VIEW DESCRIPTION - NEW PRODUCTS
A report analyzing lost revenue associated with products that generated sales in the last 30 days but are currently unavailable in the product file. The report combines data from Google Analytics 4, Google Ads shopping campaigns, and Meta Ads, providing a complete picture of potential revenue losses related to product unavailability. By default, data is sorted by net revenue from Google Analytics, showing products with the greatest impact on lost revenue.
The report integrates key indicators, including:
Sales metrics from Google Analytics (product views, add to cart, revenue), showing the scale of interest in products before their disappearance from the offer
Advertising indicators from various platforms, enabling assessment of effectiveness and costs of promoting products that are no longer available
Temporal data indicating when the product was last available in the product file
Detailed information about categories and manufacturer, helping identify areas requiring special attention in assortment management
TEMPORAL DATA RANGE
The report is created based on the last 30 days counted from yesterday.
SAMPLE CONCLUSIONS FROM THE DATA VIEW
Analyze the value of lost revenue by sorting products according to Google Analytics revenue to identify which withdrawn products had the greatest impact on sales.
Check Google Analytics metrics (view_item, add_to_cart, begin_checkout) to understand the level of customer interest in products during the 30 days before their withdrawal.
Monitor advertising campaign cost indicators (gads_netto_costs, meta_netto_costs) to manage the budget that was used for advertising products no longer in the offer.
Compare the total number of impressions (total_impressions) and clicks (total_clicks) of withdrawn products from different advertising systems to assess the potential impact on store traffic and identify possible decrease in user numbers caused by lack of popular products. Special attention should be paid to products with high CTR, whose absence may significantly affect the overall effectiveness of marketing activities and store traffic volume.
Analyze data at the category level (product_category_1/2/3) to detect availability issues in specific assortment segments.
Track ROAS/COS indicators to assess their marketing effectiveness for products no longer available in the offer.
Use manufacturer information (brand) to identify potential bestseller shortages in your key brands from the offer.
Analyze the number of campaigns (gads_campaign_count) and their names (gads_campaign_names) in which withdrawn products appeared to optimize spending in campaigns due to lost assortment.
Monitor the add-to-cart conversion rate (add_to_cart_conversion_rate) of withdrawn products to identify high-potential products worth returning to the offer.
Check the promotion status (promotion_status) of withdrawn products to assess whether promotions could have influenced stock depletion.
DATA SCHEMA SPECIFICATION
Product File:
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 had a Sale Price then it is labeled "on promotion"
last_seen_date - Date when the product was last in the product file
last_seen_in_days - Number of days that have passed since the date when the product was last in the product file
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 (without tax and shipping costs) from purchase events in Google Analytics
Google Ads Shopping Campaigns:
gads_impressions - Number of product impressions from shopping campaigns in Google Ads
gads_clicks - Number of product clicks from shopping campaigns in Google Ads
gads_ctr - Percentage ratio of clicks to impressions from shopping campaigns in Google Ads
gads_netto_costs - Total net cost value from shopping campaigns in Google Ads
gads_conversions - Number of product conversions from shopping campaigns in Google Ads. Only main conversions that are campaign goals are counted
gads_netto_conversions_value - Total net conversion value from shopping campaigns in Google Ads. Only the value of main conversions that are campaign goals is counted
gads_roas - Ratio of net conversion value to net costs from shopping campaigns in Google Ads (Net conversion value / Net costs)
gads_cos - Ratio of net costs to net conversion value from shopping campaigns in Google Ads (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, the value "Not seen in any campaign" is returned
Meta Ads Shopping Campaigns:
meta_impressions - Number of product impressions from shopping campaigns in Meta Ads
meta_clicks - Number of product clicks from shopping campaigns in Meta Ads
meta_ctr - Percentage ratio of clicks to impressions from shopping campaigns in Meta Ads
meta_netto_costs - Total net cost value from shopping campaigns in Meta Ads
Totals:
total_impressions - Total number of product impressions from shopping campaigns from all advertising systems connected to the DataOctopus application. For example, if you have Google Ads, Meta Ads, and Bing Ads connected to DataOctopus, and the product received 1 impression from Google Ads, 1 from Meta Ads, and 1 from Bing Ads, the total number of impressions will be 3 (sum from all sources)
total_clicks - Total number of product clicks from shopping campaigns from all advertising systems connected to the DataOctopus application
total_ctr - Percentage ratio of clicks to impressions from shopping campaigns from all advertising systems connected to the DataOctopus application
total_costs - Total net cost value from shopping campaigns from all advertising systems connected to the DataOctopus application
total_roas - Ratio of net revenue from Google Analytics to total net costs from shopping campaigns from all advertising systems connected to the DataOctopus application (Net revenue / Total net costs)
total_cos - Ratio of total net costs from shopping campaigns from all advertising systems connected to the DataOctopus application to net revenue from Google Analytics (Total net costs / Net revenue)
FAQ
What to do if the data view in my store doesn't show data?
If you have a non-functioning data view, use the chat icon in the bottom right corner and report the problem to the Data Octopus team.
Why is my view missing data, e.g., from Google Ads?
If there is a problem with missing data from any source, there are three possibilities for its occurrence:
The data source is not connected to the application.
The product identifier (id) from the system where data is missing differs from product ids in other systems. For example, in Google Ads we use the product SKU from the warehouse, and in Google Analytics 4 the id from the online store. For the report to work correctly, you need to have the same product identifier in all data sources.
Data across systems is at different levels, e.g., product identifier and product variant identifier. A detailed description of this problem can be found in the article Differences in product identification levels.