Retail Next Extractor Documentation

Integration Overview

Retail Next provides information on visitors to your brick & mortar stores so that you can understand foot traffic and in-store conversion.

The Daasity<>Retail Next integration provides data on the flow of customers in and out of retail locations. Data is reported at an hourly level.

Key Topics

Integration Availability

This integration is available on

  • Pro

ERD

Endpoints

 

Locations API https://<susbcription>.api.retailnext.net/v1/location
Datamine API (Traffic) https://<subscription>.api.retailnext.net/v1/datamine  

Locations

JSON Element 

Database Column 

id 

location_id 

name 

name 

type 

type 

parent_id 

parent_id 

timezone 

timezone 

store_id 

store_id 

address.street_address 

address 

comp_start_date 

start_date 


Incremental data extraction.

Business Rule 

Value 

Load type 

TRUNCATE & REPLACE 

Extraction Frequency 

Daily 


Sync Key definition:
 

MD5 Hash of the following fields:

  • location_id 
  • __source_id 

Traffic Table

JSON Element 

Database Column 

MD5(location_id ||’:’||start_date ||’:’||hour_begin) 

traffic_id 

locations (location_id being passed in the API request) 

location_id 

date_ranges.first_day (first day being passed in the API request) 

start_date 

date_ranges.last_day (last day being passed in the API request) 

end_date 

data.group.start 

hour_begin 

data.group.finish 

hour_end 

data.value 

traffic 


Incremental data extraction.

Business Rule 

Value 

Load type 

Upsert 

Extraction Frequency 

Daily 

API Example 

{"locations": ["location_id"], "metrics": ["traffic_in"], "date_ranges": [{"first_day": "2020-01-15", "last_day": "2020-01-15"}], "time_ranges": [{"type": "store_hours"}], "group_bys": [ {"group": "time", "value": 1, "unit": "hours"} ]} 


Sync Key definition:
 

MD5 Hash of the following fields:

  • traffic_id 
  • __source_id 

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