Retail Next Extractor Info

Integration Overview

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

The Daasity<>Retail Next integration provides data on customers moving throughout a retail location to provide information on user flow in and out of retail locations. Data is reported at an hourly level.

ERD

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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 

 

Copyright Daasity, Inc 2020

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