Target personalized campaigns with current session behavior. Recommendations are one of the key aspects of personalization — they give customers a far more relevant browsing experience, and give marketers greater visibility for associated products or services.
Built over the unified customer stack, Plumb5 features a unique recommendation widget which can recommend products to the browsing visitor, based on both individual and global parameters. This allows the marketer to recommend either based on the context of the current session, or based on past data.
Recommendations can be set based on individual attributes of the browsing visitor.
Recommend products to the browsing visitor based on a particular user segment or for a particular score-range.
Recommend products based on user profile data.
Recommend products based on past behavior or interactions of a particular user group.
Recommend a product based on a particular product category or a particular product strategy.
Recommendations can be automated using overall data to apply association rules to arrive at recommendations.
Based on page pattern — assign scores to data parameters and generate customer scorecards, then create customer segments across all data parameters.
Based on purchase pattern. Data used includes all sessions where the selected product is purchased, and recommends either purchased or browsed products.
Based on what other customers within the same segment bought. Fine-tune recommendations across similar parameters to optimize click-throughs for cross-selling.
By default, Plumb5 recommendations are set to "People who viewed the product also viewed," since this can be generated directly from web analytics data. To enable recommendations based on purchases, integrate your e-commerce data — and to recommend by customer type, tag it to a customer segment you've created.
See real-time recommendations configured against your own catalog and traffic.