About the Client
The client is a leading American luxury fashion brand, manufacturing clothing, fragrance, and fashion accessories. Apart from selling through concessions in third-party stores, the company has several business units and franchisees spread all over the globe.
The Business Challenge
Retail companies today face several long-term challenges that must be addressed skillfully to avoid adverse outcomes. As IT technologies have matured, tremendous investments have been made by retailers to solve both the tactical and strategic problems surrounding business operations. But it’s crucial to note that without the basic skills and analytics tools one cannot get to the root of the challenge and analyze factors impacting growth.
The client- a leading luxury retailer was looking at analyzing the needs of their customers to design more personalized and relevant promotions and marketing campaigns by incorporating real-world, behavioral insights. Additionally, the retailer identified that its localized store assortments were key drivers of incremental foot traffic and sales. But, the huge volumes of unstructured customer, product, and transaction data sets that were generated from various channels proved to be a major challenge due to which each business unit was pushed to work in silos to address their priorities. Also, its crucial to note that owing to the siloed business structure, the campaigns often resulted in low redemption rates and failed to drive adequated foot traffic to their retail outlets.
The client needed to deploy a full suite of retail analytics services to skillfully address the challenges and drive positive business outcomes. Considering the fragmented nature of the retail landscape, the client found it difficult to determine where to start and which retail analytics services to leverage to drive better outcomes. This is when they chose to collaborate with Quantzig and leverage its retail analytics services to analyze the impact of their promotional campaigns and gain insights into customer preferences at a more granular level.
The challenges faced by the luxury retail brand included:
- Complex and unstructured customer data sets
- Uneven and inconsistent data in multiple formats
- No standard approach to data normalization
- Lack of effective territory alignment
Out of the millions of players in the American retail industry, a small fraction of them have been successful in turning data to insights. Are you included? If not, get in touch with our analytics experts and learn how we can help you get there through our customized retail analytics services.
Solutions Offered and Value Delivered
Quantzig’s dedicated ‘Analytics Centre of Excellence’ with a team of 20+ data scientists, domain experts, and attribution modelling experts designed an innovative three-pronged approach to tackle the challenges faced by the retailer. The retail analytics services leverage sophisticated mathematical models and AI-driven algorithmic decision making to analyze customer data and build personalized campaigns.
To help the client gain a 360-degree customer view, we adopted a comprehensive three-pronged approach.
The first phase of this engagement revolved around leveraging our retail analytics services that use dynamic machine-learning algorithms to understand purchase patterns by different stores and customer types to drive localized product assortment.
The retail analytics services offered in the second phase of this engagement focused on analyzing the redemption patterns to refine the targeting criteria and drive campaign effectiveness.
The retail analytics services offered in the final phase of the engagement revolved around the use of statistical techniques and data visualization to help the client identify and prioritize the drivers of incremental sales.
The retail analytics services offered also empowered the client to simulate various scenarios and gauge incremental sales by performing a deep dive analysis of customer data sets. The use of regression techniques also empowered them to extract key information and insights from existing datasets.