Cross-Selling and Up-Selling
Displays product recommendations that are related to the product that the visitor is viewing, such as “Customers Who Viewed This Also Viewed.” Cross-selling and up-selling has include and exclude rules allowing filtering which type of products are displayed in a recommendation, for example controlling whether the recommendation displays alternatives or supplementary products. The recommendation is also controlled with scoring settings adjusting how relevancy between recommended products is assessed. Read more about include and exclude settings here and scoring settings here.
Shopping Cart Recommendations
Similar recommendation type to cross-selling and up-selling, but intended for shopping cart page. Shopping cart recommendation displays products based on all products in shopping cart and is often displayed as “Customers Who Bought These Bought Also.” Recommendations typically become more relevant when more items there are held in the cart at the same time, as Nosto can base recommended products on more data. Recommended products can be narrowed down to a specific subset using include and exclude settings and scoring settings.
Free Shipping Recommendation
Free shipping recommendation is a similar setting to shopping cart recommendation, but including customisable visibility settings based on total cart value. Otherwise the recommendation type works similarly to the shopping cart recommendation.
Best sellers and trending products or top lists in short is a recommendation type based on overall trend data and popularity displaying what is currently “hot and popular” on the online store. Displayed products can be filtered and for instance narrowed down to a specific selected subset of products by applying include and exclude settings. Read more here.
Geo-targeted Trending Products
Geo-targeted is geo-based version of best sellers, featuring all the same options, but recommending products that are trending in user's location: country, state, city or even city district. Read more here.
Designed as ticker version and instead of showing products that are trending, the recommendation shows in real-time what products current customers interact with: view, add to cart and buy, optionally displaying user's location at a city level. Live feed is designed to create similar buzz effect online that is common during sales seasons in an offline environment.
Recommendation displays visitors the items they viewed or added to their cart, but did not buy, during previous visits to the store (technically browser sessions), giving more weight for items visited more frequently, multiple times and especially those added to the cart, optionally excluding bought items. If a user only interacted with small amount of products, recommendation falls back to relevant alternative items automatically. Usually displayed as: “Items you recently viewed”. Personalized recommendations feature only one additional setting: “Products in shopping cart – Exclude from recommendations”. If selected, products currently held in a shopping cart are removed from the recommendation. Nosto suggests to keep the additional setting enabled. Since the recommendation type is based on personal shopping history, it’s only displayed to visitors who have browsed more than one product during current or previous visits to the site.
Displays visitor’s product browsing history in a linear order. Similar to personalized recommendations, but it doesn’t add any weight for products meaning that products are displayed in the order they have been browsed. Since the recommendation type is based on personal shopping history, it’s only displayed to visitors who have browsed more than one product during current or previous visits to the site.
Browsing History Related
Displays new products related to a visitor’s recent browsing history, excluding products a visitor has already browsed or bought, by comparing visitor’s browsing history to similar profiles. In practice it displays new and unseen products to an individual visitor, based on their personal preferences. Since the recommendation type is based on personal shopping history, it’s only displayed to visitors who have browsed at least one product during current or previous visits to the site. Browsing History Related supports Inclusion and Exclusion Filters which allow for example limiting recommended products to selected categories or to products within a pre-defined margin range.
Search and Visit Related Recommendations
Displays products that other visitors have gone on to view and buy following the same search query in internal search. Alongside with all searches made, recommendation type also catches trending search terms, common typos and in practice is often able to display a recommendation whereas site’s internal search returns an empty search result.
Search and Purchase Related Recommendations
A sibling of Search and Viewed Related Recommendation. Displays items that customers bought after using the same internal search term. Since the recommendation type only tracks purchases made after an internal search it requires massive amount of data to work effectively as only a share of search terms are taken into account. Search and viewed tracks also product views not explicitly conversions making it in almost always more practical recommendation type. Use only if your visitors make a massive amount of searches daily.
Order Related Products
Displays product recommendations that are related to the products a visitor has just purchased. Best used on the thank you for your order page where a successful purchase is communicated to a customer.
Note: When not used there, we will base the recommendations on the previous order.
Landing Page Recommendations
Recommendation type displays items that customers coming in from the same source such as PPC ads have expressed an interest in. Typically used on landing pages, blog posts talking about a specific category, brand or seasonal products to automatically determine common denominators for users after engaging with content. Landing page recommendations take into consideration both UTM tags, and Google gclid parameter, so grouping users by advertisement channel and determining interest after engaging with content happens automatically. Landing Page Recommendations work automatically when deployed on the target page and don't have any additional options, but due to its nature we recommend using Fallback Recommendations with it.
Manual merchandising. Displays always the same products based on productIDs and order of productIDs. Remember to verify that products are instock, since even manual merchandising adheres to availability status.
Shows completely random set of products indexed by Nosto. Intended for debugging and testing purposes for example on test-environments.
Note: Nosto deletes the customer data after 15 months of inactivity. Please consider this time period when using algorithms that require customer data.