Going Beyond Cart Abandonments with Facebook Ads - Part 1

Every campaign manager working on an ecommerce site strives to take a data driven approach in his campaigns. This is a common saying all of us will agree on. But what does that mean?

The average advertiser keeps valuable two tools in his toolbox: Remarketing and Lookalike audiences. Using these audiences, it’s relatively simple to generate a positive ROI over time. The above campaigner will set a threshold for the users to which he remarkets or creates lookalikes from.

This threshold can be a low or high one:

1. A low threshold would exclude unengaged users, e.g., bounced users.
2. A high threshold would focus on the highly engaged ones, e.g., cart abandonments.

Matching these behaviors to the products the user engaged with (product views) yields good results. But the harsh truth is that this just doesn’t cut it any more.

Cleaning your lists

Most users coming to your site are irrelevant. Some studies show numbers as high as 60% of users being irrelevant to you. Bounced users are a good example for this, with most sites having a Bounce rate of 60-70%. But what if that user scrolled down the product page, viewed several images and shipping costs. Can they still be counted as irrelevant?

Tracking all the interactions described above is simple – simply add matching events to fire into your ad platforms. These, in turn, can be used to create various segments based on user actions.

But real-life interactions are complex. They use a measure across multiple different user actions, user attributes (device, language, browser, etc.) and their endless mixtures. So even you find the right “mix” of actions and attributes, these are usually hard to manage and tend to change over time.

Crèmè de la crèmè

But cleaning out the unengaged users is only half of the equation. Finding your highest engaged users is just as important and uses a similar process. The classic target audience is users who added a product to their cart but didn’t complete a purchase (AKA Cart Abandonments). The downside to this tactic is that it overlooks a great number of engaged users, leaving you with only a fraction of your top users.

From action-based to intent-based targeting

Working daily with high spend campaigns we’ve experienced these exact pains. Instead of ranting, we decided to develop Fixel, a fully automated segmentation tool that ranks your website audience based on their level of engagement.

Using a powerful machine learning algorithm, we take out the guess work and manual labor from segmentation.

The result is a straightforward user engagement score within the ad platform: Unengaged, Basic, Medium or High. This additional layer of insight enables campaign managers to target their top audiences with the right message accurately.

The user score is set directly on the ad platforms (Google Adwords, Facebook, Twitter and more), and can be used in conjunction with other segmentations you already use.

In Part Two of this post, I'll share specific use cases and explain how easily Fixel integrates with Facebook, Google and other online platforms.

This post originally appeared on the Fixel blog.