Analytics & retail analytics
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This document discusses analytics and retail analytics. It defines analytics as discovering patterns in data through statistics, programming, and research. Retail analytics specifically aims to improve customer loyalty and sales. It does this by identifying valuable customers, understanding their preferences, and creating personalized shopping experiences through offers targeted to individual needs. Retailers can gather customer data through in-store and online analytics to gain insights that optimize performance.
Analytics & retail analytics
- 1. Analytics & Retail Analytics Analytics of Market with Retail Analytics
- 2. What is Analytics? Analytics is the discovery and communication of meaningful patterns in data. Especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance.
- 3. Analytics often favors data visualization to communicate insight. Firms may commonly apply analytics to business data, to describe, predict, and improve business performance.
- 4. Specifically, arenas within analytics include Enterprise decision management Retail analytics Store assortment and stock optimization Marketing optimization and mix analytics Web analytics Sales force sizing and optimization Price and promotion modeling Predictive science
- 5. Retail Analytics In these times of economic uncertainty and decreasing margins, retailers must improve their approach to driving traffic and sales. With increased mobility and always- connected capabilities, shoppers today can easily research competitive offerings, even while standing in a store aisle, such as marketing attribution and overall marketing effectiveness.
- 6. The Importance of Retail Analytics Identify and target the most valuable customers. Analytics can help retailers understand customers’ social behavior and provide valuable insights on what is important to them. For retailers like Walmart, Target and others that depend on increased spending among existing customers to boost sales, loyalty is a particularly important goal.
- 7. Turning Data Insights into Revenue By leveraging analytics tools and models, retailers can boost customer loyalty by creating a personalized shopping experience that customizes offers to needs.
- 8. Analytics in Customer Loyalty Analytics tools can help retailers connect with customers at every stage of the lifecycle by turning these patterns into valuable insights that describe, predict and improve business performance. To collect all this data, retailers use two methods: In-store analytics and Online analytics.
- 9. In-store analytics: This is one area where physical monitoring of customers can reveal valuable information. Online analytics: This is used to collect and analyze online customer information. Commonly used tools are social media monitoring tools, mobile device usage and Web searches.
- 10. Summary The importance of Retail Analytics is well established, and successful retailers are continuously looking to invest in analytics to attract new customers and retain their customer base. It is imperative for retailers to delve deeper into customer data and utilize different analytics tools.
- 11. Thank You