Usage analytics is the collection, processing, and interpretation of data that shows how EV charging infrastructure is being used—across chargers, sites, user groups, and time periods. It helps CPOs, site owners, and fleets understand utilization, performance, revenue drivers, and operational issues so they can optimize pricing, capacity planning, and reliability.
What Are Usage Analytics in EV Charging?
Usage analytics typically combine operational, energy, and commercial data from:
– Chargers and connectors (status, sessions, meter values) via OCPP
– Roaming and customer platforms (CDRs, authorizations) via OCPI
– Payment systems (authorizations, captures, fees, refunds)
– Maintenance systems (fault logs, downtime reasons, repair history)
– Fleet systems (vehicle schedules, telematics) where applicable
Analytics can be real-time (dashboards) or periodic (weekly/monthly reporting).
Why Usage Analytics Matter
EV charging networks are only profitable and reliable when usage and operations are understood and actively managed. Usage analytics support:
– Better site planning and expansion decisions (where to add chargers next)
– Higher uptime through early fault detection and faster troubleshooting
– Pricing and tariff optimization (per kWh, time-based fees, idle fees)
– Improved user experience (reducing session failures and congestion)
– Stronger ROI tracking and TCO management
– Evidence for stakeholders (site hosts, municipalities, investors)
Common Metrics Tracked
– Utilization rate (time occupied / available time, per connector)
– Sessions per day/week/month per charger and per site
– Energy delivered (kWh) per charger, per site, per user segment
– Peak usage windows (hour/day/season) and queue/congestion indicators
– Average session duration and average kWh per session
– Session success rate (started vs failed/aborted)
– Idle time and idle fee exposure (occupied but not charging)
– Revenue per charger and margin drivers (where available)
– Uptime / availability and mean time to repair (MTTR)
– Payment performance: authorization failures, refunds, chargebacks
– Roaming share vs direct customers, and roaming CDR latency
How Usage Analytics Are Used
– Capacity planning
– Identify high-demand sites for expansion and low-demand sites for relocation or pricing changes
– Validate assumptions used in feasibility studies and rollout plans
– Operations optimization
– Detect recurring faults, connector wear, or communication instability
– Prioritize preventative maintenance and parts stocking
– Commercial optimization
– Adjust tariffs and fee rules (idle fees, minimum fees) to improve turnover
– Improve settlement accuracy with transaction reconciliation insights
– Evaluate partner performance in roaming and unified billing setups
– User experience improvements
– Reduce friction by finding where sessions fail (auth, connector, comms, payment)
– Improve signage and bay enforcement where blocking is frequent
Data Quality and Analytics Reliability
Usage analytics is only as good as the underlying data. Key considerations:
– Consistent identifiers (EVSE ID, connector ID, session IDs)
– Accurate timestamps and time zones (charger clock drift can distort KPIs)
– Complete meter values and session lifecycle events (start/stop, partial sessions)
– Clear downtime classification (out of service vs occupied vs offline)
– Alignment between charger logs, backend records, and billing records
Privacy and Governance Considerations
– Limit personal data collection to what is necessary (privacy-by-design)
– Use role-based access and retention rules
– Separate operational analytics from personally identifiable customer data where possible
– Ensure data sharing rules are clear in site host and roaming contracts
Related Glossary Terms
Utilization rate
Network performance KPIs
OCPP
OCPI
Charging Data Record (CDR)
Idle fees
Transaction reconciliation
Unified fleet billing
Predictive maintenance
Total cost of ownership (TCO)