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Is AI and Predictive Analytics Transforming Retail Decision Making?

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Artificial Intelligence

Thanks to the COVID-19 pandemic, 2020 was a year in which consumers learned to do many things in a contactless manner and shopping was no exception. Retail industry has had the most crucial decision-making months during the pandemic, especially on their ability to predict the future. 2020 has definitely made retailers expect the unexpected.

Retailers today are facing lots of concerns. These include how to increase sales, improve sell-through and profitability. Certain forward-thinking retailers are beginning to understand that from here on, no year will be like the one before. And as a result, to answer those questions, retailers are adopting technology to their advantage.

2020 has demonstrated that fashion retail cannot build its forecasting models on historical data alone, and unpredictability is set to become the new normal. Digitization can help, but how?

Let’s understand that without AI, retailers might have tons of data, but how would they use and interpret the data to forecast demand? If they don’t understand this demand, how can they create a personalized and localized offering? How would they provide a great in-store experience with the wrong or unavailable stock?

That is where AI comes in. By integrating AI and Predictive Analytics, retailers can solve some of the immediate challenges they face and can be benefited in various ways. Some of the benefits include –

Smoother Supply Chain

The pandemic has created a significant hurdle in seamless management of retail supply chains.  Disruption in supply chain results in lost revenue and dissatisfied customers. Inefficient inventory management is a weak spot for many retailers which AI can resolve to a large extent. The entire supply chain, including stock, logistics, staffing, and distribution, can now be managed in real-time with AI. This helps brands to predict and understand demand fluctuations and trends.

Define Ideal Quantities and Reduce Leftovers

AI will assist retailers to buy the apt quantity of new products by anticipating local demand. Immediate, long-term forecasts at SKU-level ensure that their buying decisions are 80% data and 20% intuition and not the other way around.

First Allocation & Replenishment

Retailers can now allocate the right amount of initial units, at SKU level, across all stores and locations. With predictive analytics, the demand is anticipated at each location and the retailer can avoid overstocking while keeping more units available in the warehouse for planned distribution later.

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Also Read: How Data Science is transforming Retail Business
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Improve Personalization to Drive Sales

AI is critical in helping to deliver a personalized and seamless customer experience. It provides retailers with the intelligence they need to understand customer’s shopping habits and preferences. This enables retailers to align their offerings with customer expectations. With AI, brands now have the power to offer personalized shopping experience to their customers.

Conclusion

AI provides the flexibility that retailers need to meet changing demands and deliver operational efficiencies. By evaluating consumer data with AI, retailers can provide unmatched services to their customers and address operational difficulties with ease.

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