If you're after more heavy-duty reporting than provided by the console's in-built heatmap and charting functions, or if data feeds are required to power in-house dashboards or otherwise enrich data records, you have a number of options.
First head over to Analytics>Data Tables.
Data tables are downloadable CSV files in a structured format that enable the processed data* to be exported from our platform. Every region is included - you can always add/amend regions if a particular area doesn't have one - before self-servicing a fresh set of downloads, specifying the time range you want.
Data tables have been designed to import into BI tools, whether that's Excel or Sheets, more specialist analysis tools like Power BI or Tableau, or your own data pipeline.
There are two types of data tables:
24-hour or full period data tables contain data in the following format:
region name, region type, deviceCount, averageDwell
Event data tables contain data in the following format:
event name, region type, deviceCount, averageDwell
Second, on request, we can supply a visit file output which enables the data to be mapped to other data sets (e.g. demographics or other declared data from app user registration data). The inclusion of the appinstallID enables this mapping to be undertaken. The visit file has the following format:
deviceId, gripId, regionName, visitStartTime, visitEndTime
Third, we provide APIs for real-time data access. Head over to the APIs section of this knowledge base for more details on these.
* Handling raw location data is time-consuming. So we transform it into visit metrics. By processed data we mean visits and dwells. We take the raw data (namely deviceID, timestamp, xy or lat/lng and convert this into something useable - i.e. processed data.