# Analytics Source/Medium + Ad Cost
# Introduction
Data collection is an invaluable way to get a complete picture of your business. The more data, the more difficult it is to collect, store, process and obtain useful information. Our tool solves this problem with an automated data collection process based on security, completeness and monitoring. Below you can familiarize yourself with the results of the work of our tool, such as the report GA Source/Medium + Ad Cost
# What opportunities does this report offer you?
- Linking data from Google Analytics with cost data
- A report with all the dates for the morning coffee
- Time savings due to automatic processes
- Transparent form of data presentation
- We automatically convert currencies from different accounts to a common currency
- The ability to share with other colleagues in the organization
- Adding your own calculation fields
- You’ll see what you lose and what you gain
# What do you find in this report?
- Answers to important questions tailored to your company
- Useful business indicators including ERS, ROAS
- Information on the current and historical performance of the company
- Information about user behaviour in different marketing channels
- Information on the effectiveness of marketing campaigns
Below you can see what your report might look like!
To make it even easier for you to understand what your options are with our report and what you can find in it, we've put together a detailed tutorial with you in mind:
Demo Report (opens new window) which will allow you to test our report against the data you are interested in at a time you specify.
Blog link (opens new window) here you will find a detailed description of the report along with examples and instructions on how to calculate the metrics you are interested in.
# List of necessary and optional collectors to create a report.
Necessary to create a report:
- Google Analytics Link (opens new window) or WitCloud Stream
Optional collectors:
- Google Ads Link (opens new window)
- Facebook Ads Link (opens new window)
- RTB House Link (opens new window)
- Optimize link (opens new window)
- Awin link (opens new window)
- Domodi & Allani Link (opens new window)
- Convertiser link (opens new window)
- TikTok Link (opens new window)
- Ceneo Link (opens new window)
- Criteo Link (opens new window)
- Custom Data Link (opens new window)
# Data schema
- List of metrics and dimensions in the table
Hide out for the data schema
| name | type | dataStudio/description |
|---|---|---|
| data_source_type | STRING | Type of data source e.g Ecommerce, Ad systems, User behaviour |
| data_source_subtype | STRING | Second type of data source e.g Magento, Analytics, Facebook, Tradedoubler |
| data_source_name | STRING | Name of your WitCloud resource |
| date | STRING | Date |
| channel | STRING | Channel |
| source_medium | STRING | Analytics source/medium |
| source | STRING | Analytics source |
| medium | STRING | Analytics medium |
| campaign | STRING | Analytics campaign |
| ad_content | STRING | Analytics ad Content |
| keyword | STRING | Analytics keyword |
| country | STRING | Analytics country |
| region | STRING | Analytics region |
| city | STRING | Analytics city |
| device | STRING | Analytics device |
| details | INTEGER | Analytics sessions with product details |
| add_to_cart | INTEGER | Analytics sessions with add to cart |
| remove_from_cart | INTEGER | Analytics sessions with remove from cart |
| purchase | INTEGER | Analytics sessions with purchase |
| checkout | INTEGER | Analytics sessions with checkout |
| transactions | INTEGER | Analytics transactions count |
| transaction_revenue | FLOAT | Analytics revenue from transactions (tax and shipping included) |
| original_transaction_revenue | FLOAT | Analytics revenue from transactions (tax and shipping included) before currency conversion |
| product_revenue | FLOAT | Analytics revenue from products (tax and shipping excluded) |
| original_product_revenue | FLOAT | Analytics revenue from products (tax and shipping excluded) before currency conversion |
| shipping_value | FLOAT | Analytics shipping value |
| original_shipping_value | FLOAT | Analytics shipping value before currency conversion |
| tax_value | FLOAT | Analytics tax value |
| original_tax_value | FLOAT | Analytics tax value before currency conversion |
| sessions | INTEGER | Analytics sessions |
| page_views | INTEGER | Analytics page views |
| bounces | INTEGER | Analytics bounces |
| users | INTEGER | Analytics users |
| new_users | INTEGER | Analytics new users |
| time_on_site | INTEGER | Analytics time on site |
| costs | FLOAT | Ad system cost |
| original_costs | FLOAT | Ad system cost before currency conversion |
| clicks | INTEGER | Ad system clicks |
| impressions | INTEGER | Ad system impressions |
| ad_system_conversions | FLOAT | Ad system conversions |
| ad_system_conversion_value | FLOAT | Ad system conversion value |
| original_ad_system_conversion_value | FLOAT | Ad system conversion value before currency conversion |
| account_id | STRING | Ad system account id |
| account_name | STRING | Ad system account name |
| campaign_id | STRING | Ad system campaign id |
| campaign_name | STRING | Ad system campaign name |
| ad_id | STRING | Ad system ad id |
| ad_name | STRING | Ad system ad name |
| publisher_id | STRING | Ad system publisher id |
| publisher_name | STRING | Ad system publisher name |
| placement | STRING | Ad system placement |
| currency | STRING | Currency |
| report_currency | STRING | Report currency |
- List of calculation fields configured in the Data Studio template
Hide out for the data schema
| id | name | formula |
|---|---|---|
| cost_per_session | cost_per_session | SUM(costs) / SUM(sessions) |
| cr | cr | SUM(purchase)/SUM(sessions) |
| ers_gros | ers_gros | SUM(costs) / SUM(transaction_revenue) |
| ers_net | ers_net | SUM(costs) / SUM(transaction_revenue - tax_value) |
| no_checkout | no_checkout | 1 - SUM(checkout) / SUM(details) |
| no_details | no_details | 1 - SUM(details) / SUM(sessions) |
| no_purchase | no_purchase | 1 - SUM(purchase) / SUM(checkout) |
| roas_net | roas_net | SUM(transaction_revenue - tax_value) / SUM(costs) |
| roas_gros | roas_gros | SUM(transaction_revenue) / SUM(costs) |
| avg_session_duration | avg_session_duration | sum(time_on_site)/SUM(sessions)/1000 |
| bounce_rate | bounce_rate | SUM(bounces)/SUM(sessions) |
| page_session | page_session | SUM(page_views)/SUM(sessions) |
| revenue_net | revenue_net | SUM(transaction_revenue) - sum(tax_value) |
# Instructions for configuring the report
To create a report, you must first:
- Register on our platform Witcloud (opens new window)
TIP
If you don’t have a WitCloud account yet or need information on how to log in, you can find the instructions here (opens new window).
- After logging in, select the button Smart Data in the left pane.
- Select Reports from the drop-down list. You will be taken to a section where you can create a new report.
- To do so, click on the button “Add new report” at the top left, which will take you to a page with a list of available reports. Select the report Analytics Source/Medium + Ad Cost
- To create your report, you must have created the necessary Collect and then click on the “Create your own report” button. If you receive the following message, you have not set up the required collectu. You have to create it.
In the next step, you will be taken to a section where the following fields are required to be completed:
Report name - under this name you will find your report in our platform.
After filling in the above fields, click on the Next button
In the next step, you specify the period for which the historical data should be downloaded. Click on the “create” button to complete the creation of your report.
# Visualization
To get the visualization of the data in our proposed Data Studio tool, select the button “Link to template” in the Report Draft section, which will take you to the Studio date where you need to enter your login data for Witcloud.
The first step is to select your project Witcloud.
After clicking on “Next”, select your report.
To complete the configuration of the data visualization in the upper right corner, click the “Connect” button and then “Create Report” button. The data for the period you set is loaded into a table in BigQuery, which is updated every hour. Read more about this in the [Autoworkflow] section.
If you want to visualize the collected data in a tool other than Data Studio, you have the option. You can do this with a program of your choice, provided it connects to BigQuery. To do this, select the “Link to table” button in the Draft Report section, which will take you to the table in BigQuery.