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