Give a helping hand to your customers 
			Get ahead of their buying needs using the business intelligence solutions available from SARE
			
		 
					
					
				
					Recommendation systems 
					SARE’s recommendation models use machine learning technologies, which allows us to continuously improve and enhance recommendations, and provide more valuable product and service suggestions. In addition, our solutions can use data from a variety of sources, such as online behavior, purchase histories and surveys, to provide even more insight into customer needs and preferences. 
 
				
			 
					
				
					Co-occurrence analysis 
					This is a concept in which customers who buy two products choose them more often as a set than buying each separately. This means that there is a strong purchase relationship between them. 
For example, if customers buy coffee and milk together, the recommendation system may suggest to customers that they should also buy sugar. 
Applying the data collected in the co-occurrence analysis to the recommendation mechanisms will not only provide accurate recommendations, but, more importantly, influence the increase of the value of the shopping cart through the well-known upselling strategy. 
 
				
			 
						
			Ponadto: 
			
								
					  
					
												Marketing attribution model 
												allowing you to check the effectiveness of your marketing activities 
					
				 
								
					  
					
												CDP & owned media database management 
												for the best possible experience between your brand and your customer 
					
				 
								
					  
					
												Complete implementation of marketing automation 
												and conducting communications in an omnichannel model