The Predictive AI In Retail Market is being driven by Escalating Demand for Personalized Customer Experiences
The Predictive AI In Retail Market is expected to grow at a CAGR of 25.6% during 2024 and 2029. During this period, the market is also expected to show a growth of USD 8305.4 million. The retail industry is witnessing a significant shift towards the integration of generative AI for predictive analytics, revolutionizing the customer experience through hyper-personalization at an unprecedented scale. Predictive analytics has long been utilized for personalization, but the emergence of advanced generative models is leading to more dynamic, conversational, and individually tailored customer journeys. This trend is gaining traction in major retail markets, including North America, Europe, and APAC, as retailers strive to meet evolving consumer expectations for contextually aware and unique interactions. In North America, retail giants such as Walmart are spearheading this innovation. In January 2024, Walmart unveiled new generative AI-powered tools, including an enhanced search function that enables customers to search based on specific use cases, like football watch parties, and receive a tailored list of relevant products.
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The market is segmented based on
According to Technavio, There are several factors that are causing the market to flourish during the forecast period, which are as follows:
However, the market also witnesses some limitations, which are as follows:
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Market Scope |
|
Report Coverage |
Details |
Page number |
256 |
Base year |
2024 |
Historic period |
2019-2023 |
Forecast period |
2025-2029 |
Growth momentum & CAGR |
Accelerate at a CAGR of 25.6% |
Market growth 2025-2029 |
USD 8305.4 million |
Market structure |
fragmentation |
YoY growth 2024-2025(%) |
24.4 |
Key countries |
US, China, Germany, Japan, UK, Canada, France, India, South Korea, and Brazil |
Competitive landscape |
Leading Companies, Market Positioning of Companies, Competitive Strategies, and Industry Risks |
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In the retail sector, Predictive AI is revolutionizing business operations through various applications. AI-driven personalization enhances customer experience, while retail data integration ensures seamless information flow. Smart shelf technology and automated stock replenishment optimize inventory management. Predictive analytics helps in estimating customer lifetime value, promotional effectiveness, conversion rate optimization, shopping cart abandonment, customer churn prediction, and store traffic prediction. Staff scheduling optimization, data security protocols, and real-time analytics are other key areas of application. Model training data, algorithm accuracy metrics like precision and recall, F1-score, AUC-ROC curve, mean absolute error, data cleaning techniques, feature engineering, model validation techniques, cross-validation methods, hyperparameter tuning, model deployment strategies, API integration, and business process automation are essential components of building and implementing effective predictive AI models in retail.
In the dynamic retail industry, Predictive AI is revolutionizing business operations through machine learning models and deep learning algorithms. These advanced technologies enable demand forecasting models, optimizing inventory management, and personalizing customer experiences through natural language processing. The global application software market, a segment of the IT software industry, encompasses these Predictive AI solutions. Technavio's market analysis calculates the market size based on the collective revenue generated by companies specializing in Predictive AI application software.. Industries are leveraging the products belonging to the market for customer engagement, transactional notifications, and promotional offers.
Technavio Research
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