• LinkedIn

New version of the report

The new version of the report is not only new functionality, but also improvements to existing solutions. We have made a number of changes to make the report even better suited to your needs.

Key changes:

• Description has been added to each table and chart with information on what it represents
• Description with their definitions has been added to the metrics in the charts, which displays when the cursor hovers over the “i” field
• New tab in the Data Octopus section – Detailed PT vs CL, which is a compilation of Custom Label and Product Type information
• In the Data Octopus section, new charts have also been added to existing tabs, information about the date range and new filters
• In the Profitability Sheet section there are tabs with compiled results from the perspective of overall daily profitability – Profitability Daily, and a specific product, brand, category – Profitability Product/Brand/Category for a period of 7 days, 30 days and the current month
• MTD Profitability tab removed

Functional value:

• Increased clarity and understanding with additional descriptions
• Expanded analysis capabilities. New tabs and charts allow you to dig deeper into the data and discover new relationships
• New Profitability Sheet structure provides easier access to key profitability indicators from a product, brand and category perspective

Documentation of the Reports can be found in Wiki & Help here.

Product Fields Library

Product Fields Library is a revolutionary way to enrich data about any product. Originally, the application required knowledge of what data based on the Master model you wanted to add and “clicking” it using rules.

Today this is no longer required. The Data Octopus team has prepared predefined, additional product data and the rules that build it. The involvement and necessary knowledge have been limited to a minimum, and the user is effectively inspired by what can and is worth adding, and how it can be used in business.

From now on, the user does not have to come up with the idea that it is worth adding a value to products that segments them according to revenue, first or second degree profit or price. All he has to do is decide that it has value for him and select such a field, and the application will generate it itself.

Selected Product Fields:

• Margin Segment
• Profit Segment lvl 1
• Price Segment
• Competition price
• Zombie

You can find a list of all Product Fields with a description and a short presentation in the Wiki & Help here.

Functional value:

• Predefined data and rules – the library offers ready-made sets of predefined segmentation strategies and rules, eliminating the need to invent and create them from scratch
• Minimal requirements – the user does not need deep technical knowledge to use the solution
• Automation – the application takes over some of the routine tasks, allowing the user to focus on the strategic and business aspects

New tabs in Product Ad Overview Reports Section

New section in Product Ad Overview tab in Reports based on data from Google Ads and Meta Ads systems.

ADS Overview – showing the results from advertising systems, comparison of expenses of both systems, daily results

Meta Ads – showing the results of the Meta Ads system, the number of impressions, clicks, costs and metrics such as CTR and CPC.

Documentation of the Reports can be found in Wiki & Help here

Functional value:

• comparison of both systems in one place
• analysis of the performance of a given system with regard to the most important factors

Google Ads Label and Revenue Rank tab in the Reports Section

A new tab in the Reports section based on Revenue Rank and Google Ads labels segments. The report is based on the Master data model and assigns a specific product to a segment in the context of the revenue generated.

Documentation of the Reports can be found in Wiki & Help here.

Functional value:

• No need to use Google Sheets to analyze sales data by product segment.
• No limitations typical for data processing in Google Sheets.
• Knowledge of how products are performing in a specific segment.
• Ability to quickly check the performance of a specific product by ID.

E-commerce Engine Tab in the Reports Section

A new report in the application powered by product data from the e-commerce engine. The e-commerce engine is often the best source of information on the actual quantity and value of sales. Additionally, it has data on the quantity and value of returns, which can be the basis for a new look at the sales performance of products in the store’s offer.

The report consists of several sections:

1. Overview 30 days

• Customers
• Orders
• E-commerce Revenue
• Quantity
• AVG basket value
• AVG SKU
• Reve/Orders/Customers comparison of the last 30 days to previous days
  and more…

2. Overvierw 365 days

• Reve/Orders/Customers comparison month to month

3. Delivery map

• Interactive, geographic heat map of shipments with option to filter by revenue, orders, customers, product, category

Documentation of the Reports can be found in Wiki & Help here.

Functional value:

• A more complete view thanks to data directly from the e-commerce engine.
• New data as a basis for developing the Master data model and additional product segmentations.
• Ability to calculate 2nd level margin, which takes into account the quantity and value of returns, revenue, profit after margin and advertising costs.
• Inspiration for how to manage the geography of image campaigns.

Reporting Environment

The reporting environment is made available in the Data Octopus app. We used Looker Studio to build it, which is based on data in Google BigQuery. The same data powers our proprietary Master data model, which is the basis for product segmentation.

The report consists of several sections:

1. E-commerce Overview

• Sales Funnel Overview
• Impression and Clicks overview
• Campaign Overview
• Category Overview
• Brand Overview
• Product Overview
• Profit Overview

2. AD systems overvierw

• Google Ads

3. Feed Octopus

• GA4 Performance
• Google Ads Performance

Documentation of the Reports can be found in Wiki & Help here.

Functional value:

• Activation of data stored in BigQuery not only for Data&Feeds but also for Reports.
• Combining key product data from multiple sources in one place.
• Insight into the sales performance of products, brands, categories based on data from Google Ads, Google Analytics 4, the e-commerce engine.
• Support in making decisions on sales strategies, advertising budget allocation, etc.

Integration with IdoSell

We have developed an API connection with one of the most popular e-commerce platforms in Poland. IdoSell is over PLN 16 billion in GMV annually and is a very often chosen platform for the high market e-commerce segment. It is also the most frequently represented e-commerce engine among Data Octopus customers.

Full documentation of the integration along with the specification of the data collected can be found in Wiki & Help here.

Functional value:

• High-quality product sales data combined with data from other sources in BigQuery provides the potential to create completely new segments.
• Ability to calculate 2nd level margin, which takes into account the quantity and value of returns.
• Ability to fully assess the effectiveness of advertising campaigns using this data.
• Ability to validate sales data between the e-commerce engine and Google Analytics 4.

Export table view to Excel

It is now possible to export any table from the Data Octopus app to Excel. Using the Export to Excel button, a table file in xlsx format is downloaded to our device.