How we helped Retail Client Unlock Customer Activity Matching and Segment Mapping


Summary

  • Client: We recently engaged with a leading player in the retail and apparel industry, that has a thriving workforce of 2500 talented employees. Their cutting-edge fashion expertise and unparalleled presence redefine the industry, captivating fashion enthusiasts nationwide.
  • Challenges: The client grappled with the daunting task of reconciling web data, CRM data, and customer segment mapping data throughout their customer transactions. This lack of synchronization posed a significant obstacle in their quest to deliver a flawlessly cohesive customer experience, necessitating an improved solution to ensure accurate matching of customer activities.
  • Solutions: Quantzig provided the client with a solution that involved building probabilistic fingerprinting models to accurately identify customer IDs based on device and transactional parameters. This enabled the mapping of customer transactions across multiple devices, resulting in improved customer segmentation and accurate tracking of customer behavior. Unleashing the dynamic duo of AWS SageMaker and Python, our client experienced a customer fingerprinting revolution, transforming data into tailor-made experiences, that set new industry standards.

Impact Delivered

All of the above initiatives resulted in:

  • 50% improvement in customer activity matching
  • Hidden customer segment mapping unveiled
  • Seamless customer mapping, no login required
  • Precision in identifying customer segments
  • Customer behavior patterns unleashed

About the Client

  • Our recent client was a prominent player in the retail and apparel industry in the United States. With a thriving business operation and a robust workforce of 2500 talented employees, they are redefining the fashion landscape. Their commitment to delivering exceptional products and a seamless shopping experience has earned them a loyal customer base.
  • With a wide range of trendy collections and a keen eye for the latest fashion trends, they cater to diverse tastes and preferences. As they continue to make waves in the making market, this client remains at the forefront of the fashion world, inspiring individuals to express their unique style and make a lasting impact on the industry.

Challenges

  • The client grappled with significant challenges in reconciling web data, CRM data, and customer segment mapping data across their customer transactions. The lack of synchronization among these crucial data sources posed a considerable obstacle to achieving a seamless customer experience. Existing approaches proved inadequate, failing to deliver reliable matching of customer activities. The fragmented data landscape created frustration and hindered the clients ability to gain comprehensive insights into their customers. They yearned for a robust solution to bridge the gaps and ensure a frictionless customer experience.
  • Without a cohesive solution, the client struggled to personalize interactions, offer targeted recommendations, and effectively engage with their customer base. The complexity of harmonizing these disparate data sets compounded the challenge, requiring a robust and holistic approach to ensure accurate and consistent customer activity matching. It became evident that a more advanced solution was imperative to overcome these hurdles and unlock the full potential of their consumer data.

Solutions

  • Quantzigs cutting-edge solution harnessed probabilistic fingerprinting models to unlock customer insights like never before. By seamlessly combining device and transactional parameters, we unveiled the probable customer ID and empowered accurate cross-device mapping of customer transactions. Our innovative approach revolutionized customer segmentation, enabling them to uncover hidden patterns across multiple devices.
  • The probabilistic fingerprinting models enabled the client to identify customers with a high degree of certainty. By considering device and transactional parameters, the models could match transactions to specific customers, reducing ambiguity and improving data accuracy. Besides, our models facilitated the mapping of customer transactions across multiple devices. This feature was particularly valuable in todays multi-device environment, where customers interact with businesses through various platforms. The client could gain insights into customer journeys and preferences across devices, leading to enhanced personalization and targeted marketing strategies. Our solution provided them with reliable customer segment mapping. By combining the probabilistic fingerprinting models with segmentation techniques, they could categorize customers based on their behaviors, preferences, and demographics. This allowed for more effective customer targeting and tailored marketing campaigns.
  • Our team ensured that the solutions provided were accurate by conducting rigorous validation and testing processes. The probabilistic fingerprinting models were fine-tuned and calibrated using historical customer data to optimize their accuracy. We also employed techniques such as cross-validation and performance evaluation to measure and validate the accuracy of the customer ID and segment mapping.
  • Our implementation of AWS SageMaker combined with Python revolutionized the retail organization, empowering their business with customer fingerprinting capabilities. By leveraging SageMakers advanced machine learning algorithms and Pythons versatile programming language, the client was able to create eye-catching personalized experiences for their customers. Through sophisticated data analysis and pattern recognition, these technologies enabled the retailer to understand customers on a deep level, identifying their preferences, and shopping habits, and even predicting future purchases. With this knowledge, they tailored their offerings, promotions, and recommendations to create captivating and memorable shopping experiences. The synergy between AWS SageMaker and Python transformed the retail and apparel industry, driving customer engagement, and loyalty, and ultimately boosting sales.
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