The Frequency panel offers deeper insights into customers based on number of purchases completed. Use the date and segment filters at the top of the page to see how frequency is influenced by specific campaigns and/or timeframes. (You can always download this data as a .csv file using the download icon.)

Using frequency data to improve your marketing 

Frequency data is a powerful way to map your customer lifecycle and loyalty progression. By understanding which stage the majority of your current customers are at, you can determine which retention strategies to implement first.
For example, if you see a high percentage of 1x buyers, then you have a great opportunity to create a First Purchase Automator and drive those 1x buyers to make their second purchase. Conversely, if you notice that a significant portion of your customers (or revenue percentage) are repeat purchasers, you should incentivize customer loyalty with WhatCount’s Best Customer Automator.


A Clarifying Note 

AOV, CLV, and Percent Customers by Lifetime Number of Orders are generated by plotting the individual metrics within the date range against the lifetime number of orders made by each customer. The lifetime number of orders is across all data available and is not limited to the date range. This differs from the Lifetime Number of Orders on the Dashboard as the Dashboard chart takes lifetime orders up to the ending date of the date range. Since the Dashboard compares data year over year, this context is more beneficial.

Common questions about Frequency 

Question: How can I view specific group’s Frequency?
Answer: Use the segment selector at the top of the page to filter data using segments you've built with the Segment Builder

Question: Can you give me an example of how I can analyze/use Frequency data? 
Answer: Look for large jumps in the data. Often you can identify which products are escalation points for your customer base and build out automations to follow up on those purchases. You may also have inflection points around the holiday season or another particular time of year: use this data to focus your marketing efforts on the right customers at the right times. 

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