Outlier delivers high-value personalized data journalism via text message. We use the following framework to make sure our journalism is meeting information needs and increasing accountability. It also keeps us responsive to our news consumers.
Identify the biggest information gaps: We use aggregate data like United Way 211 data, federal complaint data or city complaint data to see where the biggest information gaps and accountability gaps are. In response to this data our first project addresses information gaps around housing.
Use traditional reporting to find where better information could lead directly to more accountability: Outliers news consumers can use our information to hold landlords and public officials accountable directly. This allows Outlier to concentrate our enterprise reporting on more complicated or more entrenched housing issues.
Compile specific, high value and personalized information using basic data journalism methods: We built a database from some public data, some scraped data we bought and some FOIA data. Our users access the database using their address.
Serve the broadest range of news consumers possible: All our information is delivered over SMS to reach people quickly and easily. We buy cell phone numbers targeted by zip code and text directly.
Engage through information: We don’t rely on brand loyalty because we believe high value information can speak for itself. We keep our feedback loop tight and adjust our information based on needs we see in user responses.