AI, Personalization, and Omnichannel Strategies in Marketplaces (2025): How to Build Better Customer Experiences

In 2025, customer experience is the key competitive advantage in e-commerce marketplaces. With millions of sellers on Amazon, Shopee, Lazada, eBay, and Etsy, businesses can no longer compete on price alone. Instead, they must deliver personalized, seamless, and consistent shopping experiences powered by artificial intelligence (AI) and omnichannel strategies.

According to Statista (2024), global e-commerce retail sales are expected to surpass $5.7 trillion in 2025. With more customers shopping online than ever, sellers who adapt to personalization and omnichannel approaches will capture the greatest share of this growth.

Why AI and Personalization Are Essential in 2025

Shoppers now expect sellers to understand their needs. Deloitte (2024) found that 80% of consumers are more likely to buy from brands that offer personalized experiences.

AI allows sellers to analyze buyer behavior and create customized recommendations, dynamic pricing, and targeted promotions. For example, McKinsey & Company (2023) reports that 35% of Amazon’s revenue comes directly from its AI-powered recommendation engine.

Personalization improves:

• Relevance – showing shoppers the right products at the right time.
  
• Engagement – keeping customers browsing longer.
  
• Conversions – increasing purchase likelihood.
  

1. AI-Powered Product Recommendations

Recommendation engines are among the most effective AI applications in marketplaces.

Benefits:

• Suggest products based on browsing and purchase history.
  
• Increase sales through cross-selling and upselling.
  
• Boost conversions by making product discovery easier.
  

Top tools:

• Algolia – AI-powered search and recommendations.
  
• Dynamic Yield – delivers personalized experiences across web and mobile.
  

McKinsey & Company (2023) shows that AI-driven personalization can increase revenue by 10–15%.

2. Personalized Marketing in Marketplaces

Personalization extends beyond recommendations. Sellers can use AI to personalize:

• Email campaigns with custom product suggestions.
  
• Discount offers tailored to browsing behavior.
  
• Dynamic retargeting ads to bring shoppers back to abandoned carts.
  

Forrester (2024) confirms that companies using personalized marketing achieve stronger customer acquisition and retention rates.

3. Omnichannel Consistency

Modern shoppers use multiple channels before buying. Deloitte (2024) found that 70% of customers expect consistent experiences across online and offline channels.

Best practices:

• Keep product information consistent across all platforms.
  
• Use centralized customer data to track behavior.
  
• Ensure brand voice and visuals remain the same everywhere.
  

Tools like Shopify Plus and Salesforce Commerce Cloud make omnichannel selling easier by integrating data from marketplaces, websites, and physical stores.

4. AI in Customer Service

AI-powered chatbots and virtual assistants are now standard in customer service. They handle routine queries quickly, improving satisfaction and freeing humans for complex issues.

Benefits of AI support:

• 24/7 availability for instant answers.
  
• Reduced response times improve buyer trust.
  
• Collect customer insights for future improvements.
  

Gartner (2024) predicts that AI will manage 70% of all e-commerce customer service interactions by 2025. Tools like Zendesk and Gorgias already provide AI-driven customer support.

5. AI-Driven Inventory and Pricing Optimization

AI also improves backend operations by forecasting demand and adjusting prices dynamically.

Advantages:

• Predicts demand to prevent stockouts.
  
• Suggests optimal prices based on competitors and market conditions.
  
• Balances profitability with competitiveness.
  

Tools like Feedvisor use AI to automate pricing and inventory optimization.

6. Data Analytics for Customer Experience

Data drives personalization and omnichannel success. Sellers can analyze customer journeys to improve every touchpoint.

Forrester (2024) reports that data-driven companies are 23 times more likely to acquire customers.

Key metrics include:

• Conversion rate (CR).
  
• Customer lifetime value (CLV).
  
• Net promoter score (NPS).
  
• Cart abandonment rate.
  

Analytics tools such as Google Analytics 4 and Tableau help visualize this data for better decision-making.

7. Case Studies: Amazon and Shopee

• Amazon uses AI-powered personalization in recommendations, search rankings, and pricing. Its recommendation system alone accounts for 35% of its sales revenue (McKinsey & Company, 2023).
  
• Shopee applies localized personalization and omnichannel promotions, tailoring offers to regional markets, which helps it dominate e-commerce in Southeast Asia.
  

Best Practices for Implementing AI and Omnichannel Strategies

1. Start small: Begin with product recommendations before scaling into other areas.
   
2. Unify data: Use CRM systems to centralize customer insights.
   
3. Protect privacy: Ensure compliance with GDPR and other data regulations.
   
4. Measure and optimize: Continuously test personalization campaigns for improvement.
   

As Mr. Phalla Plang, Digital Marketing Specialist, explains:

“AI and omnichannel strategies are no longer optional—they are essential. Sellers that deliver consistent, personalized experiences will earn customer trust and loyalty in the long term.”

References

Algolia. (2024). AI-powered product discovery solutions. https://www.algolia.com

Deloitte. (2024). Personalized commerce and omnichannel experience study. Deloitte Insights. https://www2.deloitte.com

Forrester. (2024). The power of data-driven personalization. Forrester Research. https://go.forrester.com

Gartner. (2024). AI trends in customer service for 2025. https://www.gartner.com

McKinsey & Company. (2023). Personalization and AI in e-commerce. https://www.mckinsey.com

Statista. (2024). Retail e-commerce sales worldwide from 2014 to 2027. https://www.statista.com