smrtr Data Universe

We believe the true picture only emerges from connecting several different views within a single data universe.

Privacy Compliant Insights at Scale

We combine genuine transactional data from industry partners with demographic, life stage, attitudinal and socio-economic variables. We use AI and traditional analytics to predict which consumer segments are more likely to demonstrate your desired behaviour.

  • 16 million Australian adult consumers
  • 5 million automotive purchase transactions
  • 8 million residential properties with information on their location, size and value
  • 19 million mobile devices
  • 1.2 million + POIs

How we do it

How we do it infographic
How we do it (data sets)

We collect a wide range of data on people, consumption, and behaviour across key industries.

How we do it (analytics)

We leverage data assets to create business intelligence products that can be used for analysis and marketing.

How we do it (Identity graph)

Our matching techniques enables us to connect the data.

How we do it (platforms)

and already-built connections into technology to drive seamless communication strategies and execution.

Our data assets

Real Estate Transactions & Values

We’ve connected CoreLogic data on over 8 million Australian residential properties including listing activity, values, tenure & property characteristics.

Example: We worked with a large residential property developer to help them target and filter the segments of the population that will be in-market to buy a new-build property.

Automotive Transactions

We collect purchasing data from over 50% of car dealers in Australia, containing 5 million vehicle purchases over the last five years, and covering make, type and price.

Example: We worked with a European luxury car brand to help launch a new model by identifying sub-segments of the car market and targeting them through digital advertising.

Device Behaviour

We collect anonymised data from several different providers of mobile data covering 11 million MAIDs with 50 billion location pings per year. This provides multiple views of the apps people use, their online brand engagement and the places they go.

Example: We helped a government department understand the needs, behaviour and interests of different groups of people in their jurisdiction.


Demographics include age, gender, income, household structure, length of tenure, tenure type and net worth.

Example: We worked with a major Australian cultural institution to help them understand their core customer base and then diversify into different ages and ethnicities.

Relevant content

Got Questions?

We have all the answers! Well, maybe not all but we’ll do our best to help.