Upload Products to your Online Store
The most essential part to get your online store started is adding your products. With this tutorial, we want to give you a brief overview of how y...
Product recommendations are a useful mechanism to boost your online sales by offering your other customers products in your catalogue that they might also like, or that are bought together.
Let’s take as an example, a store which is selling perfumes.
When a customer visits a page of a perfume, a good practice is to show him, similar perfumes, namely perfumes from the same brand or targeted for the same gender or with a related smell.
Another good type of recommendation is to suggest other products he could complete his order with. What this means is that, it is a good idea to recommend products that are frequently bought together as bundles in order to increase the volume of purchases.
Also, after a client successfully places an order, sending product recommendations along with the order’s email is a good strategy to boost sales.
At Jumpseller, you’re able to make use of these types of recommendations.
We use Artificial Intelligence to analyse information about your product catalogue and detect which products are semantically more related, that is, more similar.
We do this by processing the information that was filled up by you when creating or editing a product, namely the product names and descriptions.
We also take advantage of the other thousands of customers using Jumpseller, to analyze the sentences and words they used to describe their products in their stores in order to make the recommendation system more robust and accurate.
Let’s go back to the initial example of a store which is selling perfumes.
By analyzing the product name and description we know that keywords such as “Boss”, “Hugo”, “Mujer”, “Perfume”, “rosa”, “frutal” and some others help characterize this perfume.
This way, other perfumes characterized by the same or similar words will be recommended when visiting this product.
If no good recommendations are found by this method, the default is to recommend products within the same category.
In this sense, you have some control over these types of recommendations, since the more accurate and descriptive you are when editing your product, the better the similar product recommendations should be.
The recommendations are usually shown at the bottom of the product page, below the product information, but that behaviour can be changed by editing the theme.
This type of recommendation is currently only available for clients with the Advanced and Enterprise Plan.
Frequently bought together products are shown in product pages.
We use an algorithm to process the recent order history from your store and check which products are bought together so that the next time someone is buying a certain product we can verify which products are more frequently bought with it.
We also take into consideration products that are not bought together at all, and for that reason are less similar in this recommendation case. Taking our previous example, look at the image below.
In this scenario, you have two perfumes being bought together in the same order. If this happens more frequently we can assume that the next time someone buys “PERFUME GOLDEN SECRET VARON EDT 200ML”, the “Perfume The One Hombre Edp 150ml” is a good recommendation to be suggested.
As you can see, the more orders you have in your store history, the more accurate this type of recommendation will be.
In order to access the functionality of Smart Cross-selling, it is necessary to be subscribed to Advanced or Enterprise Plan.
To access this Cross Selling functionalities, in the Admin Panel of your store go to Settings > Checkout > Cross-selling.
This feature supports two ways of performing cross-selling recommendations of your products with Jumpseller.
The first one is recommended products in the cart page, by analysing the current products that the customer added to the cart. By viewing the products the customer is intending to purchase and by using your store’s order history, we try to predict what he would buy or click next.
This is called automatic cross-selling, in the sense that our system is in charge of calculating the recommendations. In the recommendation section of the cart page, you can see these recommendations, where we exclude showing the same products that are present in the cart, unavailable products or products with no stock.
The second way is recommending products via e-mail, after an order has been paid since the procedure is replicated by analysing the products which were bought in that order.
Sometimes, it is not possible to calculate these recommended products for multiple reasons, for instance when your store does not have a big enough order history. When this happens we use a series of fallbacks, that is, we attempt to use similar product recommendations and frequently bought together products in order to avoid the section being empty.
If you wish, you can disable the Recommendation of Related Products, Smart Cross-Selling and Frequently Bought Together Products features for products within the categories of your choice (e.g.: for product bags).
To do this, on your store’s Admin Panel, go to Products > Categories. Select the category of products where you want to disable these features and then, in the Properties section, add the tick corresponding to “Don’t show in recommendations”.
This feature is available for all Jumpseller plans.
Cross Selling functionalities are available in your store Admin Panel, go to Settings > Checkout > Cross-selling.
You can specify manual cross-selling products that will be shown in the cart’s page, but instead of being calculated by Jumpseller, they will be manually selected by you. The limit of cross selling products to be added is 12.
If you have any questions about this or any other topic, do not hesitate to contact us.
The bought together products are calculated every day. If a store just moved to the plan Advanced/Enterprise has to wait at most 24h (assuming it already has orders which are required for the algorithm).
The system requires at least 100 paid orders with more than one product in the last 100 days to calculate packs of Frequently Bought Together products.
The algorithm gives a score for each possible pack of Frequently Bought Together Products using the most recent orders and only shows the best packs (= highest score) so if a product is in a pack that doesn’t make sense (= low score) or it has a product that is set to not show in recommendations: the pack won’t be considered.
No. The system defines if there is enough data to automatically show Frequently Bought Together Products.
Yes, a product with the most bought variant selected might be shown in the generated packs of Frequently Bought Together Products.
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