Forbes has laid out four ways artificial intelligence (AI) can be leveraged to improve retail basics. “The days of reactionary responses, such as raising or slashing prices on consumer goods to break even or move excess inventory for long-term success, are gone. Retailers must work in new, better ways, as the economy—along with shoppers and trends—will always change,” suggested the Forbes Technology Council post. “The trick is effectively planning for change, uncertainties and unknowns—and being positioned to thrive regardless of shifting tides. Technology—specifically artificial intelligence (AI)—can help retailers focus on four retail basics constant to success.”
Weather-driven demand analytics enable retailers to utilize AI/ML (machine learning) capabilities to gain visibility and plan for some of those “changes, uncertainties and unknowns” by quantifying how the most important day-to-day external driver of sales volatility – the weather.
Here are the core retail basics that benefit from the use of AI, according to the Forbes article:
- Cultivating Stellar Customer Service
“Consider the best ways you can enhance your customer experience and explore how AI can bring those enhancements to life. From answering basic questions to routing advanced inquiries to generating workers’ schedules and tasks to forecasting demand, AI can help you elevate your customer service.”
- Detecting And Preventing Fraud
“Harness the power of AI to catch—or even prevent—losses early, correct them and prevent future losses by adding predictive and prescriptive analytics to your existing technology platform.”
- Optimizing Inventory Management
“Using AI demand planning and machine learning, retailers can better manage inventory, even staying ahead of its curves. Demand intelligence drives inventory decisions by anticipating demand, planning accordingly, and executing to meet those demands. For example, retailers and consumer packaged goods (CPG) companies enabled with demand forecasting solutions have the ability to analyze the relevant ‘who, what, where, when, and why’ variables at a granular level, down to the weather or world events.”
- Powering Personalization
“Machine learning algorithms analyze customer data, including shopping behavior, browsing and purchase history—even social media interactions—and use those insights to help retailers personalize service down to an individual level. Most retailers offer some level of personalization ranging from messaging and product recommendations to rewards, discounts and incentives that will likely resonate with individual customers.”
Planalytics’ predictive weather-driven demand metrics can help in three of the above-mentioned areas: Cultivating Stellar Customer Service, Optimizing Inventory Management, and Powering Personalization.