Utilization analytics is the measurement and analysis of how intensely EV charging assets are used—by time, energy delivered, and session activity—at the level of connector, charger, site, and network portfolio. It turns raw charging data into KPIs that support decisions on expansion, pricing, operations, and ROI.
What Are Utilization Analytics?
Utilization analytics focus specifically on “how much the charger is used” and “how efficiently it is used,” typically combining:
– Occupancy time (connector is physically in use / bay occupied)
– Charging time (energy is actively being delivered)
– Energy delivered (kWh) and session count
– Availability and downtime states (operational uptime vs out-of-service)
– Time-of-day / day-of-week patterns and seasonality
Data sources often include:
– Charger status and meter values via OCPP
– Roaming session records (CDRs) via OCPI
– Backend transaction logs and site telemetry
– Payment and support logs (to connect utilization impacts to failures)
Why Utilization Analytics Matter
Utilization is a core driver of charging economics and planning:
– High utilization can justify expansion and additional bays
– Low utilization can signal poor siting, pricing, access friction, or reliability issues
– Utilization patterns influence grid sizing, load management, and tariff strategy
– Correct utilization measurement supports realistic ROI and TCO models
– It helps prioritize O&M efforts where downtime has the biggest revenue impact
Core Utilization Metrics
Common utilization KPIs include:
– Connector utilization rate = time charging (or occupied) ÷ total available time
– Charger utilization (aggregated across connectors)
– Energy throughput = kWh per connector per day/week/month
– Sessions per connector per day/week/month
– Average session duration and average kWh per session
– Peak utilization windows (congestion periods)
– Idle occupancy = occupied but not charging (critical for turnover)
– Availability-adjusted utilization (excludes downtime from denominator)
– Queue indicators (high occupancy + failed starts + peak clustering)
Charging Time vs Occupancy Time
A key nuance in utilization analytics is defining what “used” means:
– Charging utilization: only counts time energy is flowing (best for electrical sizing and throughput)
– Occupancy utilization: counts time a bay/connector is occupied (best for congestion and user experience)
Both matter, and they can diverge significantly when idle time is high.
How Utilization Analytics Are Used
– Expansion planning
– Identify sites where additional chargers are needed
– Determine optimal mix of AC vs DC based on dwell time and throughput
– Plan phased rollout without oversizing grid upgrades
– Commercial optimization
– Adjust tariffs to improve turnover (idle fees, time-based components)
– Evaluate roaming vs direct customer mix and margin impact
– Improve pricing transparency to reduce session abandonment
– Operational optimization
– Find underperforming chargers caused by downtime, comms issues, or connector faults
– Prioritize maintenance based on revenue-at-risk
– Reduce start failures by targeting specific locations or hardware variants
– Policy and enforcement
– Detect bay blocking and poor turnover in public sites
– Support enforcement requests with data (high-demand congestion evidence)
Data Quality and Interpretation Considerations
– Ensure consistent state definitions (available, occupied, charging, faulted, offline)
– Correct time zone handling and charger clock drift
– Avoid inflating utilization by ignoring downtime (always track availability)
– Separate planned maintenance from unplanned outages
– Normalize across sites with different connector counts and power levels
– Consider context: high utilization can be good for revenue but bad for queues if capacity is insufficient
Common Pitfalls
– Treating “occupied” as “charging” and missing idle congestion problems
– Comparing utilization across AC and DC without accounting for dwell time differences
– Ignoring seasonality and local demand drivers (events, tourism, commuting patterns)
– Not linking utilization to session success rate and user satisfaction
– Making expansion decisions without checking grid constraints and transformer lead times
Related Glossary Terms
Usage analytics
Utilization rate
Network performance KPIs
Charging Data Record (CDR)
OCPP
OCPI
Idle fees
Queue management
Load management
Charging ROI modeling