Data Views
Lost Revenue
Data Octopus data view: products that generated sales in the last 30 days but are no longer in the product file. Field specifications, insights and troubleshooting.
View overview – Lost Revenue
This report analyses potential lost revenue associated with products that generated sales in the last 30 days but are no longer present in the product file. It combines Google Analytics 4, Google Ads Shopping campaigns and Meta Ads to show the potential impact of unavailable products. By default, data is sorted by Google Analytics net revenue, showing the products with the largest potential revenue impact.
Key metrics
- Google Analytics sales metrics (item views, add-to-cart events and revenue), showing interest before products disappeared from the assortment.
- Advertising metrics across platforms to assess performance and promotion costs for unavailable products.
- Date information showing when each product was last present in the product file.
- Category and manufacturer details to identify assortment areas requiring attention.
Data date range
The report covers the last 30 days, ending yesterday.
Example insights from the data view
- 1Analyse lost revenue by sorting products by Google Analytics revenue to identify which withdrawn products contributed most to sales.
- 2Check Google Analytics metrics (view_item, add_to_cart, begin_checkout) to understand customer interest during the 30 days before withdrawal.
- 3Monitor campaign costs (gads_netto_costs, meta_netto_costs) to reallocate budget previously used to advertise products no longer offered.
- 4Compare total_impressions and total_clicks across advertising systems to assess the potential effect of withdrawn products on store traffic. Pay particular attention to high-CTR products whose absence may significantly affect marketing performance and traffic.
- 5Analyse product_category_1/2/3 to detect availability problems in specific assortment segments.
- 6Track ROAS/COS to assess the marketing performance of products no longer offered.
- 7Use brand information to identify missing bestsellers among your key brands.
- 8Analyse gads_campaign_count and gads_campaign_names for withdrawn products to optimise campaign spending after assortment loss.
- 9Monitor add_to_cart_conversion_rate for withdrawn products to identify high-potential products worth bringing back.
- 10Check promotion_status for withdrawn products to assess whether promotions may have contributed to stock depletion.
Product file
| Field name | Description |
|---|---|
| id | Product variant identifier. |
| title | Product name. |
| product_category_1 | Level 1 category. |
| product_category_2 | Level 2 category. |
| product_category_3 | Level 3 category. |
| brand | Manufacturer name. |
| price | Product price. |
| sale_price | Sale price. |
Data Octopus
| Field name | Description |
|---|---|
| promotion_status | If the product had a Sale Price, it is labelled "on promotion". |
| last_seen_date | Last Seen Date: the date the product was last present in the product file. |
| last_seen_in_days | Last Seen in Days: the number of days since the product was last present in the product file. |
Google Analytics 4
| Field name | Description |
|---|---|
| ga4_item_view_event | Number of view_item events in Google Analytics. |
| ga4_item_add_to_cart_event | Number of add_to_cart events in Google Analytics. |
| ga4_item_check_out_event | Number of begin_checkout events in Google Analytics. |
| ga4_add_to_cart_conversion_rate | Ratio of add_to_cart events to view_item events in Google Analytics. |
| ga4_item_purchase_quantity | Total quantity of products in purchase events in Google Analytics. |
| ga4_item_netto_revenue | Total net revenue (excluding tax and shipping) from purchase events in Google Analytics. |
Google Ads Shopping Campaigns
| Field name | Description |
|---|---|
| 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 costs of Google Ads Shopping campaigns. |
| gads_conversions | Number of product conversions from Google Ads Shopping campaigns. Only primary conversions used as campaign goals are counted. |
| gads_netto_conversions_value | Total net conversion value from Google Ads Shopping campaigns. Only primary conversions used as campaign goals are counted. |
| gads_roas | Ratio of net conversion value to net Google Ads Shopping campaign costs (Net Conversion Value / Net Costs). |
| gads_cos | Ratio of net Google Ads Shopping campaign costs to net conversion value (Net Costs / Net Conversion Value). |
| gads_campaign_count | Number of Google Ads campaigns in which the product received impressions. |
| gads_campaign_names | Names of Google Ads campaigns in which the product received impressions. If none, returns "Not seen in any campaign". |
Meta Ads Shopping Campaigns
| Field name | Description |
|---|---|
| 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 costs of Meta Ads Shopping campaigns. |
Totals
| Field name | Description |
|---|---|
| total_impressions | Total product impressions from Shopping campaigns across every advertising system connected to Data Octopus. For example, 1 impression each from Google Ads, Meta Ads and Bing Ads adds up to 3 impressions. |
| total_clicks | Total product clicks from Shopping campaigns across every advertising system connected to Data Octopus. For example, 1 click each from Google Ads, Meta Ads and Bing Ads adds up to 3 clicks. |
| total_ctr | Percentage ratio of total clicks to total impressions from Shopping campaigns across all advertising systems connected to Data Octopus. |
| total_costs | Total net Shopping campaign costs across every advertising system connected to Data Octopus. For example, PLN 1 each from Google Ads, Meta Ads and Bing Ads adds up to PLN 3. |
| total_roas | Ratio of Google Analytics net revenue to total net Shopping campaign costs across all advertising systems connected to Data Octopus (Net Revenue / Total Net Costs). |
| total_cos | Ratio of total net Shopping campaign costs across all advertising systems connected to Data Octopus to Google Analytics net revenue (Total Net Costs / Net Revenue). |
Questions and answers
What should I do if the data view shows no data for my store?
In the Data Octopus app, use the chat icon in the bottom-right corner to report the issue to the Data Octopus team.
Why is data missing from a source such as Google Ads?
Possible causes: the data source is not connected; product identifiers differ across systems (for example, warehouse SKU in Google Ads and store ID in GA4); or data uses different identification levels (product versus variant). The report requires consistent product identifiers and identification levels across all sources.
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