Google has just released Recommendations AI, which is now available in public beta. This tool essentially allows brands to deliver personalised product recommendations to their customers using sophisticated AI-driven technologies.
As consumer expectations become increasingly more demanding, brands are forced to keep up or fall behind. With the vast amount of options readily available to shoppers, giving a personalised experience really cements brand commitment and loyalty.
Google uses the newest Artificial Intelligence architectures to pinpoint the preferences of each individual user to create a more bespoke and tailor-made experience.
The users of this platform will be able to choose a model type and optimization objective so they can track their specific results.
What do product recommendations do?
- Product recommendations can drive clickthrough rate, conversions, revenue, and also increase the total revenue per visit to the site.
- Product recommendations use machine learning to identify trends in consumer behaviour, specific attributes, and use situational context to provide shoppers with the best possible tailor-made experiences.
Why might Google’s Recommendations AI rival existing models?
- Recommendations are built to scale and extremely customisable/personalised
- They use market algorithms that already have access to a huge volume of data
- Recommendations are distinct and are delivered real-time
- Customisable and adaptable to any situation
- Metrics provided from US data promote positive results
Customers become impatient and want to find what they are looking for immediately. AI product recommendations can also leverage the buying intent of customers and sway them towards a greater order value.