Bunting offers many algorithms which can be applied to Product Recommendations, with each having certain levels of suitability for different pages of your eCommerce website.
The following list details the algorithms and the uses for them:
- Adaptive – These are the default setting for recommendations from Bunting using a machine learning algorithm to detect what the best recommendations are given in the context of the page.
- Recently Viewed by Visitors
- Most Popular – Last 24 Hours
- Most Popular – Last 7 Days
- Most Popular – Last 30 Days
- Popular Alternatives – This is most often used on Product Pages. It takes into consideration what customers view, add to cart and buy after viewing the specified product.
- Cross Selling – Commonly shown on both Cart/Checkout pages and Product pages. This takes into consideration what other customers buy from these pages.
- Repeat Custom – This will determine what customers usually buy, based on what their last purchase was. The context for this is the order complete page, this is done cumulatively.
Continue reading What Product Recommendation algorithms are there?
Can I still use Google Analytics if I install Bunting?
Yes, of course! In fact, the first stage of the Measure Impact step is an option to turn on Google Analytics Event Tracking.
Many of our clients still have Google Analytics and use it alongside Bunting. This allows them to make a more informed decision on just how much ROI Bunting is providing.
Continue reading Can I still use Google Analytics if I install Bunting?
How to filter recommendations by Brand?
This can be implemented on variations in a recommendations content campaign in the Recommendations Settings. Here if you navigate to Content of Recommendations then Filters there is a Brand Filters drop-down. From here there are 2 options. Only show products from the following brands: or Hide products from the following brands:. Once an option has been selected there is functionality to add specific brands or only show the brand of product being viewed.
Continue reading How to filter recommendations by Brand?