Product recomendations for online store

efb4c0_738fc99085154d71a750f380aee528bcOnce retailers know us, they know each customer’s needs. Once retailers know what the consumer wants, it results in better sales and customer loyalty. Basically, Softcube does three things: it collects customer behavior data, uses algorithms to analyze it and creates ways to get in touch with the customer.

Algorithms produce shopping recommendations for customer based on historical data. The goods meant to be valuable for customer can be send through number of channels, like recommendation block on site, personalized emails or push notifications. Recommendation blocks like “Frequently Bought Together” increase click-through rates, average order size, and total sales. Softcube generated offers contain items from an online store’s merchandise only. Product blocks display different items for each unique customer, and can be placed on the main page, product pages, category pages, and even on 404-pages and “Thank you” pages.

Product recommendations increase average order size by recommending products that are similar to what a customer has already viewed or added to their cart. Product recommendations are determined by using Self-Improving Big Data Algorithms. Softcube increases sales of online stores through this kind of personalization, which is based on the analysis of customer data. The strong advantages we have are reliable pricing, simple integration and real-time technology. Softcube is easy for businesses to use, though it is powered by an impressive methodology. Personalized product recommendation technology improves customer shopping experience, increases customer conversion rates and average order size, and boosts total sales by up to 20%.

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