A system may use search refinements to identify new product trends. These product trends may be associated with attributes or product features that may previously have been available, but are newly of interest to a users. The system may compare search refinements used by users during an earlier time period with search refinements used during a more recent time period to identify search refinements that are used more often during the later time period. Based on this comparison, the system can identify a product feature that is of interest to users during the later time period, but not the earlier time period. The system can then recommend products with the product feature to potential customers. Further, if the product feature was not available during the earlier time period, the system can identify to potential customers that the product feature is newly available in relation to the earlier time period.
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