Marketers in the e-commerce space know this: shopping cart abandonment is the #1 challenge when running an online shop. Most shoppers abandon their carts during the checkout process, but if reminded, are likely to return.
This ability to re-engage customers screams the importance of targeted email campaigns and retargeting ads.
But first, you’ll need to segment your customers. In other words, identify the customers with cold feet and establish a target group for re-engagement.
In this article, we’ll explain how you can build a data app that will segment your "abandoned cart" customers on a daily basis so you can build this target audience without ever lifting a finger.
To identify this particular customer group, we’ll filter our sales data to find customers who left their email address and still have pending items in their shopping cart. After that, we'll send the final “abandoned cart'' customers list to a specified email address (receive your results straight to your inbox). Finally, we’ll schedule this app to be triggered every day at 12 pm.
The behavior data that I will be using is pulled from a medium-sized, online cosmetic store’s database (publicly available on Kaggle).
The table that I found on Kaggle looks like this:
This table contains data for February 2020 from a large online, multi-category store. Each row in the file represents an event related to a product or a user.
For this example, I am interested in the “event-type” and “email” columns.
So, my first step is to filter the original table and find customers who still have items in their shopping carts (this indicates that they left the shop empty handed).
In Intersect, filtering is easy. Just select the “Filter block” and add all the conditions as seen on the image below:
Next, using the "Remove rows with missing values" block, I'll delete the event rows where the customer's email is missing. If we plan to use this list for a retargeting ad or an email campaign, we’ll need to have their emails.
At this point, we have all the data we need as well as a couple of columns that are not relevant for this example. Using the "Select subset of columns" block, we can pick the columns we want to include in the final list.
We add a final "Send email attachment" step to specify who should receive the final list.
Scheduling the app
The data that we used for this example is pretty old; it dates back to February 2020. But, let’s imagine that you are running an e-commerce store on Shopify and you want to get your “abandoned cart” customers on a daily basis.
To do this, you can schedule the data app to run with your own data. Plus, you won’t need to upload your data manually. Intersect supports many native integrations, including Shopify and Woocommerce. When you connect your business tools to Intersect, you will be able to import data automatically and preview it in real-time.
In order to schedule this data app to run every day, you'll need to publish the app and set up a trigger - like in the preview below:
Aaaaand BAM- you’re good to go! Every day this data app will be automatically triggered and you or your manager will receive the list with the “abandoned cart” customers, allowing you to take fast action on missed sales opportunities.
The public version of this data app is available on our website. Explore it and learn how to create your own automated data apps. The Intersect team is here to help, so if you have any questions, feel free to contact us!