Client: A leading fashion retail company with multiple online and offline stores.
Challenge:
The company struggled to understand customer behavior due to a lack of structured data collection across various sales channels. Without clear insights into customer preferences, sales trends, and engagement patterns, their marketing strategies were ineffective, leading to reduced customer retention and low conversion rates.
Solution:
We implemented a comprehensive data collection strategy by integrating multiple data sources, including:
- Surveys & Feedback Forms: Collecting direct responses from customers about their shopping experience.
- Point-of-Sale (POS) Data: Gathering transactional data from both online and offline stores.
- Website & Social Media Tracking: Using analytics tools to track user engagement, product preferences, and purchase intent.
- Competitor Analysis via Web Scraping: Extracting pricing, trending products, and promotions from competitor websites.
Our team also automated data collection using APIs to pull real-time customer interactions and purchase histories.
Results:
- 30% improvement in customer engagement due to targeted marketing campaigns.
- 20% increase in sales through personalized recommendations based on customer purchase history.
- Better demand forecasting, reducing stock shortages and overstocking.
By leveraging structured data collection, the retailer optimized its marketing strategies, improved customer retention, and enhanced overall sales performance.