Easy online data management with DataOrganizer 🌟

Gain access to up-to-date data from your e-commerce store. Our robots automatically analyze information from various sources, giving you full control over your e-commerce.

What you will find in the reports

Here you will find answers regarding DataOrganizer data from store systems such as WooCommerce, Idosell and Magento 2, as well as Google Analytics statistics and Google Ads, Facebook Ads, Criteo and Tradetracker advertising data. If you have any questions, our support team is ready to help.

Chart Revenue for the last 30 days

The graph shows Net Revenue for the last 30 days. Net revenue per day from the store system(s) (from selected markets) whose data is connected to Datadiary. Net revenue only applies to orders with the status fulfilled and in progress for the given period.

The graph does not show statistical data from Google Analytics, but full revenue data from the store system(s).

Chart Costs for the last 30 days

The graph shows all Media Costs from the last 30 days. It shows the total costs for media expenses including advertising and affiliate commissions from all connected data sources, i.e. Google Ads, Meta Ads etc. to Datadiary per day.

Table Key Performance Indicators

The table presents data from the last periods: yesterday, last 7 days, last 30 days and the current month. For each of these periods, a comparison to the previous period is available, with information on whether the current period is better or worse than the previous one, along with a visual indicator of the difference.
In the table, you will find KPIs such as:

Net revenue – Information on revenue without VAT, only for orders completed and in progress.
Media costs – Total media costs from connected advertising and affiliation systems.
Media cost share – Ratio of media costs to net revenue. A lower indicator means a higher margin and profitability of the company.
Number of orders – Orders fulfilled and in progress according to data from the store system.
Discount granted – The sum of the discount, as the difference between the regular price and the actual selling price of the products.

Table Google Analytics Data

Google Analytics needs time to process the data, so full information is only available after 72 hours. Data from the last three days may be incomplete. The table includes data from periods such as yesterday, last 7 days, last 30 days and the current month. You can compare it with previous periods, and the differences are highlighted in color. You will find key metrics such as the number of users (new and returning), sessions, interactions with products (e.g. adding to cart, views) and the number of purchases. All data is collected in accordance with GDPR regulations and may be subject to user consent for cookies.

Chart Income and expenses

The chart shows net revenue and media costs for the selected period for specific markets.

– Net revenue per day from the store system(s) whose data is connected to Datadiary. Net revenue only applies to orders with the status fulfilled and in progress for the given period.

– Media costs is the sum of costs for media expenses including advertising and affiliate commissions from all data sources connected, i.e. Google Ads, Meta Ads, etc. to Datadiary per day.

The chart does not show statistical data from Google Analytics, but full revenue data from the store system(s).

Chart Revenue prediction

The graph shows net revenue from the last 4 days and the revenue prediction calculated from the last four days and the revenue prediction for the next 4 days.

– Net revenue per day from the store system(s) whose data is connected to Datadiary. Net revenue applies only to orders with the status fulfilled and in progress for the given period.
– Revenue prediction is the estimated net revenue calculated based on Datadiary’s predictive models based on collected and processed data in the research and analytical methodology.

Chart Media costs by source

The pie chart displays all Media Costs broken down by source in percentage and dollar terms when you hover over the chart for the selected time period.

Table Income and expenses per day

Delivery method – Types of delivery methods available in the store, according to data from the store system.
Delivery type – Information whether the delivery was free or paid for by the customer.
Number of orders – Number of orders completed and in progress from the store system.
Percentage share – Percentage share of a given delivery method in all orders in a given period.
Fee cost – Total costs incurred by customers for a given type of delivery.
Revenue – Revenue excluding VAT from completed and in progress orders.

Table Monthly Income and Expenses

Net revenue – Revenue excluding VAT, only for orders that have been completed and are being completed.
Media cost – Total costs from connected advertising and affiliation systems.
Number of orders – Total number of orders completed and are being completed in the store system.
GAds cost – Total costs incurred for Google Ads ads.
Meta Ads cost – Total costs incurred for Meta Ads ads.
Tradetracker cost – Total commissions for accepted and completed orders acquired through ads from Tradetracker.
Criteo cost – Total commissions for accepted and completed orders acquired through ads from Criteo.
COS – Cost of sales indicator, calculated as the sum of media costs divided by net revenues from completed and in progress orders.

Table Interactions with products

Table presents key metrics for the selected period with the option to compare to the previous period, along with highlighting differences in color.
Source, Medium, Campaign – Data can be passed to Google Analytics in three ways:UTM – Adding utm_source, utm_medium, utm_campaign parameters to store links.

Google Ads Auto Tagging – Automatically adding UTM parameters to ad URLs.

Referral – Referrer pages that provide the source and medium.

Market – Information about the store or market the product comes from.

Product – Unique product name with variant, assigned to the identifier.
Source – A parameter that specifies where the user’s traffic comes from, e.g. utm_source.
Medium – A parameter that specifies the advertising medium, e.g. utm_medium.
Campaign – A parameter that describes the advertising campaign, e.g. utm_campaign.
Products Viewed – The number of times a product was viewed on different store pages, from Google Analytics.
Products Added to Cart – The number of times a product was added to the cart from Google Analytics.
Products Purchased – The number of times a product was purchased from Google Analytics.
GA Product Revenue – The gross sum of orders excluding shipping costs from Google Analytics, which does not reflect the exact data from the store.

Table Revenue and number of orders

The table presents specific metrics and data for the selected period along with the ability to check the comparison of data to the previous period with information whether the current period is better or worse than the previous one along with a color-coded difference.

Information about the Source, Medium and Campaign can be transferred to Google Analytics in three ways:

Through UTM parameters, i.e. adding the utm_source, utm_medium, utm_campaign parameters to the store links.
Through Google Ads automatic tagging – Google Ads automatic tagging is a feature that allows you to track Google Ads campaigns in Google Analytics. This feature automatically adds UTM parameters to the URLs of Google Ads ads. In the case of Google Ads automatic tagging, the medium parameter takes the value “cpc” (i.e. – cost per click) and the Campaign parameter is determined based on the Google Ads campaign from which the user comes. For example, if a user came to a website from a Google Ads ad whose campaign name is “spring_campaign”, the value of the campaign parameter will be “spring_campaign”.
Through referring pages, so-called referrals, which can pass the source and medium parameters. – When a user enters the store from another page through a link placed on it without UTM parameters, the source will indicate the address of the page from which the user came to the store, and the medium will be indicated as “referral”.

Source – A parameter informing about which advertising source or page the user came to the store from. In the case of the source parameter, you can use the UTM parameter called utm_source, which is used to determine the source of traffic. For example, if the utm_source parameter has the value “google”, the source will be “google”.
Medium – A parameter informing about which advertising medium the user came to the store from. In the case of the medium parameter, you can use the UTM parameter called utm_medium.
Campaign – A parameter informing about the advertising campaign from which the user came to the store. In the case of the campaign parameter, you can use the UTM parameter called utm_campaign.
Number of GA purchases – The number of orders regardless of their status that were recorded in Google Analytics as statistical information in accordance with GDPR, consent expressed to cookies and Behavioral Modeling.
GA revenue – The gross sum of the order value together with the cost of delivery from Google Analytics shows only the sum of orders without verifying the status of these orders and does not present the real sum of orders from the store. This is because Google Analytics is only a statistical tool collecting data from devices that have agreed to cookies or when data is transferred in accordance with GDPR if data transfer to Behavioral Modeling is set correctly. Google Analytics revenue with unknown status will never be equal to store system revenue for orders with order status completed or in progress from store data.

Table Interactions with products

Information about the Source, Medium and Campaign can be transferred to Google Analytics in three ways:

Through UTM parameters, i.e. adding the utm_source, utm_medium, utm_campaign parameters to the store links.
Through Google Ads automatic tagging – Google Ads automatic tagging is a feature that allows you to track Google Ads campaigns in Google Analytics. This feature automatically adds UTM parameters to the URLs of Google Ads ads. In the case of Google Ads automatic tagging, the medium parameter takes the value “cpc” (i.e. – cost per click) and the Campaign parameter is determined based on the Google Ads campaign from which the user comes. For example, if a user came to a website from a Google Ads ad whose campaign name is “spring_campaign”, the value of the campaign parameter will be “spring_campaign”.
Through referring pages, so-called referrals, which can pass the source and medium parameters. – When a user enters the store from another page through a link placed on it without UTM parameters, the source will be indicated by the address of the page from which the user came to the store, and the medium will be indicated by the value “referral”.

Market – Presents information about the store/market from which the presented product comes and information about it.
Product – The unique name of the product with its variant, if any, assigned to the unique identifier. The product name is a pair with the identifier.
Source – A parameter informing about the advertising source or page from which the user came to the store. In the case of the source parameter, you can use the UTM parameter called utm_source, which is used to specify the source of traffic. For example, if the utm_source parameter is “google”, then the source will be “google”.
Medium – A parameter that informs which advertising medium the user came to the store from. In the case of the medium parameter, you can use the UTM parameter called utm_medium.
Campaign – A parameter that informs about the advertising campaign that the user came to the store from. In the case of the campaign parameter, you can use the UTM parameter called utm_campaign.
Products Viewed – The number of times products were viewed on category cards, product cards, and in sections presenting products on the store page with Google Analytics. This metric does not only show the view_item event but also products from the view_item_list metric.
Products added to cart – The number of times a product was added to the cart from Google Analytics.
Products purchased – The number of purchases of a given product from Google Analytics.
Product GA revenue – The gross sum of the order value excluding shipping costs from Google Analytics only shows the sum of orders without verifying the status of these orders and does not present the real sum of orders from the store. This is because Google Analytics is only a statistical tool that collects data from devices that have agreed to cookies or when data is transferred in accordance with the GDPR if data transfer to Modeled Behavioral is set correctly. Google Analytics revenue with an unknown status will never be equal to the revenue from the store system for orders with the order status completed or in progress from store data.

Table Events in the store

<div>Table shows key metrics and data comparison to the previous period, with a color-coded highlight of the difference.
Data source in Google Analytics can be passed in three ways:

Via UTM – Adding <code>utm_source</code>, <code>utm_medium</code>, <code>utm_campaign</code> parameters to store links.

Google Ads auto tagging – Adds UTM parameters to Google Ads URLs.

Referral – For non-UTM links, the source is the site address and the medium is “referral”.

Source – Set by <code>utm_source</code>, e.g. “google”.

Medium – Defined by <code>utm_medium</code>.
Campaign – Defined by <code>utm_campaign</code>.
Product Views – Number of times a product was viewed on a product card from Google Analytics.
Added to Cart – Number of times a product was added to a cart from Google Analytics.
E-commerce Purchases – Number of purchases recorded in Google Analytics.
GA Purchase Revenue – Total gross order value including shipping from Google Analytics, not reflecting exact order totals from the store.</div>

Table Data-driven attribution

Table presents key metrics for the selected period, allowing comparison with the previous period along with a color-coded highlight of the difference.
Data source in Google Analytics can be passed in three ways:UTM parameters – Adding utm_source, utm_medium, utm_campaign parameters to store links.

Google Ads auto tagging – Adds UTM parameters to Google Ads URLs, where the medium parameter is “cpc” and the campaign parameter is determined based on the Google Ads campaign name.

Referral – When a user enters the store from another site without UTM, the source is the site address and the medium is “referral”.

Source – Informs what source the user came to the store from, e.g. utm_source = “google”.
Medium – Specifies the medium from which the user came, using utm_medium.
Campaign – Specifies the campaign from which the traffic came, using utm_campaign.
Conversions – Number of conversions in Google Analytics, it is recommended to mark a purchase as a conversion.
GA Revenue – Total order value recorded in Google Analytics, regardless of order status.

Table Most frequently purchased

Table presents key metrics for the selected period, with the option to compare to the previous one, along with a color-coded difference.
Market – Indicates which store or market the product comes from.
ID – Unique product identifier in the store system.
Product name – Unique product name, including variants, assigned to the identifier.
Net revenue – Information on revenue without VAT, applies to orders completed and in progress.
Number of orders – Number of orders completed and in progress in the store system.
Number of ordered items – Number of ordered items in completed and in progress orders.
Average discount percentage – Percentage difference between the regular price and the purchase price in orders completed and in progress.

Table Best deals

Table presents key metrics for the selected period, with the option to compare to the previous one, along with a color-coded difference.
Market – Indicates which store or market the product comes from.
ID – Unique product identifier in the store system.
Product name – Unique product name and its variants, assigned to the identifier.
Average discount percentage – Percentage difference between the regular price and the purchase price without additional discounts.
Number of products viewed – Number of “view_item” events from Google Analytics, recorded when the user views the product page.
Number of orders – Number of orders fulfilled and in progress in the store system.
Number of ordered items – Number of ordered items of a given product in orders fulfilled and in progress.
Revenue – Revenue excluding VAT, relating only to orders completed and in progress.

Table The most interesting

Table presents key metrics and allows you to compare data to the previous period, with the difference highlighted in color.
Market – Information about the store or market from which the product comes.
ID – The unique identifier of the product in the store system.
Product name – The unique name of the product, along with its variants, assigned to the identifier.
Net revenue – Revenue excluding VAT, relating only to orders fulfilled and in progress.
Number of products viewed – The number of “view_item” events from Google Analytics, recorded when interacting with the product.
Number of adds to cart – The number of “add_to_cart” events from Google Analytics, recorded when users add a product to the cart.
Add to cart rate – A metric calculated by dividing the number of times a product is added to a cart by the number of times it is viewed.

Table Product prices as of

Table presents metrics and data for the selected period, with the possibility of comparison to the previous period and a color-coded difference marker.
Market – Information about the store or market from which the product comes.
ID – A unique product identifier in the store system.
Product name – The name of the product along with its variants, assigned to the identifier.
Price – The current price of the product, as displayed on the product card.
Revenue from the day – Daily revenue from the store system excluding VAT, only for products from orders fulfilled and in progress.

Table Gross price history for the last 7 days

Table presents metrics and data for the selected period, with the possibility of comparison to the previous period and with a color-coded difference.
Market – Information about the store or market from which the product comes.
ID – Unique product identifier in the store system.
Product name – Name of the product along with its variants, assigned to the identifier.
Daily date – Price of the product on a given day, as displayed on the product card.

Chart Net sales

The chart shows Net Revenue only from orders with a discount granted. Net revenue only applies to orders with the status fulfilled and in progress for a given period from the store system.

Wykres Average feed discount

The chart presents the percentage difference between the regular price of products in the store’s assortment and the price at which the product can be purchased in the store on given days of the period.

Table Daily discount and sales information

Sales after discount – Information from the store system about revenues without VAT for discounted orders. The presented revenue applies only to orders with the status completed and in progress.
Number of orders – The number of all orders with the status completed and in progress from the store system.
Number of orders with discounts – The number of orders discounted only with the status completed and in progress from the store system.
Percentage total discount – The percentage difference between the regular price in the product feed and the price at which the products were purchased with additional discounts or coupons.
Number of orders with coupons – The number of orders in which a discount coupon was used. Orders only with the status fulfilled and in progress from the store system.
Percentage discount coupons – The percentage difference between the regular price in the product feed and the price at which the products were purchased, only for purchases in which a discount coupon was used.
Average discount in the feed – The percentage difference between the regular price in the feed and the price at which the product can be purchased in the store without additional discounts or coupons in the selected period.

Chart Shopping funnel

Sessions – Number of “session_start” events. A session is the time during which a user, as a unique identifier, interacts with the store. A session starts when a user opens the store page when no session is active (e.g. due to the previous session timeout). By default, a session ends (times out) after 30 minutes of user inactivity. There is no limit to the length of a session.
Product views – Number of “view_item” events. The event should be sent to Google Analytics every time a user opens a product page, changes its variant, size, or color on the product page, or composes a set of products sold under a single product identifier.
Added to cart – Number of “add_to_cart” events. The event should be sent to Google Analytics every time a user adds a product to the cart through an action, e.g. clicking. Adding a product to the cart in many cases can occur not only from the product page, but also from the category page, section page, or even the home page, or the cart itself by increasing the number of products in the cart.
Payment starts – Number of “add_payment_info” events. The event should be sent to Google Analytics every time the user selects a payment method through their activity in the purchasing process.
Orders – Number of “purchase” events. The event should be sent to Google Analytics once after the order confirmation page is displayed. The number of purchases from Google Analytics only shows the total number of orders without verifying the status of these orders and does not present the real number of orders from the store. This is because Google Analytics is only a statistical tool that collects data from devices that have agreed to cookies or when data is transferred in accordance with the GDPR if data transfer under Modeled Behavioral is set correctly. The number of orders from Google Analytics with unknown status will never be equal to the number of purchases with the order status completed or in progress from the store data.
Percentage to previous – Information about the percentage of a given step to the immediately preceding step in the funnel.
Percentage to first – Information about the percentage of a given step to the first step in the funnel.
Percentage to period – Information about the percentage of a given step to the same step in the preceding period.

Table Google Analytics Data

The table presents data on what events and in what numbers occurred in the store, divided into specific sources, mediums and campaigns of traffic on the site.

Information about the Source, Medium and Campaign can be transferred to Google Analytics in three ways:

Through UTM parameters, i.e. adding the parameters utm_source, utm_medium, utm_campaign to the store links.
Through Google Ads automatic tagging – Google Ads automatic tagging is a function that allows you to track Google Ads campaigns in Google Analytics. This function automatically adds UTM parameters to the URLs of Google Ads ads. In the case of Google Ads automatic tagging, the medium parameter takes the value “cpc” (i.e. – cost per click) and the Campaign parameter is determined based on the Google Ads campaign from which the user comes. For example, if a user came to a website from a Google Ads ad whose campaign name is “spring_campaign”, the value of the campaign parameter will be “spring_campaign”.
Through referring pages, so-called referrals, which can pass the source and medium parameters. – When a user enters the store from another page through a link placed on it without UTM parameters, the source will indicate the address of the page from which the user came to the store, and the medium will be indicated as “referral”.

Source – A parameter informing about which advertising source or page the user came to the store from. In the case of the source parameter, you can use the UTM parameter called utm_source, which is used to determine the source of traffic. For example, if the utm_source parameter has the value “google”, the source will be “google”.
Medium – A parameter informing about which advertising medium the user came to the store from. In the case of the medium parameter, you can use the UTM parameter called utm_medium.
Campaign – A parameter informing about the advertising campaign from which the user came to the store. In the case of the campaign parameter, you can use the UTM parameter called utm_campaign.
Event – The name of the event from Google Analytics according to the GA documentation or the custom configuration of triggering events on the store page.
Number of events – The total number of events per event name

Chart Number of orders by customer type

Orders Per Day Chart – Presents the number of orders per day for the selected period, divided by customer type.

Store Data – Number of orders from the store systems (from selected markets), applies only to orders completed and in progress.

Customer – Defined by a unique phone number or email address (if no phone) provided during the order.

New Customer – First purchase made to a unique number or email, or a purchase after a break of more than a year since the previous purchase.

Returning Customer – A customer who places another order to the same number or email, if the break between orders does not exceed 365 days.

Second Purchase – Second order placed by the same customer within 365 days.

Chart does not present data from Google Analytics, only full revenue data from the store systems.

Chart Revenue by customer type

Net Revenue Per Day Chart – Presents net revenue per day for the selected period, divided by customer type.
Store Data – Net revenue from store systems (from selected markets), applies only to orders completed and in progress.
Customer – Specified by a unique phone number or email address provided during the order.
New Customer – First purchase to a unique number or email, or purchase after a break of more than a year.
Returning Customer – A customer who places another order to the same number or email, if the break between orders does not exceed 365 days.
Second Purchase – Second order placed by the same customer within 365 days.
Note: The chart does not use Google Analytics data, only full revenue data from store systems.

Table Data on the days of the week for a given customer type

Day of the week – Data is aggregated and presented from the last day of the week of the selected period. It is recommended to select full weeks, i.e. periods multiple of 7 days, for correct data reading.
Number of customers – Number of unique phone numbers or email addresses provided during the order.
Net revenue – Revenues excluding VAT from the store system, regarding orders completed and in progress.
Average revenue from the day – Average revenues excluding VAT for a given day of the week, regarding orders completed and in progress. When selecting a period longer than a week, the data is averaged.
Average net basket – Average revenue excluding VAT per order, regarding orders completed and in progress.
Number of orders – Number of orders completed and in progress from the store system. Average number of orders – The average number of orders completed and in progress from the store system, given for the last 7 days. The number changes and is averaged when a longer period is selected.

Table Most frequently purchased products for a given customer type

Market – Shows the store or market where the product comes from.
ID – Unique product identifier in the store system.
Product name – Unique product name and its variants, assigned to the identifier.
Total product revenue – Revenue excluding VAT for the product on a given day, concerning only completed and in-process orders.
Number of orders – Number of completed and in-process orders from the store system.
Number of ordered items – Number of items of a given product ordered in completed and in-process orders.

Table Second purchase

Market – Information about the store or market from which the product comes.
ID – Unique product identifier in the store system.
Product name – Product name with its variants, assigned to the identifier.
Total product revenue – Revenue excluding VAT from second purchases for the product on a given day, regarding orders completed and in progress.
Number of orders – Number of second orders per user, completed and in progress.
Number of ordered items – Number of product items ordered from second orders, completed and in progress.

Table Payments

Table presents metrics and data for the selected period, with the option to compare to the previous period and a color-coded difference marker.
Payment method – Types of payment methods available in the store, according to data from the store system.
Number of orders – Number of orders completed and in progress from the store system.

Table Deliveries

Table presents metrics and data for the selected period, with the possibility of comparison to the previous period and a color-coded difference.
Delivery method – Types of delivery methods available in the store, according to data from the store system.
Delivery type – Information whether the delivery was free or paid for by the customer.
Number of orders – Number of orders completed and in progress from the store system.
Percentage share – Percentage share of a given delivery method in all orders in a given period.
Fee cost – Total costs incurred by customers for a given type of delivery.
Revenue – Revenue excluding VAT from completed and in progress orders.

Simple and without technical knowledge

Your data ready in 1 day! 🚀

Thanks to our proprietary technology, experience and cloud computing, in 1 day you will independently connect your data to DataOrganizer.

You do not need technical knowledge or knowledge of databases. We will guide you through the entire process of launching and connecting information. Without learning technology and without hours spent studying documentation, you will start collecting and reporting your data.

Key benefits of DataOrganizer 🙌

Discover the benefits of fast analytics, automation, better customer understanding, marketing optimization, and full control over store performance.

Analysis and reports

Szybko analizuj dane e-commerce i otrzymuj gotowe raporty i tabele.

Data processing

Process large volumes of data by combining revenues and costs and organize information in the cloud.

Automation and BI

Automate reports and use built-in BI tools.

Customer Habits

Learn about customer habits and analyze product data to make better decisions.

Marketing optimization

Optimize your store marketing and increase sales with Datadiary.

Data history

Build a history of your data while having full control over your store's performance.

Check out the features 🎯

Data in the Cloud

We use Google Cloud Platform (GCP) to store and process data, ensuring the highest security standards. Data is encrypted and monitored 24/7, which guarantees full control and protection.

AI Chat

Chat AI in DataOrganizer combines data from various e-commerce systems, enabling advanced analysis and optimization of activities. It offers instant insights, integrates advertising expenditure with sales results, measures ROI, enables advanced filtering and sorting of data, and analyzes global market trends.

Any Date Range

DataOrganizer reports support long-term planning and forecasting. By analyzing historical data, companies can better predict future trends and adapt their strategies to changing market conditions.

Advanced Filtering and Sorting

DataOrganizer offers advanced filtering and sorting features that enable precise data management. With these options, you can quickly find and analyze key metrics, customizing data views to your needs.