Retail data analytics is the act of gathering and analyzing retail data (such as sales, inventory, pricing, and so on) in order to identify trends, forecast outcomes, and make better business decisions. When done correctly, data analytics enables retailers to get faster and greater insights into the performance of their stores, products, customers, and vendors –thus making better business increase profitability. Source:
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Data Analytics Services[list=][/list]Descriptive Analytics – the most common one: helps retailers organize their data to tell a story and uses it to describe “what” is happening in their business.
[list=][/list]Diagnostic Analytics – the simplest form of “advanced” analytics: It enables retailers to use data to answer the “why” of specific business concerns.
[list=][/list]Predictive Analytics – the second most advanced type: It forecasts the future using findings from both descriptive and diagnostic analytics.
[list=][/list]Prescriptive Analytics – the most advanced type: it gives retailers good recommendations to do.
Future of Retail Analytics (Top 10 Trends) 1. Create more hyper-personalized experiences for a one-to-one market.
2. Spending and demand can be predicted.
3. Develop automated, dynamic pricing models.
4. Build new experience within the store thanks to the retail analytics trends
5. Selling online is non-negotiable
6. Omnichannel tools are creating more meaningful shopping experiences
7. Automated technology is helping retailers get a handle on the labor shortage
8. Voice search
9. Extensive reality
10. Machine learning
