All the elements of the “What to start with?” list could also be used in a/b testing. The list here-after provides additional Best Practices that can be quickly tried.
Group | Name | Short description | |
|---|---|---|---|
| 1 | Product Views & Engagement Trends | Most viewed or baskested items within different time frames | |
| 2 | Views > Price Range Views > Higher Price Range | Products which match (or are slightly higher than) the products price range of the previsouly viewed products | |
| 3 | Views > End-up Buying | Products which are often bought in the same session after viewing the same products the current visitor has already viewed | |
| 4 | Views > Defining Tags | Promote products or content with Discovery Tags matching previously viewed products. Each product gets a list of Discovery Tags representing the most common search terms used to find a product. Each product gets a list of Defining Tags representing which is a subset of the product attributes values that have been identified as important in the selection of a product | |
| 5 | Neural Collaborative Filtering for individual recommendations based on the purchases of the customer and leveraging the patterns in the purchase behaviors of other customers | ||
| 6 | Widget Display $Value Self-Learning | Promote products based on the self-learning of the Widget click/display score, either directly on the amount of clicks or on the conversion, average bought value or margin generated by the clicks Display = visual impression detected on the screen of the user before, during and after scrolling on the page | |
| 7 | Basket > Often Bought Together Basket > Collaborative Filtering Bought Together | Promote products often bought together with products already in the basket of the visitor (first practice with statistics, second variant with AI Collaborative Filtering) | |
| 8 | Views > Often Bought Together Views > Collaborative Filtering Bought Together | Promote products often bought together with products the visitor has already viewed (first practice with statistics, second variant with AI Collaborative Filtering) | |
| 9 | Views > Often Viewed in Same Session Views > Collaborative Filtering Viewed Same Session | Promote products often viewed in the same session as products the visitor has already viewed (first practice with statistics, second variant with AI Collaborative Filtering) | |
| 10 | Purchases > Rebuyable products | Promote products the customer has already bought which can be repurchased Each product can be automatically labelled as repurchaseable if enough people bought it several time, or if it belongs to a category you know to be repurchasable or doesn’t belong to any category which you know to be not-repurchasable. |
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