Make smarter decisions with deeper energy insight

Data usage disaggregation breaks total consumption down into meaningful categories, revealing what’s really driving energy use so you can target opportunities with confidence.

Why total consumption isn’t enough

Total energy use only tells half the story

A single consumption figure shows you how much energy a home uses, but not what it’s being used for. Without that detail, it’s difficult to target interventions, model behaviour accurately or identify the real opportunities for change.

Whole-home figures hide the biggest energy drivers

It’s hard to spot inefficiency or opportunity without category-level detail

Low carbon technologies like EVs and heat pumps distort traditional usage patterns

Behaviour-change programmes need specificity to be effective

Raw data alone doesn’t reveal where to act

Granularity

Breakdown from 30-minute smart meter feeds.

Scale

Detailed insight across 10,000+ GB homes.

Categories

Multiple electric and gas usage categories.

Quality

ISO9001, ISO14001 and ISO27001 certified.

Turning raw feeds into smarter data

Our property data disaggregation breaks 30-minute energy data down into distinct usage categories, powered by advanced algorithms refined through three years of consumer feedback.

The result is a clear view of where energy really goes, ready to inform research, planning and product decisions. We break energy down into meaningful categories.

Cooking, heating, entertainment, EV charging, hot water, lighting, refrigeration, washing, always-on devices and more.

Cooking, heating and hot water.

By highlighting a home’s most energy-hungry areas, disaggregation helps you move beyond the numbers and identify clear, evidence-based opportunities for improvements and upgrades.

How it works

From smart meter feeds to actionable insights

Disaggregation sits at the top of Chameleon’s data offering, building on whole-home and enhanced data to deliver our most comprehensive dataset. Each step is designed to turn continuous energy readings into clear, usable insight.

Data collection

Energy data is gathered via our consumer-facing ivie app, connected directly to smart meters.

Consent capture

Explicit consent is gained from every user for the use of anonymised data in research and development.

30-minute feeds

Core electricity and gas data is collected at 30-minute intervals across thousands of homes.

Algorithmic disaggregation

Our refined algorithms break usage down into distinct, meaningful categories.

Category breakdown

Data is separated by fuel type and by usage category, revealing a home’s most energy-hungry areas.

Insight delivery

Results are provided in a clear, interpretable format, ready for analysis and action.

Disaggregated insight can be combined with enhanced home profiling, including property type, occupancy and low carbon technology adoption, for even richer segmentation.

Trusted by housing and energy leaders

Market-leading data capabilities with frequent, granular insight.
ISO9001, ISO14001 and ISO27001 certified.
Trusted to deliver quality, reliability and secure data handling.
pioneers in smart energy since
devices delivered to UK homes
UK homes already reached

Frequently asked questions

Disaggregation breaks a home’s total energy consumption down into distinct, meaningful categories, revealing what energy is actually being used for rather than just how much is consumed. By separating usage by fuel type and by area of the home, it highlights a property’s most energy-hungry activities, so you can move beyond a single figure and see where the real opportunities lie.

For electricity, we break usage into categories including cooking, heating, entertainment, EV charging, hot water, lighting, refrigeration, washing, always-on devices and more. For gas, we cover cooking, heating and hot water. This category-level detail gives you a genuine picture of where energy goes, ready to inform research, planning and product decisions.

Our disaggregation is powered by advanced algorithms refined through three years of consumer feedback, applied to granular 30-minute smart meter data. This combination of real-world refinement and high-resolution input means you get a dependable, evidence-based breakdown you can confidently build decisions on.

Technologies like EVs and heat pumps distort traditional usage patterns, making whole-home figures misleading. Disaggregation isolates specific loads such as EV charging and electric heating, so you can see exactly how these technologies contribute to demand, rather than having their impact hidden within a single consumption total.

Yes. Disaggregation sits at the top of Chameleon’s data offering and can be combined with enhanced home profiling, including property type, occupancy and low carbon technology adoption. This lets you segment your analysis far more richly, understanding not just what energy is used for, but which kinds of homes are driving each pattern.

Behaviour-change programmes need specificity to be effective. A whole-home figure can’t tell a household or a provider where to focus, but a category breakdown pinpoints the biggest energy drivers, revealing clear, evidence-based opportunities for improvements and upgrades and helping interventions land where they matter most.

Speak to our team about smart energy technology