Programmers.ai Improves Performance and Marketing Strategies for Fashion Design Company with Dynamic API Integration/ ETL Processes

About the Client

This successful fashion design company creates apparel and accessories for women and children in 23 locations, independently owned shops, and major department stores, such as Belk, Lord and Taylor, Nordstrom, Saks Fifth Avenue, and Neiman Marcus. The client designs and creates a unique, signature collection of dresses, tops, lounge & active ware, shoes, and jewelry that reflects the sunny, bright colors and floral prints of the west coast.

  • Industry: Retail and Consumer Goods
  • Headquartered: West Coast of the United States
  • Platforms: Microsoft Azure, Microsoft Azure, RESTful APIs
  • Team Size: 6-8 professionals
the_client
 

The Challenge

The client essentially had a two-part problem they needed solved. The first challenge involved bringing real-time data from cloud applications into a data warehouse to better understand company performance and the effectiveness of their marketing strategies.

A second challenge was to determine how to extract the data from APIs that had no built-in API connection. For this we needed to develop dynamic customized APIs.

 

Our Solution

Programmers.ai started by solving their data/API integration and process automation, outlined in the following modules:

The Solution

API Customization

Since there was not built-in API profiling available, we started with understanding how Facebook, Google Ads 360, and Google DV 360 APIs could be analysed to work for the client. We analysed how we can have a smaller number of API hits to get the most out of the data in real time. We created our own API connection as a plugin to our ELT Process.

The Solution

Parsing Semi-Structure Data And Loading It Into The DWH

We built the process to parse the semi-structure data to multiple level nodes. Parsed data will get loaded to different layers inside the DWH with different load strategies in a single pipeline framework. We set up the process between each data transaction to audit and handle up to 50% failure rates without manual intervention and to notify the responsible person through various modes.

Technologies Used

Our software architects and engineers are experts in using the latest technologies.

  • Matillion
    Matillion
  • Snowflake
    Snowflake
  • Postman
    Postman
  • Looker
    Looker
  • Meta Console API
    Meta Console API
  • Python
    Python
  • cURL
    cURL
  • SQL
    SQL
 

Business Impact

As it helped the in-house team optimize and simplify testing processes.

Here’s how we did it

  • business impacts

    Centralized Cloud-Based Data Warehouse

    Created a shared cloud-based warehouse (DWH) using data from multiple social media platforms and search engines that anyone in the company could access.

  • business impacts

    Targeted Insights for Marketing and Sales

    Could focus on specific demographics and other necessary information for marketing campaigns and sales reports using multiple targeted searches in the data warehouse.

  • business impacts

    Driving Sales Through Data Insights

    Increased sales over 33% due, in part, to the ability to identify interest for specific fashion designs through targeted searches of the DWH and tracking website link clicks using the dynamic API integration and ELT processes.

we-did-it

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Over the past year I have worked with them, they have worked very hard to understand our highly customized system and troubleshoot things with little or no documentation while managing to keep the business up and running normally. Without the hard work and dedication they have shown, I know we would have had some issues causing downtime or lost production. I am looking forward to continuing working them in the next year as well.

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