Google AI Eases Online Shopping: How Machine Learning is Transforming the Retail Industry
The Importance of Personalized Shopping Experiences
With online retail sales rapidly increasing, it is becoming more important than ever for retailers to provide personalized shopping experiences for their customers. In order to stand out in a crowded market, positive interactions can make all the difference between a sale and an abandoned shopping cart.
Case Study: How Kinguin.net Improved User Experience
Kinguin.net is one of the leading global marketplaces for digital products, servicing over 10 million registered users and conducting over 500,000 new transactions each month. Despite these impressive numbers, the brand recognized the need to improve user experience in order to stand out in a competitive retail landscape.
Challenges of Product Recommendations
In the pursuit of personalized shopping experiences, Kinguin.net recognized that product recommendations were key. However, there were several challenges that needed to be addressed:
- Customer behavior
- Omnichannel context
- Product data challenges
Partnering with Google to Overcome Challenges
While Kinguin.net had the data necessary to provide personalized product recommendations, they lacked the machine learning model expertise. They opted to apply for the Google Recommendations AI beta program, becoming the first European gaming e-commerce platform to do so. By leveraging Recommendations AI, Kinguin.net was able to overcome the challenges of personalized product recommendations and improve user experience.
Understanding the Shopping Graph
Google’s Shopping Graph is a machine learning-powered, real-time database of the world’s products and sellers. The Shopping Graph processes billions of global product listings and stores specific information about those products, including availability, reviews, materials, colors, and sizes. It uses machine learning to understand relevant, nuanced characteristics and provide users with the most accurate search results.
Google Cloud Services for Retailers
Google Cloud is working with retailers to accelerate digital and omnichannel revenue growth, become more customer-centric and data-driven, and provide solutions that drive operational improvement.
The Retail Acceleration Program
The Retail Acceleration Program (RAP) is a services offering that helps retailers optimize their website, build a unified view of customer data, and drive increased foot traffic. Google Cloud also offers Customer Reliability Engineering, a white-glove service that helps retailers plan and execute flawlessly during peak shopping seasons.
Google Cloud Search for Retail
Google Cloud Search for Retail is a tool currently being piloted by Google that provides retailers with high-quality product search results for their websites and mobile applications. Powered by Google Search infrastructure and cloud AI technologies, Google Cloud Search for Retail gives retailers the ability to surface the right products to the right customers.
Google Recommendations AI
Google Recommendations AI is an AI service that uses algorithms to deliver highly personalized product suggestions based on customer preferences. Recommendations AI uses deep learning models that iterate in real-time, delivering personalized product recommendations to cold-start users and for long-tail products.
Conclusion
As the retail industry continues to become more competitive, providing personalized shopping experiences is crucial for retailers to stand out and maintain customer loyalty. By leveraging machine learning and AI-powered services like Google Recommendations AI, retailers can overcome the challenges of personalized product recommendations and provide users with more intuitive product discovery. Additionally, Google Cloud’s Retail Acceleration Program and other services can help retailers drive digital and omnichannel revenue growth and provide solutions to improve operational efficiency.
FAQs
What is Recommendations AI?
Recommendations AI is an AI service that uses deep learning models to deliver highly personalized product recommendations based on customer preferences. Recommendations AI can help retailers overcome the challenges of personalized product recommendations and improve user experience.
What is the Shopping Graph?
The Shopping Graph is Google’s machine learning-powered, real-time database of the world’s products and sellers. It processes billions of global product listings, stores information about those products, and uses machine learning to provide users with the most accurate search results.
What is the Retail Acceleration Program?
The Retail Acceleration Program (RAP) is a services offering from Google Cloud that helps retailers optimize their website, build a unified view of customer data, and drive increased foot traffic. Through RAP and other services, Google Cloud helps retailers drive digital and omnichannel revenue growth and provides solutions to improve operational efficiency.
What is Google Cloud Search for Retail?
Google Cloud Search for Retail is a tool currently being piloted by Google that provides retailers with high-quality product search results for their websites and mobile applications. Powered by Google Search infrastructure and cloud AI technologies, Google Cloud Search for Retail gives retailers the ability to surface the right products to the right customers.
What is Customer Reliability Engineering?
Customer Reliability Engineering is a white-glove service from Google Cloud that helps retailers plan and execute flawlessly during peak shopping seasons. Through Customer Reliability Engineering and other services, Google Cloud helps retailers drive digital and omnichannel revenue growth and provides solutions to improve operational efficiency.