trbo Insights – Susanne Horvat’s Favorite Feature

In our blog series, we asked our colleagues what their favorite feature in the trbo tool is. After Giovanna gave us insights into multi-variant tests last time, Senior Client Success Manager Susanne Horvat shows us how to strategically place product recommendations in the user journey.

1. Which trbo feature do you particularly like to implement?

I’m a big fan of strategically placing product recommendations in the user journey to minimize the bounce rate. That’s why I like to combine the possibilities of our currently 23 different product recommendation templates with the trigger ‘exit intent’ on desktop or ‘mobile return’ on mobile and tablet or ‘inactivity’.

2. Can you describe the product recommendation insertion feature in a bit more detail? Where can it be included on a website and what opportunities does it create?

As soon as a user wants to leave the website and moves the mouse cursor towards the browser address bar to close the window or tab, this behavior is detected and triggers the playout of an ‘exit intent’ overlay. The user is then reminded that there are still items in their shopping cart. This is a crucial moment in the customer journey, when the user can change their mind and ideally stays on the website to complete the purchase. If the user does not yet have any items in the shopping cart, this measure can also inspire them to make spontaneous buys by suggesting exclusive offers or top sellers. 

Since the ‘exit intent’ trigger is only applicable on desktop, the counterpart for mobile and tablet is the ‘mobile return’ trigger. This element is displayed when the user has left the tab via one of the mobile browser elements and returns to the same window. 

The ‘inactivity’ trigger in combination with the display of product recommendations is also helpful to remind the customer that they have products waiting in their shopping cart if the user has not been active for a certain amount of time.

3. Why exactly do you like this measure so much?

I find dynamic product recommendations that are based on user behavior particularly exciting. For example, the user can be shown the products in their shopping cart before they want to leave the website or is inactive. The same applies to the last products viewed, to remind them of their interests. This individual approach, which is made possible by our filling logics and additional filter settings, is often the deciding factor in the conclusion of a purchase, which would never have taken place without this measure. 

4. An online retailer wants to implement the feature on their website. What advice would you give them before implementing it?

There should be careful consideration of how to address customers who want to leave the website. As an online retailer, I have to put myself in the target group’s shoes. Do I opt for a nice ‘Are you sure you want to leave already?’ with an offer to get in touch if they have any questions using the contact details provided, and add discreet product recommendations? Or do I prominently point out the products in the shopping cart to the user who wants to leave?

5. Is this feature an all-time classic or do you think its impact has been underestimated so far?

I think that the positive impact of product recommendations in combination with triggers for inactivity or bounce is still very much underestimated, because the focus of product recommendations is on product detail pages and in the shopping cart, which is of course completely correct. But as soon as an online store is struggling with high bounce rates, this would be a good measure to combat it.

6. Which industries can benefit most from this strategy? Can you give us some examples?

This measure is a winner for all industries that have a range of products to choose from — and minimizing bounce rate and increasing spontaneous purchases is what every online store wants.