VIEW DESCRIPTION - NEW PRODUCTS
A report focusing on newly added products, tracking their performance across different data sources during their first 30 days in the product feed. By combining data from the Product Feed, Google Analytics 4, Google Ads shopping campaigns, and Meta Ads, the report provides key insights into how new products perform immediately after being introduced to the offering. The report displays products added within the last 30 days, based on the product age tracking system in the DataOctopus application.
The report integrates key indicators, including:
Product visibility metrics from Google Analytics (product views, add to cart, begin checkout), providing information about customer interest and purchase intentions for new products
Performance data from advertising platforms, with separate summaries for Google Ads and Meta Ads systems, allowing monitoring of early product effectiveness
Key conversion indicators, including add-to-cart conversion rates and purchase quantities, helping identify which new products best resonate with customers
Revenue and cost indicators from various platforms, with calculated ROAS and COS values to assess early marketing effectiveness
Tracking new product availability, helping monitor whether they are still available in the product feed
TIME RANGE OF DATA
The report is created based on the last 30 days counted from yesterday.
SAMPLE INSIGHTS FROM THE DATA VIEW
Analyze the effectiveness of new products based on preferred metrics. By default, the table is sorted by Google Analytics revenue, but you can change the sorting to find products with the highest number of impressions, clicks, or other indicators in the first days after introduction.
Monitor new product sales pace through Google Analytics indicators analysis. Metrics such as product views (view_item), add to cart (add_to_cart), and begin checkout (begin_checkout) show how quickly new products gain customer interest.
Check if new products receive impressions across all connected advertising systems. For example, if a product has impressions in Google Ads but not in Meta Ads, this may indicate a need to optimize Meta Ads campaign configuration for new products.
Compare click-through rates (CTR) between advertising platforms to identify which new products generate the most interest. Higher CTR may suggest stronger market demand and potential for increased advertising budget.
Analyze return on ad spend (ROAS/COS) for new products to quickly identify which ones have the best advertising potential and deserve budget increases in the first days after introduction.
Track add-to-cart conversion rate (ADD TO CART CR) to identify which new products best meet customer needs and have the highest sales potential.
Use the purchased products quantity metric to identify new products that quickly gain popularity and may require special attention in inventory management.
Monitor product availability to ensure popular new items don't lose sales potential due to stock shortages.
Monitor promotion status of new products to assess their sales effectiveness both at regular and promotional prices in the first period after introduction.
Analyze data at the product category level (product_category_1/2/3) to identify which categories perform best when introducing new items and where to focus future new product introductions.
DATA SCHEMA SPECIFICATION
Product Feed:
id - Product variant identification number
title - Product name
product_category_1 - Category level 1
product_category_2 - Category level 2
product_category_3 - Category level 3
brand - Manufacturer name
price - Product price
sale_price - Promotional price of the product
Data Octopus:
promotion_status - If the product has a Sale Price, it is labeled as "on promotion"
product_age_days - Product age in days. Age is determined based on the date when the product first appeared in the product feed
Google Analytics 4:
ga4_item_view_event - Number of view_item events from Google Analytics
ga4_item_add_to_cart_event - Number of add_to_cart events from Google Analytics
ga4_item_check_out_event - Number of begin_checkout events from Google Analytics
ga4_add_to_cart_conversion_rate - Ratio of add_to_cart events to view_item events from Google Analytics
ga4_item_purchase_quantity - Total quantity of products in purchase events from Google Analytics
ga4_item_netto_revenue - Total net revenue value (excluding tax and shipping costs) from purchase events in Google Analytics
Google Ads Shopping Campaigns:
gads_impressions - Number of product impressions from Google Ads shopping campaigns
gads_clicks - Number of product clicks from Google Ads shopping campaigns
gads_ctr - Percentage ratio of clicks to impressions from Google Ads shopping campaigns
gads_netto_costs - Total net cost value from Google Ads shopping campaigns
gads_conversions - Number of product conversions from Google Ads shopping campaigns. Only primary campaign goal conversions are counted
gads_netto_conversions_value - Total net conversion value from Google Ads shopping campaigns. Only primary campaign goal conversion values are counted
gads_roas - Ratio of net conversion value to net costs from Google Ads shopping campaigns (Net Conversion Value / Net Costs)
gads_cos - Ratio of net costs to net conversion value from Google Ads shopping campaigns (Net Costs / Net Conversion Value)
gads_campaign_count - Number of Google Ads campaigns in which the product was displayed
gads_campaign_names - Names of Google Ads campaigns in which the product was displayed. If the product hasn't been displayed in any campaign yet, returns "Not seen in any campaign"
Meta Ads Shopping Campaigns:
meta_impressions - Number of product impressions from Meta Ads shopping campaigns
meta_clicks - Number of product clicks from Meta Ads shopping campaigns
meta_ctr - Percentage ratio of clicks to impressions from Meta Ads shopping campaigns
meta_netto_costs - Total net cost value from Meta Ads shopping campaigns
Totals:
total_impressions - Total number of product impressions from shopping campaigns across all advertising systems connected to the DataOctopus application
total_clicks - Total number of product clicks from shopping campaigns across all advertising systems connected to the DataOctopus application
total_ctr - Percentage ratio of clicks to impressions from shopping campaigns across all advertising systems connected to the DataOctopus application
total_costs - Total net cost value from shopping campaigns across all advertising systems connected to the DataOctopus application
total_roas - Ratio of net revenue from Google Analytics to total net costs from shopping campaigns across all advertising systems connected to the DataOctopus application (Net Revenue / Total Net Costs)
total_cos - Ratio of total net costs from shopping campaigns across all advertising systems connected to the DataOctopus application to net revenue from Google Analytics (Total Net Costs / Net Revenue)
FAQ
What should I do if the data view in my store doesn't show data?
If your data view isn't working, use the chat icon in the bottom right corner and report the issue to the Data Octopus team.Why is data missing from my view, e.g., from Google Ads?
If there's a problem with missing data from any source, there are three possible causes:
The data source is not connected to the application.
The product identifier (id) from the system with missing data differs from product ids in other systems. For example, in Google Ads we use the warehouse SKU, while in Google Analytics 4 we use the online store id. For the report to work correctly, you need to have the same product identifier across all data sources.
Data across systems is at different levels, e.g., product identifier vs. product variant identifier. A detailed description of this issue can be found in the article Differences in Product Identification Levels.