How GrooveGrid measures rental energy readiness

Baseline Method

We establish your pre-optimization energy baseline using 12 months of historical utility data (via Green Button API or bill upload). For new enrollments without history, we use a weather-normalized regression model using NOAA HDD/CDD data and EIA regional consumption benchmarks for your property type.

Counterfactual

We compute what you would have paid without GrooveGrid by projecting baseline consumption forward using your actual utility rate schedule, adjusted for weather. This is the “do nothing” scenario.

Opportunity Attribution

We frame savings as opportunity across five non-overlapping categories. Each is measured against the counterfactual and tagged with who benefits (owner, tenant, or both):

1. Owner-paid waste— common-area loads, idle equipment, oversized gear on the owner’s meter (kWh avoided × rate; verified against owner-side meters only).
2. Tenant cost pressure — envelope, equipment, and scheduling improvements that reduce bills tenants pay, reported as opportunity in the building. We do not assume the landlord controls tenant comfort.
3. Missed incentives captured— Mass Save, HEAR, HEAT Loan, weatherization, and similar programs the property qualifies for but isn’t using. Tracked as eligibility → submission → award.
4. Avoided repairs— equipment trending poorly, freeze risk, moisture/ventilation flags. Reported per event flagged, with conservative event-cost ranges; only counted as “avoided” when a corrective action is logged.
5. Upgrade prioritization — heat pump, insulation, water heater, and weatherization scopes ranked by payback, deadline, and incentive stack. Recorded as decisions made, not promises about future bills.

Battery dispatch revenue (ConnectedSolutions and similar VPP/DR programs) is reported separately as actual cash received, not estimated.

These categories do not overlap. A kilowatt-hour of waste removed is counted once. An incentive captured is counted once. Avoided-repair credit requires a logged corrective action.

Sensitivity

Savings estimates carry a ±20% range reflecting variation in weather, occupancy, and equipment performance. We report actuals vs. estimates monthly and update projections quarterly.

Methodology note

This approach follows CalTRACK methodology (OpenEEmeter, Apache 2.0 license) for savings verification, consistent with DOE IRA Home Energy Rebate standards.

Architecture note

GrooveGrid is the small-landlord product surface. Underneath it sits the Project Flux platform:

• Flux EQ — the data collection / signal layer. Reads utility (Green Button, Bayou), weather, and equipment telemetry. Produces an honest record of how each building actually performs.
• Flux Insight — the analytics / recommendations layer. Takes Flux EQ signals, applies the baseline + opportunity attribution above, and ranks the shortlist customers see in the GrooveGrid app and monthly readiness report.

The broader utility / meter / grid-edge data world (e.g. advanced metering platforms in the Itron, Honeywell, Landis+Gyr category) is a useful frame of reference for what data can exist about a building. GrooveGrid does not integrate directly with those platforms or imply any partnership; we work from the customer-authorized utility data feeds the property already has, and may add direct integrations only when a customer explicitly enables them.

Functionally, this gives each customer a private property energy grid: a decision grid across the rentals they own. It is owned by the customer, scoped to their portfolio, and distinct from the public utility grid.

Our OpportunityAttributionService and BaselineEngine are in active development inside Flux Insight. Estimates today use regional benchmarks; we switch to property-specific attribution as Flux EQ accumulates 12 months of meter data. Every figure on this site is currently an estimate with the sensitivity range above — not an actual. As we onboard customers, we’ll publish actual vs. estimate performance on this page.

Trust & data handling

Trust is part of the product, not a bolt-on. The principles below are how we operate by default — they make GrooveGrid easier to adopt, not harder.

• Customer-authorized data. Every account connection — utility, weather, equipment, property records — is initiated and authorized by the customer. You can revoke any connection at any time and your historical data goes with you.
• Minimum necessary signals.Flux EQ ingests only the signals needed to score the building and match it to programs. We don’t collect data we don’t use, and we don’t resell or rebroker it.
• Building performance, not personal behavior. Models look at envelope, equipment, weather response, and load shape — not occupancy patterns or individual households. There is no tenant surveillance.
• Read-mostly by default.Flux EQ reads. Write actions (e.g. enrolling a meter in a program, suggesting a thermostat schedule on the owner’s account) require a second, explicit owner action — and never override a comfort band a tenant controls.
• Resident comfort preserved. Recommendations are framed as building improvements (insulation, equipment right-sizing, scheduling on owner-side accounts) rather than nudging tenants. Comfort is the floor, not the lever.
• Secure handling of bills, meters, devices, and property records. Encryption in transit and at rest, scoped per-customer access, audit logging, and defined retention windows. Account credentials use tokenized OAuth-style flows where the upstream provider supports them.

None of this is meant to make adoption feel heavy. It is the posture we’d want as a customer ourselves.