Hop Designer
Mayank Verma
Category
Customer, Export
The Customer Segment Builder Hop is a report of all your customer information but what makes this report unique is that it is made for you to build customer segments using filters of your choice. Through this hop, you can create different groups of customers that match the chosen criteria.
It is important to note that all dimensions and metrics are available as filters to build your segment.
As a tip, you can save each segment you create as a new Hop and schedule it to run automatically at any interval of your choice.
Integration(s)
How to use this Hop.
Simply create an Airboxr account and connect your Shopify store to automatically run this export/analysis for your store. If you already have an account, click on the Add to my Collection button above.
Tailored Customer Retention Strategies: Segment customers based on behavior, such as the number of orders, lifetime duration, high-value buyers or even predicted spend tiers. You can design retention strategies tailored to each segment in order to boost customer loyalty and repeat business.
Operational Efficiency and Customer Service: Monitor order fulfillment statuses and track cancellations to identify trends and enhance operational efficiency.
Regional Targeting and Localization: Filter customers by location, including city, state, country, or zip code. This data can be used to identify trends per location and location-based marketing campaigns.
Revenue Optimization and Predictive Analysis: Leverage Shopify's predicted spend tier to categorize customers. Tailor marketing strategies based on spending potential to maximize revenue from each segment.
In This Report
Metrics
Total Spend
Total Orders
Number of Cancellations
Lifetime Spend
Lifetime Orders
Lifetime Average Order Value (AOV)
Additional parameters
Customer Name
Customer E-mail
Customer Phone
Address
City
State
Country
ZIP
Lifetime Duration (in Days)
Predicted Spend Tier
Tags
See also:
Connect your Shopify store and automate this report. You will never have to manually work with data again.