Once retail knows us, it knows each customer’s needs. Once retail knows what consumer wants, it results in better sales and customer loyalty. Basically, Softcube is three things: customer behavior data, algorithms to analyze it and channels to get in touch with 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. Trigger emails with recommended items for an abandoned item, for example increase conversion from carts to orders, resulting in greater total sales. Softcube generated emails contain items from an online store’s merchandise only. Recommendation blocks inside emails display different items for each unique customer, and can be generated with different logic, trying to up-sell or cross-sell something.
Trigger emails increase total sales size by returning customers making them re-think purchasing. It is not simply a reminder, it is another chance to show customer something similar or complement to what he has already viewed or added to the cart. Recommendations for emails are determined by a self-improving big data learning with time. Softcube increases sales of online stores almost of any scale through customer data analysis and personalization based on it. Strong advantages we have are reliable pricing, simple integration and real-time technology. It is easy for business to use, though it is backed up by strong methodology. Personalized product recommendation technology improves customer shopping experience, increases conversions and boosts total sales by up to 20%.