The Business Challenge
The customers today are savvier, well-informed, and wield more purchasing power than ever before. Factors such as these have prompted retailers to improve customer experience by addressing key issues that suppress their ability to drive customer experiences across touchpoints. In such a scenario, retailers poised to stand out from the pack are those that can predict and analyze customer behavior and purchase patterns. From that viewpoint, it’s quite evident that retailers who leverage advanced retail analytics solutions are poised to gain an edge over the competing brands in their ability to use data to improve customer experiences.
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With data being generated from diverse sources in the retail sector, businesses have started realizing the potential of retail analytics and its role in enhancing predictive capabilities to deliver better retail customer experiences. Similarly, owing to the data deluge the client faced challenges around customer experience management and several other long-term challenges that needed to be addressed to ensure process compliance and drive customer satisfaction. For the client, adopting a retail analytics-based approach to address issues around customer experience seemed quite challenging as they were unsure of where to start and which solutions to consider. This is when they approached Quantzig to leverage its retail analytics expertise and drive customer experience.
The challenges faced by the client included:
- Lack of on-demand access to reports
- High licensing and infrastructure costs associated with data visualization for quick decision making
- Ineffective aggregation and processing of data from disparate sources such as marketing campaigns, mobile, and other customer touchpoints
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Solution Offered and Value Delivered
To help the client tackle their challenges, we adopted a two-phased approach that focused on generating real-time insights from large customer data sets. In the first phase, our retail analytics team adopted a comprehensive approach consisting of market surveys to build a retail data categorization model to analyze the overall business ecosystem. The use of detailed retail analytics survey reports and recommendations helped analyze the true potential of retail analytics.
The devised retail data categorization model also offered recommendations on different spend levels and their ROI. The big win for the retailer, however, was reflected in their ability to enhance customer experience by automating key business functions. Moreover, the ability to improve data management and create a recurring data aggregation, analysis, and decision-making process empowered them to improve customer experience by a whopping 33%.
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What is Retail Analytics?