Lonta Research — Service mix hypothesis worksheet v1.0
Source: https://lonta.io/research/home-service-demand/
2023 AHS historical household projects are context, not local advertising ROI.

1. One question, written before the test
Service line / exact job scope:
Service area and supported capacity:
Message or offer to test; why the research suggests a hypothesis:
Alternative explanation (equipment stock, building type, price, season, referrals):

2. What every inquiry needs
Inquiry ID; arrival date; requested job scope; serviceable yes/no/unknown;
new/returning/unknown customer; quote amount and date; accepted work and date;
completed work and date; collected revenue and date; variable job costs;
source and attribution rule. Do not collect housing/health/identity data you do not need.

3. Set rules in advance
Included channels and media-only/fee-inclusive cost definition:
Comparable lead-age window and eligible count:
Primary outcome (accepted/completed/paid; choose one):
Guardrails (available technician hours, dispatch loss, margin, phone coverage):
Observation period; minimum local sample; stop/change decision:
Record all outcomes, including unknowns and failed dispatches.

4. Read the result
Did job scope/customer mix change? Were lead ages and attribution comparable?
How much was collected after variable costs? What remains uncertain?
An AHS median is neither a current quote nor a margin/ad-budget ceiling.
The worksheet and research are usable without buying Lonta.

Prepared with Codex. No client outcomes, human review or causal effect asserted.
Lonta original worksheet: CC BY 4.0. Underlying survey sources retain their own terms.