As offline shop owner I want gather some data about popular goods and places where my customers are standing more then N secs, also I can build prediction how many persons are standing at venue each time. Each viewed product will be marked as suggested if my customer is leaving shop without any buyings.
As customer I will be glad to get some discount without begging - just for the fact I'm a permanent buyer here.
What it does
We collect depersonalized (until customer approves it to get extra discount) information about indoor location.
How we built it
With iBeacons from estimote, the ecommercetools API, an php backend and leaflet.js for the map.
Challenges we ran into
We chose one technology, but after some research we understand that we cannot get what we want in certain amount of time. So we decided to switch to fallback technology stack just 24 hours before hackathon ends. The iBeacon data is jumping all over the place.
Accomplishments that we're proud of
Fixing the jumping iBeacon data, tracking data in realtime and visualizing it on a map.
What we learned
a lot how to handle iBeacon data and mapping.
What's next for Watchr
Inject BI into collected data.