A/B testing - how to measure the effectiveness of recommendations in your store?
We offer both visual and behavioural based recommendations. You get to decide which one best suits your needs, or you can opt for a hybrid.
Qanuk can behave like an in-store retail assistant, guiding customers with useful recommendations for visually similar products that align with your users' styles. In mere milliseconds you can improve user engagement and delight your customers with visually relevant products.
You can opt to enhance your customers’ experience by analysing their interaction with your site. Choosing this by option allows us to create behavioural patterns and recommend suitable products based on the clients’ actual interests.
Introducing changes in online stores can bring increased conversions, but come at the risk of causing frustration and cart abandonment. We can help you use A/B testing to test the waters and make evidence based changes that will be beneficial to business, without relying on intuition. We will help you conduct these tests and interpret the results.
Machine learning and image/text analysis can make repetitive tasks like product management and personalization of offers a lot faster. Optimize your business expenses by automating tedious tasks so that your team can spend more time on creative problem solving and innovating.
Create an account on the console, configure your store and products.
We download your product list and start receiving events from the store.
Visual-based and behavioural models are trained.
When new products are added, ML models are updated.
You can check the results in the user-friendly console dashboard.
Learn more about behavioral and visual recommendations