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Case Study

Revolutionizing fashion by cutting time to market in half and boosting customer retention by 30%

Client Background

An online, membership-based fashion retailer with a portfolio of five direct-to-consumer brands specializing in shoes, handbags, jewelry, lingerie, activewear, and denim.

Client Need

  • Lack of high available data warehouse solution.
  • Implement data visualizations for predictive analysis based on past trends.
  • Gain a deeper understanding of customer purchase patterns and measure the effectiveness of campaigns and referrals on customer enrollment.
  • Leverage social media platforms (Facebook, Snapchat, Instagram, TikTok) to attract new customers through targeted advertising.

Our Solution

  • Migrated the data warehouse from SQL Server to Snowflake, a cloudbased
    solution.
  • Transformed the source data to create data warehouse tables, providing valuable insights into sales trends, customer behavior, topselling products, and promo usage details.
  • Utilized Tableau as the analytics platform, offering a user-friendly interface for interactive and dynamic dashboards, empowering the client to visualize data, identify patterns and trends, and make datadriven decisions.
  • Created dashboards for customer enrollment and sales analysis, evaluating the effectiveness of different mediums and campaigns (email, SMS, and push notifications), and analyzing the impact of promos and referral processes on sales.
  • Utilized Python for API integrations, enabling seamless communication between applications and providing insights into social media metrics and engagement.

Tools & Technologies

Snowflake,SQL,python,+ableau,Airflow,SSRS

Key Benefits

  • 50% time and 25% cost savings through optimized resource usage.
  • Increased processing capacity by over 100x, enabling efficient handling of larger data volumes and complex processing tasks.
  • In-depth insight into key trends in customer behavior, preferences, and purchase patterns, enabling targeted marketing, product development, and customer engagement, leading to 15% increase in revenue and 30% increase in customer retention.
  • Automation of real-time data tasks, ensuring up-to-date information for informed decision-making.
Case Study KeyPoints

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