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      Integration: RetailNext

      This article will help you learn about how Daasity replicates data from RetailNext, limitations to the data we can extract and where the data is stored in the RetailNext schema.

      Key Topics

      Click on the links below to take you to the section where you can learn more about this Integration

      Integration Overview

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

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

      Integration Availability

      This integration is available for:

      • Pro V2

      NOTE: You are considered V2 if...

      • Your account says Pro V2 in the Daasity App

      Not sure? Reach out to Support@Daasity.com

      API Endpoints

      The Daasity RetailNext extractor is built based on this RetailNext API documentation.  The following endpoints are used by Daasity to replicate data from RetailNext:

      Entity Relationship Diagram (ERD)

      The embedded diagram houses the ERD for the Daasity RetailNext integration illustrating the different tables and keys to join across tables. Hover over the embedded diagram to reveal controls to zoom and scroll.

      RetailNext Schema

      The Daasity RetailNext extractor creates these tables using the endpoints and replication methods listed. The data is mapped from source API endpoint to the table based on the mapping logic outlined in each table.

      Locations

      • Endpoint: Location
      • Update Method: TRUNCSERT
      • Table Name: retailnext.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
      source_id __source_id
      MD5(id + source_id) __sync_key
      Daasity: timestamp when loaded into DB __synced_at

      Traffic

      • Endpoint: Datamine
      • Update Method: UPSERT
      • Table Name: retailnext.traffic
      JSON Element Database Column
      MD5(location_id + start_date + traffic_in::group::start) traffic_id
      location_id location_id
      date_ranges::first_day start_date
      date_ranges::last_day end_date
      traffic_in::group::start hour_begin
      traffic_in::group::finish hour_end
      traffic_in::value traffic_in
      traffic_out::value traffic_out
      source_id __source_id
      MD5(location_id + start_date + traffic_in::group::start + source_id) __sync_key
      Daasity: timestamp when loaded into DB __synced_at

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