Managing an Amazon store’s performance can be overwhelming, especially with the vast amounts of sales and customer data available. However, understanding whether your advertising investment brings in new customers or encourages repeat purchases is key to optimizing your PPC strategy. Amazon provides New-To-Brand purchase data, which tells sellers how many ad-driven sales come from first-time buyers. Returning customer purchases reflect repeat buyers who have already interacted with the brand. By analyzing this data, sellers can make smarter advertising decisions. In this article, we’ll explore how Defog’s seamless integration with Amazon Advertising helps sellers track the percentage of sales from ads from new vs. returning customers, empowering them to adjust their bidding strategy, campaign focus, and budget allocation to drive sustainable growth.
Amazon Advertising differentiates new and returning customers using New-To-Brand metrics, available only in Sponsored Brands (SB) and Sponsored Display (SD) campaigns. By leveraging AI-powered analytics, Amazon sellers can automatically track their New-To-Brand percentage (NTB%)—the proportion of purchases made by first-time buyers—against their total ad-driven sales. If your NTB% is high, your PPC campaigns effectively acquire new customers. If it’s low, your advertising helps retain existing customers, which can increase customer lifetime value.
To help Amazon sellers easily interpret their New vs. Returning Customer data, we use a bar chart as the primary visualization. A bar chart is ideal because it compares the number of ad-driven purchases made by new customers and returning ones side-by-side.
This is what the results of this article will look like:
Suppose a seller notices that the percentage of returning customers is significantly higher than that of new ones. In that case, they may need to adjust their PPC strategy by increasing ad spend on Sponsored Brands (SB) and Sponsored Display (SD) campaigns, which are more effective at attracting new customers.
By regularly monitoring this data, Amazon sellers can ensure they make profitable advertising decisions—whether they focus on acquiring new customers, increasing brand loyalty, or maintaining a balanced growth strategy.
One great advantage of Defog’s spreadsheet is that once the data is updated, you can repeat the prompt to get the latest insights into your customer behavior.
ChatGPT – Setting Up Google Sheets Integration
Step 1: To facilitate the data upload from Defog to ChatGPT, we suggest you connect your ChatGPT with Google Drive. Here is how to set up this integration. Start by clicking on the paper clip icon and then click on Connect to Google Drive (see images below):
Follow the login and authorization process presented by Google Drive. Then, you can upload data from Google Drive to ChatGPT.
ChatGPT – Upload Your Defog from Google Drive
Step 2: Now that you have connected your Google Drive with ChatGPT, click on the paper clip icon again and then click Add from Google Drive.
You can choose your Defog on Google Drive. For this example, we will use “Defog Advertising (Sample).”
Generate a table showing the percentage of new vs. returning customers based on ad-driven purchases with ChatGPT.
Step 3: Copy and paste the prompt below into your ChatGPT and press send.
Analyze my Amazon PPC campaign data to determine the percentage of ad-driven purchases from new customers vs. returning customers. Use only CampaignSB and CampaignSD worksheets' column 'New-To-Brand Purchases' to calculate the number of new-to-brand customers. Use the column 'Purchases' also from CampaignSB and CampaignSD to calculate the total number of purchases. Compare new vs. returning customers per campaign type (SB and SD) and generate a bar chart to visualize the breakdown for the two types of campaigns. Also, calculate and display the percentage of new vs. returning customers on the chart.
After ChatGPT analyzes the data, you will get a result like the one below.
If you want to learn what a particular column stands for on Defog’s tables, please visit our glossary.
Thank you for reading this post. If you still haven’t used Defog, you can do so for free here.
If you need any help, we are here for you.
Disclaimer: Defog is not responsible for any decisions made by the reader of this post regarding the data, formulas, prompts, and visuals provided.
