Data Views
Brands
Data Octopus Performance Report: performance at the brand level. Date range, insights and full field specifications for GA4, Google Ads and Meta Ads.
View overview – Brands
The report integrates Google Analytics 4 data with Google Ads and Meta Ads Shopping campaigns. Product-level data is aggregated by brand, supporting strategic decisions across the product portfolio. By default, data is sorted by net Google Analytics revenue and covers the last 30 days, with an adjustable date range.
Key performance metrics
- Google Analytics 4 conversion metrics (item views, add-to-cart events and checkouts).
- Advertising campaign metrics (impressions, clicks, costs and ROAS), broken down by platform.
- Aggregated metrics from all connected advertising systems.
- Efficiency metrics: conversion rates, CTR, ROAS and COS.
Conditional formatting highlights the highest values in green, making it easier to identify the best- and worst-performing brands and opportunities to optimise advertising budgets.
Data date range
The report covers the last 30 days, ending yesterday.
Example insights from the data view
- 1Analyse the best-performing brands by your chosen metric. The default sort is Google Analytics revenue; change it to find the highest impressions, clicks or other metrics.
- 2Check discrepancies between revenue and costs for individual brands using conditional formatting. The highest values are highlighted in green; mismatched colours may indicate underinvestment or overinvestment.
- 3Check whether your best-selling brands receive impressions across all advertising sources. If they have no Meta Ads impressions, review campaign segmentation and increase their Meta Shopping budget.
- 4Compare CTR (Clicks / Impressions) across advertising platforms to identify brands attracting consumer interest. High CTR indicates greater market demand because more users click when an ad appears in search results or a feed.
- 5Assess the relationship between advertising spend and revenue (ROAS / COS) to identify brands worth further investment based on historical performance.
- 6Compare view_item with add_to_cart events in Google Analytics to identify brands with the largest drop-offs in the purchase funnel.
- 7Use Purchase Quantity to identify high-value brands that could benefit from additional promotions or dedicated campaign strategies.
- 8Monitor COS by brand to identify which generate the highest margin on advertising spend and where budgets can be optimised.
- 9Track Add to Cart CR trends for individual brands to identify the strongest product-market fit and scaling potential.
Product file
| Field name | Description |
|---|---|
| Product brand | Product brand. |
| Product Id | Product variant identifier. |
| Product Name | Product name. |
Google Analytics 4
| Field name | Description |
|---|---|
| Item Views | Number of view_item events in Google Analytics. |
| Add to Cart | Number of add_to_cart events in Google Analytics. |
| Checkouts | Number of begin_checkout events in Google Analytics. |
| Add to Cart CR | Ratio of add_to_cart events to view_item events in Google Analytics. |
| Purchase Quantity | Total quantity of products in purchase events in Google Analytics. |
| Net Revenue | Total net revenue (excluding tax and shipping) from purchase events in Google Analytics. |
Google Ads Shopping Campaigns
| Field name | Description |
|---|---|
| Impressions | Number of product impressions from Google Ads Shopping campaigns. |
| Clicks | Number of product clicks from Google Ads Shopping campaigns. |
| Click Through Rate | Percentage ratio of clicks to impressions from Google Ads Shopping campaigns. |
| Net Costs | Total net costs of Google Ads Shopping campaigns. |
| Conversions | Number of product conversions from Google Ads Shopping campaigns. Only primary conversions used as campaign goals are counted. |
| Net Conversion Value | Total net conversion value from Google Ads Shopping campaigns. Only primary conversions used as campaign goals are counted. |
| ROAS | Ratio of net conversion value to net Google Ads Shopping campaign costs (Net Conversion Value / Net Costs). |
| COS | Ratio of net Google Ads Shopping campaign costs to net conversion value (Net Costs / Net Conversion Value). |
Meta Ads Shopping Campaigns
| Field name | Description |
|---|---|
| Impressions | Number of product impressions from Meta Ads Shopping campaigns. |
| Clicks | Number of product clicks from Meta Ads Shopping campaigns. |
| Click Through Rate | Percentage ratio of clicks to impressions from Meta Ads Shopping campaigns. |
| Net 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 Click Through Rate | Percentage ratio of total clicks to total impressions from Shopping campaigns across all advertising systems connected to Data Octopus. |
| Total Net 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. |
| 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). |
| 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). |
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