Recommenders provide list of products personalized to the individual. PureClarity has over 30 types of recommendation strategies. The majority of the recommendations are driven by PureClarity’s artificial intelligence algorithms. Recommenders can appear in BMZs on screen and within email campaigns.
To define a recommender select ‘Recommender’ from the Content Type drop down. You will then see the Recommender container. If no recommender has been define PureClarity will default to using the ‘AI Default Recommender’. The example below shows the default settings for the recommender for the BMZ HP-02 on the ‘Homepage’ within the personalized campaign for First Time Visitor.
As you can see from the example above PureClarity is initially configured to be hands off. The system will decide which types of recommenders to show to different people and the recommendations within the types will be highly personalized.
You can override the default AI recommenders and show any of the recommenders available. So you can configure what you like for the Default Campaign, standard campaigns or sales events. To do this click on the ‘Override’ radio button. You will then be presented with three drop downs as shown below:
Select the recommender type from the drop down, select the recommender sub-group and then choose the specific recommendation algorithm you require for this BMZ in the context of the campaign and Segment. There are 30+ recommenders to choose from. The section below describes the various types of recommenders.
PureClarity offers a full range of recommenders mostly driven by the AI engine, some statistical based and some that can be manual defined by the admin user.
“You May Like”– AI based recommenders using individual’s activities including browsing, past purchasing, basket contents, category likes, brand likes, recent viewed but not bought categories, products and brands; personalized best sellers, offers and new arrivals.
“Personal Activity”– a series of recommenders showing personal activity for products, brands and categories the individual has viewed, purchased and favorites, e.g. “You recent viewed”, “You recently purchased”.
“Segment Related”– a series of recommenders showing best sellers, top rated, viewed and purchased for the Segment that an individual matches; this is refined targeting. For example, showing the best sellers for people who love cameras.
“Crowd-based”– a series of recommenders showing best sellers, top rated, viewed and purchased for everyone. For example, showing the best sellers across everyone.
“Real-time Inspiration”– a series of recommenders showing product, category and brand suggestions based on what is currently happening on the site. For example, “What other customers are viewing right now”.
“Related & Alternative”– recommendations related to other products currently being viewed.
“New Arrivals”– a series of recommenders to show what has been arrived. This is less personalized than the You May Like New Arrivals AI recommenders as it just shows New Arrivals.
“Offer Based”– a series of recommenders showing top offers. This is less personalized than the You May Like Offers AI recommenders as it just shows Top Offers.
“Clearance”– allows the admin user to manual define products that are on clearance
“Moves & Shakers”– shows the fast moving products.
“Basket Related”– a series of recommenders showing recommendations based on the basket content. These are highly personalized recommenders.
“Last Order Related”– a series of recommenders showing recommendations based on the customer’s last order.
“Re-Order"– a series of recommenders showing potential products that the customer may wish to re-order.