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4 Ways To Leverage Generative AI & Analytics for Retail Success

Jun 27, 2024 12:43:33 PM

4 Ways Advanced Analytics Can Provide a Competitive Edge in the New Digital Era

In light of the current economic landscape, the "where" and "how" of global consumer spending have significantly shifted.

Recent earnings reports from large retail companies show an increase in consumers’ essential spending for items like fresh/organic food, frozen food, and beverages, pick up/delivery of restaurant foods, cleaning products, preventive healthcare, and vitamins while showing a decrease in discretionary spending as in travel, home furnishings, or luxury goods.

Consumer spending has also widely shifted from stores to online, accelerating the need for traditional retailers and digital natives to increase their investments in digital and advanced analytics to compete effectively.

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Conversely, as evidenced by some recent retail store closings and bankruptcy filings, not leveraging digital and advanced analytics effectively, could potentially place a retailer’s revenue and business model at risk.

Here are four ways advanced analytics can help:

1. Build Automated and More Accurate Demand Forecasting Models

Given the variations and fluctuations in consumer demand in part due to the economic recession, it has become even more imperative for retailers to build more accurate and reliable forecasts for consumer demand and inventory. They must continually measure and improve the accuracy of their automated demand forecasting models to help boost revenue and margins.

2. Optimize Inventory, Store Layout, and Operations

Retailers must revisit their store operations, the safety of their customers and employees, and the transparency of their supply chains. Advanced in-store analytics can track real-time sales, while customer in-store heat maps can help optimize store layouts and customer movement patterns to optimize store layouts, predict inventory needs in real-time and create more efficient store operations. 

3. Provide Real-time Notifications, Recommendations, and Personalized In-store Contactless Experience

Retailers must move beyond the traditional tenets of loyalty and personalization to provide an integrated and immersive omnichannel customer experience. By incorporating GenerativeAI and ML models, retailers can better understand customer behavior and personalize the customer journey across all channels, creating a seamless omnichannel experience.

4. Provide Optimal Media Mix and Maximize Sales

Leading retailers can leverage advanced techniques like Bayesian Models, Markov Chain, and Monte Carlo. These methods help determine optimal spending levels, profitability per medium, and the effects of the economic environment and competition, ultimately maximizing sales.

Advanced analytics could provide the necessary competitive edge and sustainable revenue growth to thrive in the new digital era.

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How Nisum Can Help

If you want to accelerate your data transformation at scale and leverage advanced analytics to make smart real-time decisions based on fact-based intelligence, then contact us. Traditional retailers and digital natives alike have found that Nisum provides them a competitive edge through innovative approaches to advanced analytics initiatives. Clients leverage Nisum to make their diverse data sources ready for advanced analytics and to help them build an AI-ready organization.

Ravi Narayanan

Ravi Narayanan

Ravi Narayanan is the Global Practice Head of Insights and Analytics at Nisum and a preferred advisor to leading Fortune 500 brands. He serves CxOs and their teams, helping them harness Advanced Analytics and blockchain technologies to help transform customer experience, improve operations, and drive growth and innovation.

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4 Ways To Leverage Generative AI & Analytics for Retail Success

Jun 27, 2024 12:43:33 PM

4 Ways Advanced Analytics Can Provide a Competitive Edge in the New Digital Era

In light of the current economic landscape, the "where" and "how" of global consumer spending have significantly shifted.

Recent earnings reports from large retail companies show an increase in consumers’ essential spending for items like fresh/organic food, frozen food, and beverages, pick up/delivery of restaurant foods, cleaning products, preventive healthcare, and vitamins while showing a decrease in discretionary spending as in travel, home furnishings, or luxury goods.

Consumer spending has also widely shifted from stores to online, accelerating the need for traditional retailers and digital natives to increase their investments in digital and advanced analytics to compete effectively.

New call-to-action

Conversely, as evidenced by some recent retail store closings and bankruptcy filings, not leveraging digital and advanced analytics effectively, could potentially place a retailer’s revenue and business model at risk.

Here are four ways advanced analytics can help:

1. Build Automated and More Accurate Demand Forecasting Models

Given the variations and fluctuations in consumer demand in part due to the economic recession, it has become even more imperative for retailers to build more accurate and reliable forecasts for consumer demand and inventory. They must continually measure and improve the accuracy of their automated demand forecasting models to help boost revenue and margins.

2. Optimize Inventory, Store Layout, and Operations

Retailers must revisit their store operations, the safety of their customers and employees, and the transparency of their supply chains. Advanced in-store analytics can track real-time sales, while customer in-store heat maps can help optimize store layouts and customer movement patterns to optimize store layouts, predict inventory needs in real-time and create more efficient store operations. 

3. Provide Real-time Notifications, Recommendations, and Personalized In-store Contactless Experience

Retailers must move beyond the traditional tenets of loyalty and personalization to provide an integrated and immersive omnichannel customer experience. By incorporating GenerativeAI and ML models, retailers can better understand customer behavior and personalize the customer journey across all channels, creating a seamless omnichannel experience.

4. Provide Optimal Media Mix and Maximize Sales

Leading retailers can leverage advanced techniques like Bayesian Models, Markov Chain, and Monte Carlo. These methods help determine optimal spending levels, profitability per medium, and the effects of the economic environment and competition, ultimately maximizing sales.

Advanced analytics could provide the necessary competitive edge and sustainable revenue growth to thrive in the new digital era.

Artificial Intelligence Playbook CTA featuring a robot waving.

How Nisum Can Help

If you want to accelerate your data transformation at scale and leverage advanced analytics to make smart real-time decisions based on fact-based intelligence, then contact us. Traditional retailers and digital natives alike have found that Nisum provides them a competitive edge through innovative approaches to advanced analytics initiatives. Clients leverage Nisum to make their diverse data sources ready for advanced analytics and to help them build an AI-ready organization.

Ravi Narayanan

Ravi Narayanan

Ravi Narayanan is the Global Practice Head of Insights and Analytics at Nisum and a preferred advisor to leading Fortune 500 brands. He serves CxOs and their teams, helping them harness Advanced Analytics and blockchain technologies to help transform customer experience, improve operations, and drive growth and innovation.

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