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Energy Comparison
Tariff Optimisation
Customers often pay more because they're on the wrong tariff structure. Fiskil analyzes usage patterns to identify the optimal tariff type for maximum savings.
Many customers would save on different tariff structures but don't know which would be optimal.
Customers don't understand tariff structure options
Time-of-use plans can save or cost money depending on usage
Demand tariffs complex to evaluate without analysis
Solar customers need specific tariff structures
No easy way to determine optimal tariff type
Analyze usage patterns to determine which tariff structure delivers lowest costs.
Model costs under flat rate, time-of-use, and demand tariffs using actual usage.
Identify if usage concentrates in peak or off-peak periods.
Evaluate if demand-based tariffs would be beneficial.
Suggest usage timing changes to maximize tariff savings.
Add tariff structure optimisation to your energy comparison tool.
Access customer usage data including interval data if available.
API analyzes when energy is consumed (peak vs off-peak vs shoulder).
Calculate costs under different tariff structures using actual usage.
Identify tariff structure with lowest cost and quantify savings.
For smart meter customers, analyze 30-minute interval data for precise optimisation.
Identify proportion of usage in peak, shoulder, and off-peak periods.
Model demand charges based on peak kW demand patterns.
Optimize both import and export tariffs for solar customers.
Show potential savings if usage shifted to off-peak periods.
Account for seasonal changes in usage patterns and timing.
A smart home app recommends optimal tariff based on appliance usage patterns.
Result: Customers shifting to time-of-use save average of $380/year.
A retailer analyzes customer usage to recommend optimal tariff products.
Result: Customer satisfaction up 25% by proactively optimizing customer tariffs.
A consultant optimises business tariffs using demand pattern analysis.
Result: Commercial clients save average of 18% through tariff optimisation.
GET /energy-accounts/{accountId}/usage-timingPOST /energy/tariff-comparisonGET /energy/optimal-tariffPOST /energy/behavior-recommendationsInterval usage data
Peak/off-peak breakdown
Demand patterns
Tariff cost comparisons
Optimal tariff recommendation
Potential savings
OAuth 2.0 / CDR consent
Yes
Flat rate, time-of-use (peak/off-peak/shoulder), demand-based, and controlled load tariffs.
Smart meters enable most accurate analysis, but daily usage data can still provide valuable insights.
Yes, if usage concentrates in peak periods. Analysis identifies this before switching.
Analysis factors in both import and export patterns to optimise total tariff structure.
Yes, system can model savings from shifting usage to off-peak periods (e.g., running pool pump at night).
Annually or when usage patterns change significantly (solar installation, EV purchase).
Demand pattern analysis identifies if demand tariffs would be more economical than usage-based tariffs.
Energy Comparison
Analyze energy bills and usage patterns to provide accurate switching recommendations. Fiskil's Energy API enables instant bill analysis from 40+ Australian energy retailers.
Energy Comparison
Recommend the best energy plan for each customer based on actual usage data. Show accurate savings and guide customers to optimal energy deals.
Solar Providers
Calculate precise solar savings using actual household energy consumption. Show realistic payback periods and ROI based on real usage patterns.
Join hundreds of companies using Fiskil to power their energy comparison applications. Get started today with our developer-friendly API.
Products
© Fiskil 2026. All rights reserved.