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Harness the same recommendations technology that drives the unrivaled success of YouTube and Google. Powerful deep-learning algorithms, coupled with Qubit's data-rich customer context that drive dramatic improvements in KPIs.
Qubit feeds Google's algorithms with enriched real-time customer data. Our behavioral data is clean and well structured, enabling Google's AI to go to work.
Customers shop in shorter 'spikier' patterns, meaning businesses have a small window of time to show the relevance of their product catalog.
Predicting the next product in the sequence uses huge scale pattern recognition technology based on every single product and customer data point.
Products in your catalog spike in purchases for a number of reasons. Sometimes these reasons are short-lived, such as a sale period.
Our recommendations use the context of the purchase to inform the algorithms. Data points such as price changes, time of day, and customer segment inform the deep learning algorithm to ensure it makes the best choices for your business.
Let Google's AI crunch Qubit's real-time customer data and predict what every customer wants next. Add the human touch to the machine with Qubit's merchandising interface.
Google has mastered the art of understanding the relevance of something in relation to someone's context. Brand new viral videos on YouTube are a great example of this.
The same technology can unearth the relevance of new products in your catalog. Our recommendations will test these products, as soon as they are introduced, to understand where they fit into certain buyer journeys.
New products and customers are introduced into the experience using deep attribute matching. Every aspect of the product data is used to find similarities with other products, such as words in the description, fabric, and color.
Similar or shared customer attributes are used to create initial "look-a-like" models until more data is gathered from their browsing.