enough site data without a site visit (site contact submits unit-mix, layouts, panel/outlet photos) to produce a Scope with cost-estimate uncertainty within ±[X%].
Test: run the remote-intake path on the first cohort; compare against any case where we later get ground truth.
Pass: uncertainty inside the band on enough cases to price confidently. Fail: we still need truck-rolls to trust the number.
H4 — Structured intake at scale (Feasibility)
We believe we can capture decision-maker goals + building needs relying primarily on a structured intake (survey tool), supplemented by Google Meet calls, at ≤[Y] of my time per building.[set time]
Test: stand up the intake tool; log time per building (I can do this manually today — the open question is scaling it off my phone).
Pass: time-per-building trends down and holds. Fail: every building still needs me on the phone.
H5 — Scope delivery + unit economics (Feasibility + Viability)
Two linked claims:
(a) Delivery.We believe we can deliver ≥50 Scope outputs in 2026 — i.e., we can actually execute the remote Scope at volume. (This is the execution side; it has nothing to do with willingness to pay, which is H1.)
(b) Economics — Scope as an understood loss leader.We believe the fully-loaded cost of a Scope, net of its $500 price, is low enough to be justified by the downstream Source revenue it unlocks.
Ideal: break even at the portfolio level on the $500 alone.
More likely: Scope is an understood loss leader. It is viable when:
Directional goal (not pass/fail): per-Scope net loss shrinking toward break-even on the trailing batch of ~50 as H3/H4 drive cost down. Getting close to break-even on the last 50 is a good result — but it is not a standalone pass/fail. A Scope that loses money is fine if conversion (H2) × Source fee more than covers the loss.
Judged jointly with H2 and realized Source economics, and fed by the time log in §6. This is measured, not run as a separate experiment.
PARKED — full arc, named for completeness, tested in 2027 (Source / Secure phase) #
(P1, was Q4) Deeper feasibility study:We believe owners will pay $3–5k to bring an electrician for a deeper study. → Source-phase desirability, early 2027.
(P2, was Q5) Yes-to-construction:We believe owners will accept a procurable retrofit proposal. → Secure-phase, later.
Channels (business-aligned): Aurora Energy Advisors (Akam, Douglas Elliman; other 3rd-party managers), First Service Energy (~98k units; 247 "simple" buildings identified).
Channels (mission-aligned): Green Co-op Council (~600 members), CNYC.
Channels (not yet identified): other 3rd-party managers or mission-aligned orgs that can serve as one-to-many aggregators of buildings.
Subs (downstream only): electricians for feasibility studies.
Scope ($500) is a sign-of-life product and, by design, an understood loss leader — not the profit engine. Ideal is portfolio-level break-even on the $500; the honest expectation is a small per-unit loss that Source revenue more than repays (see H5).
Revenue engine = Buy whole scope through Cadence.
So 2026 Scope revenue is intentionally small. The purpose of 2026 is to prove H1 + H2 — that a repeatable, channel-fed motion produces paid yeses that pull through — which is what (a) justifies the raise and (b) triggers the PM hire to build out the Source/Secure back end where the money actually is.
6. Resource needs (baked in, minimal, demand-triggered) #
The core motion and all four hypotheses (H1–H4) are identical across channels. Only the go-to-market wrapper differs. Running the same hypotheses through both channel types is itself a discrete experiment: which channel type produces qualified yeses more efficiently?
Business-aligned (Aurora, FSE)
Mission-aligned (Green Co-op Council, CNYC)
Their incentive
Rev-share — they win when we win
No rev-share — they want to serve members
Entry point
Formal, via property-management process; opt-in off Aurora energy grades
Email blasts, webinars, J-51 calculator embedded on their site
First offer
$500 Scope directly
Free initial consult to build trust → then the $500 Scope offer
What the comparison tells us: if pull-through (H2) and pay-rate (H1) hold up in the mission-aligned channel without a rev-share hook, the market is broader than the property-manager relationships. If they only work where a partner has skin in the game, we double down on Aurora/FSE-type channels and treat mission channels as awareness, not pipeline.
Above all ladders up to testing a Productized Service model referenced by @bomee here. I have also heard this described in the past as a "mass customization" approach: the process of delivering market-wide goods and services that are modified to satisfy a specific customer need. A marketing and manufacturing technique that combines the flexibility and personalization of custom-made products with the low unit costs associated with mass production. So the owner thinks they are special by their front-end treatment, but the back end is a bunch of Lego bricks.
Placeholders in [brackets] are thresholds for us to set together: H2 pull-through target, H3 uncertainty band, H4 time-per-building, and the two hire triggers.
Strategy Notebook
SCOPE — MZ Fall 2026 Test Plan
One repeatable motion, tested as discrete hypotheses #
This is the front end (Step 1: Scope) of the Scope → Source → Secure motion. It is deliberately scoped down to what can be tested this fall, with resource needs and hire triggers tied to demand signals rather than the calendar.
1. The logic chain ("if this, then this… then profit") #
The fall test isolates steps 3–5. Steps 1–2 are validated as a by-product (does the channel actually produce qualified yeses?). Steps beyond 5 (feasibility study, yes-to-construction) are named below but not tested this fall.
2. The hypotheses #
Each is written as a belief with a precise success threshold, a cheapest-first test, and a clear pass/fail signal. Tagged by risk type (Desirable → Feasible → Viable, tested in that order) and by priority on the assumptions map. See Figure 1 for where each sits.
TEST FIRST — top-right quadrant (Important, little/no evidence) #
H1 — Willingness to pay for Scope (Desirability + Viability)
We believe we can get 100 channel-referred decision makers to say yes to Scope in 2026 — "yes" = $500 paid now or line-itemed into their 2027 budget.
H2 — Pull-through to Source (Desirability)
We believe that ≥[10%] of decision makers who receive a delivered Scope will tell us they want to proceed to the next step of an on-site feasibility study (Source / bid).
TEST ALONGSIDE — Important, partial evidence #
H3 — Remote site-data sufficiency (Feasibility)
We believe we can collect enough site data without a site visit (site contact submits unit-mix, layouts, panel/outlet photos) to produce a Scope with cost-estimate uncertainty within ±[X%].
H4 — Structured intake at scale (Feasibility)
We believe we can capture decision-maker goals + building needs relying primarily on a structured intake (survey tool), supplemented by Google Meet calls, at ≤[Y] of my time per building.
[set time]THE VIABILITY QUESTION — delivery + economics (partly executed, partly derived) #
H5 — Scope delivery + unit economics (Feasibility + Viability)
Two linked claims:
(a) Delivery. We believe we can deliver ≥50 Scope outputs in 2026 — i.e., we can actually execute the remote Scope at volume. (This is the execution side; it has nothing to do with willingness to pay, which is H1.)
(b) Economics — Scope as an understood loss leader. We believe the fully-loaded cost of a Scope, net of its $500 price, is low enough to be justified by the downstream Source revenue it unlocks.
Ideal: break even at the portfolio level on the $500 alone.
More likely: Scope is an understood loss leader. It is viable when:
Directional goal (not pass/fail): per-Scope net loss shrinking toward break-even on the trailing batch of ~50 as H3/H4 drive cost down. Getting close to break-even on the last 50 is a good result — but it is not a standalone pass/fail. A Scope that loses money is fine if conversion (H2) × Source fee more than covers the loss.
Judged jointly with H2 and realized Source economics, and fed by the time log in §6. This is measured, not run as a separate experiment.
PARKED — full arc, named for completeness, tested in 2027 (Source / Secure phase) #
3. Goal (time-bound) #
[set]4. Who's involved #
5. How & when we make money #
6. Resource needs (baked in, minimal, demand-triggered) #
Tooling required to run the fall test #
My time — to be documented (the begrudging part) #
A time log, per opportunity, across the motion's steps, so we can see unit economics (feeds H5) and what to automate/hand off:
Two hires — commissioned/triggered, not consultants hired ahead of demand #
[set]. Commission structure means cost tracks revenue.[set].7. Channel variants #
The core motion and all four hypotheses (H1–H4) are identical across channels. Only the go-to-market wrapper differs. Running the same hypotheses through both channel types is itself a discrete experiment: which channel type produces qualified yeses more efficiently?
What the comparison tells us: if pull-through (H2) and pay-rate (H1) hold up in the mission-aligned channel without a rev-share hook, the market is broader than the property-manager relationships. If they only work where a partner has skin in the game, we double down on Aurora/FSE-type channels and treat mission channels as awareness, not pipeline.
8. Final aside #
Above all ladders up to testing a Productized Service model referenced by @bomee here. I have also heard this described in the past as a "mass customization" approach: the process of delivering market-wide goods and services that are modified to satisfy a specific customer need. A marketing and manufacturing technique that combines the flexibility and personalization of custom-made products with the low unit costs associated with mass production. So the owner thinks they are special by their front-end treatment, but the back end is a bunch of Lego bricks.
Placeholders in
[brackets]are thresholds for us to set together: H2 pull-through target, H3 uncertainty band, H4 time-per-building, and the two hire triggers.