Written By: Gargi Sarma In the quickly changing retail environment, customer loyalty may now be gained, and sales can be increased through customisation. The emergence of artificial intelligence (AI), specifically generative artificial intelligence (Gen AI), has enabled merchants to provide highly customized promotions and pricing to suit the distinct tastes and habits of worldwide customers. With an emphasis on pricing and promotional tactics, this article examines how AI-powered customization is revolutionizing retail and identifies merchants who are setting the bar high.
Figure 1: What are the MOST EFFECTIVE AI-Powered Applications Used in a Hyper-Personalization Strategy?
The following are some important statistics:
Personalized Recommendations
Sales can rise by up to 15% when personalized recommendations are made (McKinsey).
Personalized experiences increase a customer's likelihood of purchasing by 80% (Accenture).
Transaction rates from personalized email marketing might increase by up to six times (Aberdeen Group).
Retail AI Adoption:
According to Gartner, more than 80% of merchants are putting money into AI technology.
By 2025, the market for AI-powered personalization is projected to grow to $31 billion (Markets & Markets).
Customer Preferences:
According to Salesforce, 71% of customers believe that businesses will be aware of their requirements and expectations.
61% of customers find impersonal shopping encounters frustrating (Epsilon).
Figure 2: Ways in Which Companies Measure the Success of Using AI-Driven Personalization Worldwide 2023
AI's Potential for Personalization:
The way merchants see and interact with their consumers has been completely transformed by AI. Artificial intelligence (AI) algorithms are able to build tailored experiences by analyzing large quantities of data, including past purchases, real-time interactions, and user behavior. Retailers can now provide highly tailored pricing and promotions thanks to Gen AI, which goes one step further by using current data to generate new content and solutions.
Personalizing Pricing
Customized pricing refers to modifying product prices according to specific customer characteristics. Customers can be divided into groups by AI algorithms according to their susceptibility to price fluctuations, preferences, and purchase patterns. Retailers are able to provide customized rates that optimize sales and profitability because of this segmentation.
Example: Personalized pricing was first introduced by Amazon. Amazon may provide customized discounts and dynamic pricing that change based on individual buying preferences by evaluating customer data. To promote first-time purchases, new consumers may be provided introductory rates, while repeat buyers of a certain product may receive targeted discounts.
Personalized Promotions
Promos are an effective strategy for drawing in and keeping clients. By customizing promotions to each customer's tastes and behavior, AI can increase their efficacy. Customized marketing messages, tailored discounts, and tailored offers are just a few examples of the several ways that personalized promotions may be created.
Example: Starbucks uses artificial intelligence (AI) to offer customized promotions via its mobile app. Starbucks is able to provide customized offers and rewards because the app keeps track of client purchases and preferences. For instance, a customer who frequently purchases caramel lattes may be given a discount on their preferred beverage or presented with a new offering that better suits their palate.
Dynamic Pricing and Promotions:
Beyond only suggesting products, AI-powered customization also includes dynamic pricing and incentives. Retailers can improve prices and promotions in real-time by using AI algorithms to monitor market trends, rival pricing, and individual customer behavior.
Example: Through the analysis of market data and consumer behavior, RapidPricer, a leading AI-powered pricing tool, assists businesses in optimizing their price strategies. Retailers may provide customized discounts and promotions that appeal to certain customers by using dynamic pricing, which will eventually increase sales and improve customer satisfaction.
Figure 3: Feelings about AI are Mixed in Every Country, but Places with Greater Excitement May Offer Near-Term Opportunities
Using AI to Improve Customer Service:
To provide individualized help, chatbots and virtual assistants are essential components of AI-powered customization in customer service. These artificial intelligence (AI) powered solutions can evaluate consumer enquiries and offer customised answers, improving the entire customer experience.
Example: Global apparel retailer H&M helps clients with their purchasing requirements by utilizing chatbots driven by artificial intelligence. Through the examination of consumer inquiries and past purchases, the chatbots offer tailored product suggestions and styling guidance. This lessens the workload for human customer care representatives while also increasing customer happiness.
Figure 4: Commercial Leaders Are Already Leveraging Gen AI Use Cases (Source: McKinsey & Company)
The Role of Gen AI:
By generating new content and solutions from preexisting data, generative AI elevates customization to a new level of sophistication. Within the retail industry, Gen AI may provide tailored marketing messages, suggest products based on the preferences of particular customers, and even devise novel pricing schemes.
Example: Gen AI is used by online personal style business Stitch Fix to provide tailored outfit suggestions. Through the analysis of consumer comments and preferences, Gen AI produces personalized style recommendations and personalizes the purchasing experience for every user. Stitch Fix has increased revenue and cultivated a devoted client base because to its individualized strategy.
The Future of AI-Powered Personalization:
The possibility of hyper-personalization in retail looks even more enticing as AI technology develops. In an unparalleled level of personalisation, picture a future in which every part of a consumer's experience is customized to suit their own interests and habits.
Combining Various Data Streams
AI's capacity to analyze enormous volumes of varied data and produce useful insights is what gives it its power. Retailers may provide data to AI systems from a variety of sources, including:
POS Data: Purchase trends, product preferences, and transaction histories.
Competitive Data: Includes competitor's price plans, advertising campaigns, and market trends.
Health metrics: Activity levels, heart rate, and steps are tracked by fitness trackers and wearable technology.
Behavioral Data: Details on how consumers interact with digital material, navigate online retailers, and explore.
Voice Recognition: Interpreting tone and speech patterns to determine emotion and mood.
The Journey of Personalization
AI-driven customization may eventually get to the point where using it is nearly identical to having a personal assistant who is more aware of your wants than you are. Imagine a situation in which an AI program continuously observes your actions and modifies your surroundings as necessary:
Health & Wellness: If the AI notices any indications of stress, it may recommend a relaxing activity or place an order for a calming drink, such as green tea.
Diet & Nutrition: The AI may suggest meals or automatically modify your grocery shopping list based on your dietary choices and health indicators.
Shopping Preferences: Based on your individual preferences and purchasing patterns, the AI may provide a customized shopping experience that includes product and promotion recommendations.
Driving & Commuting: The AI may provide recommendations for the best routes, point out possible risks, and even change the settings of your car to make for a more comfortable ride by examining your driving habits.
Ethical Considerations:
Despite the enormous promise for AI-powered personalization, it's critical to address the moral issues related to permission and data protection. Customers need to be in charge of their data and be able to consent to receive these kinds of tailored experiences. By protecting consumer data, retailers and IT companies can foster confidence and guarantee openness.
Conclusion:
Realizing the full potential of AI-powered customisation is what retail will look like in the future. Retailers may increase consumer pleasure, foster loyalty, and increase sales by combining several data sources and developing hyper-personalized experiences. A new era of customer involvement is being ushered in by the seemingly endless possibilities that arise from the advancement of AI technology in retail.
Read more on Pricing Innovation: Digitalization of Pricing and the Development of Dynamic Competition
About RapidPricer
RapidPricer helps automate pricing and promotions for retailers. The company has capabilities in retail pricing, artificial intelligence, and deep learning to compute merchandising actions for real-time execution in a retail environment.
Contact info:
Website: https://www.rapidpricer.com/
Email: info@rapidpricer.nl
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