Last month, we announced the launch
of Bronto’s newest app, Recommendations Premium. We followed up with a webinar for customers to introduce some of the app’s great features. In this article, we’ll share how you can use it to automate product recommendations and create highly personalized messages that increase customer engagement and conversions.
You set the rules.
At Bronto, we recognize you’re the expert about your business. That’s why our recommendation engine is built to allow you to customize the rules that match shoppers with products. When you create a recommendation, Bronto gives you control over two things: 1. Predictive model – You can choose from a variety of models that use machine learning algorithms to identify relationships among products based on contacts’ browse and purchase histories and related product content. Examples of predictive models you can choose include:
- Bought This Bought That.
- Frequently Bought Together.
- Browsed This Browsed That.
This optional element leverages the most “intelligence” to find the best products for your customers.
2. Business rules – You can choose the product criteria that determines which products are recommended to shoppers. For example, you can set your criteria to always recommend products above a certain profitability margin or price, recommend products that are top sellers on your website, or suppress recommendations of products purchased within a certain time frame. And those are just a few of the options available to you.
Customize by product.
The Product Criteria card is where most of the customization for your business takes place, and it all depends on your product catalog. The more data you provide on your products, the more you can control the resulting recommendations.
First, if you have a product catalog with parents and variations, you can decide to show parents, variations, or both, in your results. Then, add an unlimited number of criteria to limit or exclude products in the results based on your business rules. Now, let’s say you want your recommendation to find products that are explicitly related to the products your consumers are engaging with, such as same brand, category or price range, or even more specifically within a set of user-defined products. You can do that from the Related Products Criteria card.
Exclude products based on contact history.
Customization is great, but if it doesn’t prevent you from recommending a product someone bought last week, it’s not very helpful. Use the Contact History Criteria card to exclude products the consumer has ordered in the past or limit results to products the consumer has browsed over a selected period of days.
Prioritize product results.
For recommendations that do not contain predictive models, you can use the Priorities card to define the prioritization of results. For example, you might decide products with the highest prices or customer ratings are important criteria for sorting recommendation results.
Recommend based on products in the email.
The last area where you can customize your product recommendation results is Reference Products. Use the options here to determine whether your recommendation results will be based on the products in the email or on the recent history of your customer. Finally, once you’ve built your recommendation, use Preview Results to confirm it is working the way you want before you select Publish, which makes your recommendation available for use.
All of these options give you more control over customizing your product recommendations to align with your revenue and business goals. And just in case you aren’t sure where to get started, Bronto provides almost 40 recommendation templates to get you started. Check out my next article, Recommendations Premium: Just Build and Go
, to learn more about how easy it is to create personalized messages that contain product recommendations. For more information about the app, contact your Bronto Account Manager.