AI-driven personalization in retail is important to build deeper and more meaningful relationships. Therefore, by utilizing AI technologies, retailers can make data-driven decisions and amplify customer needs in the market. In this blog post, we will explore how AI is transforming personalization in retail operations.
>> Explore our previous blog post: Top 8 Attractive Use Cases of AI in the Retail Industry
1. What is AI-driven personalization in retail?
Artificial intelligence (AI) in retail refers to the application of AI technologies to optimize and enhance various factors of the retail industry. These technologies are revolutionizing, enabling us to improve inventory management, forecast demand and sales performance analysis to personalize customer experience. Therefore, by analyzing customer data, such as purchase history, browsing habits, and demographics, retailers can create personalized recommendations, targeted marketing campaigns, and customized promotions that resonate with each customer.
2. How are retailers using AI to personalize customer experience?
AI-driven personalization provides an opportunity to connect with customers differently. For example, AI chatbot assistants have been impacting the customer experience when 40% of customers prefer chatbot and customer support agents. As well as AI also allows shopping assistants to customize customer services that meet the desires of their customers. There are five essential stages for successfully implementing AI-powered personalization with key examples.
2.1 Data management and security
Through natural language processing capabilities and machine learning algorithms, retailers can collect more information based on the process of data management and security. They can conduct customer feedback, product reviews and social media posts to identify customer insights to enhance their shopping experience. Moreover. qualitative data, like sentiment analysis and market trends, can be combined with customer profiles to build a rounded view of their preferences and behaviors. Some ways to do with AI-powered technologies consist of:
- Aggregate structured and unstructured data from multiple sources (including website, social media…)
- Identify ideal customer persona based on their preferences, behaviors, usages
- Do the dynamic segments in real-time as new customers
Example: A large fashion retailer wants to use AI to generate personalized customer recommendations to ensure all customer data is well-organized and secure. Security measures are essential: encrypting sensitive data and establishing clear access guidelines. With that, it helps AI deliver to correct customers.
2.2 Personalize marketing and customer interactions
Customers are looking forward to brands that recognize and consider them as unique individuals. New Epsilon research indicates that 80% of consumers can make a purchase when brands offer personalized experiences. To start personalizing customer interactions using AI, retailers can:
- Lauch AI-driven marketing campaigns tailored to individual customers
- Generate personalized emails, SMS and notifications based on customer product searches, purchasing behaviors or frequent purchases
- Send promotion messages frequently to engage more customers
- Deliver personalized recommendations, answer customer queries, and guide shoppers with AI-powered chatbots and virtual assistants.
Example: A coffee shop introduces AI in its inventory management and the process to identify the customer behavior and purchase easily. This helps the supermarket manage stock levels better and avoid shortages and enhance customer satisfaction in general.
2.3 Dynamic pricing and targeted recommendations
Among customers, 78% of consumers want tangible, money-saving benefits from personalization. A higher percentage mentions that special discounts significantly influence consumer buying behavior by creating urgency, increasing perceived value, and altering purchasing decisions. With the support of AI to target recommendations, retailers can use predictive analytics to anticipate future customer needs, such as what they are likely to buy next or when they might want to repurchase certain items. Moreover, retailers can adjust prices and promotions based on their customer behavior and competitors. To follow implementing a dynamic pricing strategy, it requires going through five steps: define your goals; gather and analyze data; choose your pricing model; set pricing rules and automation as well as monitor and optimize.
Example: FCC has been at the forefront of helping clients in growing their business by leveraging AI/ML capabilities. From that, it can implement a dynamic pricing strategy for our clients in the rapidly growing fashion accessories category.
2.4 Continuously enhance the customer experience
According to Capterra, nearly 70% of customers expect to check out online in four minutes or less. To help, AI can predict and automatically populate shipping and payment details for returning users, including those checking out as guests, to streamline and accelerate the checkout experience. Besides, retailers can continuously offer augmented and virtual reality tools like smart mirrors and interactive displays to deliver unique, exciting, and immersive experiences.
Example 1: IKEA has developed The Place App, which allows shoppers to use AR with their smartphone camera to put furniture. Thus, they can visualize how they look like in their setting.
Example 2: Nike uses AR and VR in their physical stores to experience the different steps in Nike’s supply chain to see how products are being made.
2.5 Continue testing and measuring performance
By integrating AI into retail operations, retailers can effectively assess customer engagement and conversion rates. AI enables them to analyze the effectiveness of personalization efforts and gain insights into customer preferences. AI is used for performance testing in 5 fields: speed, accuracy, cost efficiency, stability and continuous improvement. This data-driven approach allows retailers to refine their campaigns for better performance and improved outcomes.
3. Conclusion
By utilizing AI across different touchpoints of the customer journey, retailers can deliver convenient and engaging shopping experiences tailored to each individual consumer. Want to know how you can improve your operations with the help of AI? Contact us expert consulting team for more information!