AI For Retail: Opportunities From Operations To Marketing

The retail landscape has undergone a seismic shift in recent years. Customer expectations have reached new heights - low prices, fast shipping, and exceptional service are now the norm. For retailers, merely meeting these table stakes is no longer enough to stay competitive or retain loyal customers when nearly any product is a click away.

AI and automation present compelling solutions to tackle these challenges while delivering highly personalized shopping experiences that were unimaginable just a few years ago. As AI capabilities rapidly advance, retailers have an unprecedented opportunity to harness its potential to transform their operations.

This article explores innovative AI solutions tailored for the retail industry's unique operational challenges and opportunities. We'll delve into AI use cases across the retail value chain - from intelligently engaging consumers to optimizing intricate behind-the-scenes processes.
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The State of Retail

The retail sector faces multifaceted pressures and issues from all directions:

1. Fleeting Loyalty - With endless choice online, customers can easily switch brands at the slightest friction.

2. Personalization Expectations - Customers expect individually tailored recommendations and shopping experiences, as seen on Netflix and Amazon.

3. Siloed Data - Disjointed data across channels makes it hard to optimize customer experiences.

4. Commoditization - Differentiation is challenging when customers can find anything easily for the best price.

5. The Amazon Effect - Customers expect near instant availability with free expedited shipping.

6. Labor Shortages - It's increasingly difficult to attract and retain talent, especially in customer-facing roles.

7. Low Employee Satisfaction - Dissatisfied employees directly impact customer experience and increase costs like training and attrition.

"By 2024, 30% of all retailers will be either out of business or will have shrunk significantly." Source: SupplyChain247

Many retailers are struggling to keep pace with these compounding challenges. However, the companies that successfully leverage AI to transform experiences will gain meaningful competitive advantages.
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The AI Opportunity

AI is pivotal in supporting retailers through this evolution by:

1. Personalization at Scale - Generate tailored recommendations and experiences for each customer

2. Lower Costs - Reduce repetitive tasks through automation

3. New Revenue - Enable innovative business models like conversational commerce

4. Deeper Insights - Synthesize data across channels for a unified view of customers

5. Improved Efficiency - Streamline operations like inventory and fulfilment

6. Enhanced Agility -Continuously adjust campaigns and processes using real-time data

What makes this moment so pivotal is the convergence of:

• Abundant Data from an explosion of digital touchpoints
• Advanced AI Models like large language models and deep reinforcement learning
• Rising Consumer Expectations for personalized, seamless shopping

Together, these factors present a timely opportunity to deploy AI-based solutions that meet the challenges of today while future-proofing retail operations.

Investing in AI

Current AI adoption remains relatively low across retail, but is picking up momentum quickly:

AI Investment Area                       2021               2022  

Customer Service                       25%              57%

Supply Chain                               13%              47%

Merchandising                             12%               31%

"By 2025, early AI adopters will increase profits by $300 billion, largely by expanding revenue opportunities." Source: Capgemini Research Institute

Let's explore some AI use cases to understand its potential.
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Conversational Commerce

Messaging has become the most popular communication channel for people worldwide. Customers increasingly expect to interact with businesses conversationally as well - whether asking questions, making purchases, or seeking support.

AI-powered chatbots enable conversational commerce at scale by interacting with customers conversationally using natural language.

Consider Sephora's chatbot that provides personalized skincare recommendations and virtually try-on makeup products. By integrating advanced computer vision and NLU capabilities, this bot delivers an engaging, interactive shopping experience unmatched by static product images.

Benefits

Conversational interfaces like Sephora's chatbot have fundamentally reshaped customer experiences across industries by:

• Providing 24/7 self-service support
• Offering personalized recommendations
• Lowering customer support costs by deflecting common inquiries

Forrester estimates that $112 billion of the $339 billion dollars spent on customer service and support in 2021 could have been avoided by deploying AI solutions.

Common Use Cases:

1. Intelligent Product Finders - Help customers easily find products using natural language

2. Account Management - Enable self-service account updates like changing passwords or payment details

3. Cart Recovery - Proactively reach out to customers who've abandoned carts with personalized incentives

E-commerce retailer ASOS introduced an AI-enabled chatbot that helps customers find products using conversational queries and natural language processing. This simplified product discovery increased order values by 32%.

Many retailers are still in the early stages of exploring conversational interfaces. As capabilities continue advancing, the opportunities for innovation are immense when combining AI with creative thinking.
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Generative AI for Commerce

Generative AI takes personalization to new heights by creating wholly original, customized content and recommendations for each shopper.

For example, imagine an AI shopping assistant that interacts conversationally to understand your style preferences and budget to design clothing items personalized just for you. This ultra-personalized experience boosts engagement, conversions, and loyalty.

B8ta, a retail-as-a-service innovator, partnered with AI startup Anywear to provide store associates with a visual merchandising tool powered by generative AI. Using conversational prompts, store associates can instantly generate 3D product renderings tailored to a customer's unique style and design sensibilities. This immersive digital experience helps customers visualize products in their own lifestyle context to inform purchasing decisions.

Expanding Applications

As generative AI capabilities rapidly mature, its creative applications will reshape commerce in innovative ways we are only beginning to envision - from generating marketing collateral tailored to micro-audiences to creating personalized product configurations.

Here are a few thought-provoking concepts:

• Custom Product Design: Enable customers to describe their ideal products like jewelry or clothing and have generative AI instantly create digital renderings
• AI-Written Advertisements: Generate product listings or ad copy personalized to different local customer demographics
• Lifelike Avatar Shopping Assistants: Provide an interactive shopping advisor with customized style recommendations

Harnessing generative AI for such cutting-edge applications requires retail leaders to adopt an experimental mindset focused on continuous learning. While still early, such inventive thinking creates space for groundbreaking innovations.

Intelligent Supply Chain

Behind the scenes, AI is optimizing intricate retail operations to enable efficient, flexible, and accurate fulfillment amid volatile demand.

Inventory management is one function ripe for an AI overhaul considering over $1 trillion dollars are tied up in excess apparel inventory that goes unsold by retailers globally each year. These bloated inventories create ripple effects across the retail value chain - from constrained cash flows to profit-eroding markdowns.

AI is transforming inventory planning and control by:

Demand Forecasting

• Incorporate external signals like weather, events, pricing elasticity beyond just historical sales
• Continuously recalibrate forecasts as new data emerges
• Account for uncertainties like product life cycles, quality issues, or supplier risks

Inventory Optimization

• Dynamically calibrate reorder points and buffer stock levels
• Align inventory policies to priorities whether service levels, working capital, or margin tradeoffs
• Generate store and SKU-level recommendations to match supply with local demand

For example, Tommy Hilfiger leverages AI to tailor its assortment and inventory for each store based on local customer demographics and data on best-selling items, sizes, and colors. This intelligent approach increased Tommy Hilfiger's inventory turns by 25%.

Besides inventory planning, AI is disrupting other supply chain functions:

Sourcing & Manufacturing

• Shorten product design cycles by autogenerating designs informed by sales data, trends, and customer preferences
• Optimize raw material orders using demand forecasts and inventory policies

Transportation & Fulfillment

• Dynamically route shipments based on real-time data like weather disruptions and traffic patterns
• Optimize warehouse operations using predictive analytics and simulations

Prescriptive Analytics

As supply chain challenges grow more complex, AI's capabilities will continue advancing from just predictive insights to prescriptive recommendations. By continually synthesizing more variables, prescriptive analytics guides optimal actions amid intricate, ever-changing conditions across global supply networks. This enables retailers to remain nimble despite volatile demand.

AI-Optimized Marketing

AI is taking retail marketing to new frontiers by synthesizing data from across channels to uncover growth opportunities and reach customers more meaningfully throughout their journey.

Customer Intelligence

Mosaic is an AI-powered customer intelligence platform used by leading retailers like Nike, Rolex, and Samsung. It aggregates billions of consumer data points across online and offline channels to reveal predictive insights around customer behaviors, motivations, and affinities.

These enriched customer profiles enable retailers to:

• Identify high-value yet under-served customer niches
• Optimize channel strategies to engage audiences when and where they’re receptive
• Strategically tailor product assortments and depth for local customer demographics

Ad Impact Optimization

Levi's leverages AI to optimize digital ad impact in real-time across objectives like traffic or conversions. The AI engine rapidly iterates creative variations while analyzing performance data to automatically shift budget towards better-performing combinations.

Over 6 months, Levi's grew site traffic 6X and conversion rates 2X using this algorithmic approach to ad impact optimization.

AI unlocks more strategic applications like:

• Campaign Performance

• Measure campaign impact across online and offline channels
• Continuously adjust messaging, offers, budgets, and channels
  
  

• Personalization

• Deliver personalized content and recommendations tailored to customer interests and purchase history
• Generate millions of creative variations to optimize engagement

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AI-Enhanced Operations

Further optimizing back-office retail operations with AI can yield additional cost savings while enabling business agility.

Process Mining

Process mining analyzes workflows using transactional data to model bottlenecks, waste, variants, and risks. This quantification guides effective process redesign.

For example, a leading apparel retailer used process mining to model returns workflows. The analysis revealed that over 60% of returned goods were cleared for restocking. By streamlining inspection steps without compromising policy adherence, they achieved savings of $3 million.

Task Automation

AI automation handles high-volume, repetitive tasks:

• Accounts Payable

• Extract invoice metadata using OCR and NLP
• Validate invoice accuracy against POs
• Generate GL coding based on vendor rules
  
  

• Cycle Counting

• Optimize cycle counting schedules using demand statistical models
• Trigger cycle counts based on business rules
• Analyze performance metrics to optimize counting efficiency

• Anomaly Detection
  Cross-channel anomaly detection uncovers inventory shrinkage, quality issues, or financial reporting discrepancies faster. By processing billions of multi-structured data points with pattern recognition, issues can be detected earlier and with greater accuracy.

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Getting Started with AI

Transitioning to an AI-enabled retail enterprise may feel overwhelming initially. However, retailers can embark on their AI journey in prioritized steps:

1. Assess Opportunities

• Identify primary friction points impacting customers, employees, and operations
• Audit workflows and data landscape
• Solidify organizational goals

2. Start with a Targeted Pilot

• Given the complexity, the narrow initial scope
• Prioritize tangible pain points aligned to goals with clear ROI
• Leverage configurable no-code AI solutions

3. Continuously Expand

• Use agile sprints to launch and test incremental enhancements
• Monitor effectiveness through defined metrics and KPI dashboards
• Maintain focus on end-user impact with continuous user feedback

4. Build Internal Capabilities

• Develop in-house AI talent through training programs
• Foster an experimentation culture focused on learning
• Institute responsible for AI reviews and parameters for new models

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To sum up,

The retailers that will thrive amid the challenges ahead are the ones that continue to reinvent themselves. AI provides fertile ground for this reinvention by elevating customer experiences, optimizing operations, and future-proofing business models. Leaders who take decisive action now to unlock its possibilities will gain durable competitive advantages.

Explore Alltius to pace up with the AI transformation in retail. We at Alltius enhance the engagement of customers, improve operational efficiencies, and equip your business model for sustained competitiveness. Act now to gain a competitive edge in the cut-throat business environment.

Request a demo now!

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