See a Month’s Worth of Crime in Seconds

‘Data’ is a word that gets used very casually these days. It seems every technology company is collecting data, using data or mining data—and for good reason.

With good data, you’re able to achieve incredible insights that otherwise wouldn’t be possible. It allows you to see deeper into your company, product and community, and enables you to make informed decisions, measure success and reflect on mistakes.

At Auror, data and our community are the cornerstones of what makes the platform powerful, and for me personally, compelling to analyze. My role at Auror crosses over between Customer Success and data analysis, helping us find new ways to help our customers using the wealth of crime data available through the platform so they can better prevent crime.

Having the opportunity to dive into crime data is both a thrill and a challenge. It’s real-world sleuthing, with a modern data science twist. Because when we do dive into the data in Auror, we can discover some interesting insights.

The ultimate goal is to be able to provide real-time visualisations that empower our community to prevent and solve more crime. That’s what I’m perhaps most excited about working on. As our community grows, data become more accurate, allowing for greater potential in the intelligence we can deliver.

The beauty of Auror is that it becomes a more powerful tool with each new user that joins our community, as more data is captured, the product becomes smarter, and so more people want to use it and so on. The result is that as we grow we’ll be able to share even better insights with time.

This is how I’d demonstrate this data network effect and the value our community are seeing in different geographies.

Accurate and perceptive trend prediction, patterns and prevention measures are all possibilities, and will become more focused as time goes on and out platform becomes even smarter. Our ultimate goal is to empower our community through knowledge, and I’m looking forward to what the future has in store!

In an attempt to demonstrate this I’ve created visualisations below looking at incident data across New Zealand and Melbourne, Victoria, using a combination of incident and geolocation data captured in Auror. Each dot appearing in the animation represents a site in Auror that’s uploaded at least one incident, with the size and colour representing the value of goods stolen. Grey dots represent thefts of less than $1,000, while yellow represent more significant theft incidents. And this is just the tip of the iceberg.

Over the coming months I’ll be developing and sharing more data visualisations and insights from the data on our platform, so stay tuned for more!

Are there any insights you want to see from Lucas? Let us know and we’ll put him to work!

Retail crime in NZ, Oct. 2017
‍‍Retail crime in Melbourne, Oct. 2017