- Commerce Intelligence User Guide
- Commerce Intelligence Introduction
- Getting Started
- Administrator
- Analyze Data
- Data Analyst
- Data Warehouse Manager
- Introduction
- Advanced Calculated Column Types
- Building Google Ecommerce dimensions
- Calculated Column Types
- Configuring Replication Methods
- Configuring Data Rechecks
- Changing a metric’s operational table
- Creating and Using Data Warehouse Views
- Creating / Deleting paths for calculated columns
- Creating / Using a SQL Calculated Column
- Creating calculated columns
- Data and Updates Information
- Guest orders
- How Commerce Stores Data
- Entity Relationship Diagrams
- Managing data dimensions in metrics
- MongoDB data modeling guide
- Replicating Google Analytics channels
- Standardizing data with mapping tables
- Translating SQL queries into Commerce Intelligence reports
- Understanding and Evaluating Table Relationships
- Using the Date Difference Calculated
- Using Dashboard Wide Filtering
- Using the Event Number Calculated Column
- Using the Sequential Comparison Calculated Column
- Common Commerce Tables
- SQL Report Builder
- Using the Cohort Report Builder
- Using the Cohort Report Builder for Non-Date Based Cohorts
- Creating a qualitative cohort analysis
- Explore special filter operators
- Export the results of my query
- Using Formulas in the [Report Builder]
- Create Google Analytics charts
- Importance of the Lifetime Revenue Cohort Analysis
- Ordering data using the Show Top/Bottom feature
- Using the SQL Report Builder
- First purchase report
- Understanding the Repeat Order Probability Report
- Auditing Metrics using the SQL Report Builder
- Differences in Columns Between SQL and Data Warehouse Manager
- Connecting Data
- SaaS Integrations
- SaaS Integrations
- Understand Results Between Database and SQL Editor
- Connecting Adobe Analytics
- Expected Adobe Analytics Data
- Connecting Facebook Ads
- Expected Facebook Ads data
- Connecting Google Adwords
- Expected Google Adword data
- Auditing Google Adwords data
- Connecting Google Analytics Warehoused
- Expected Google Analytics Warehoused Data
- Connecting Google Analytics
- Expected Google Analytics data
- Connecting Google ECommerce
- Expected Google ECommerce data
- Connecting Mixpanel
- Expected Mixpanel data
- Data Validation in Mixpanel
- Connecting PrestaShop
- Connecting Quickbooks
- Expected Quickbooks data
- Connecting Salesforce
- Expected Salesforce data
- Connecting Spree
- Expected Spree Data
- Connecting Stripe
- Expected Stripe data
- Connecting WooCommerce
- Connecting Zendesk
- Expected Zendesk data
- Analyzing Zendesk data
- Auditing Zendesk data
- Database Integrations
- Connecting Amazon RDS
- Connecting Databases via VPN
- Connect Your MySQL Database to Commerce Intelligence
- Connecting Adobe Commerce
- Expected Commerce Data
- Connecting Microsoft SQL Server
- Connecting MongoDB via SSH Tunnel
- Connecting MySQL via a direct connection
- Connecting MySQL via cPanel
- Connecting MySQL via SSH Tunnel
- Connecting PostgreSQ
- Analyze Campaigns
- Analyze Customers
- Calculating Commerce churn rates
- Defining customer concentration
- Defining customer churn
- Expected Lifetime Value (LTV) analysis (basic)
- Expected Lifetime Value (LTV) analysis (advanced)
- Track User Acquisition Source Data Overview
- Track User Device and Browser Data in your Database
- Analyzing customer repurchasing behavior
- Analyzing Website Activity and Customer Conversion Rates
- Recency, frequency, monetary (RFM) analysis
- Analyze Business Performance
- Tracking goals against actual metrics
- Analyzing returned orders
- Year-over-year, month-over-month, week-over-week
- Analyzing holiday season performance
- Analyzing repeat probability decay and churn
- Understanding and building a basic analytics
- Identifying your most valuable marketing sources and channels
- Understanding Google Analytics UTM attribution
- Analyzing inventory levels
- Reporting a retail calendar
- Forecasting
- Build Reports and Share Data
- Data User
- Reports
- Dashboards
- Create Dashboards
- Out-of-the-box dashboards
- Dashboard Pro
- Importing charts from another user
- Permanently deleting a chart
- Using Dashboard Groups
- Managing Dashboards
- Deleting Dashboards
- Renaming Dashboards
- Setting a default Dashboard
- Adding charts to Dashboards
- Removing charts from Dashboards
- Sizing and arranging charts in a Dashboard
- Bulk-editing charts in Dashboards
- Cloning Dashboards
- Searching for Dashboards
- Sharing Dashboards with other users
- Sharing Dashboards organization-wide
- Accessing shared Dashboards
- Changing access to shared Dashboards
- Leaving (unsharing) a Dashboard
- Sharing Data
- Best Practices
- Working with Data
- Working with data
- UTM tagging in Google Analytics
- Formatting and Importing Financial Data
- Recommended Data Dimensions for Segmentation and Filtering
- Checking the Update Cycle Status
- Reducing Your Update Cycle Time
- Modifying Your Database to Support Incremental Replication
- Optimizing your Database for Analysis
- Optimizing Your SQL Queries
- Understanding your Commerce Intelligence Environment
- Project Organization
- Working with Dashboards
- Working with Data
- Tutorials
Reporting over Time Periods
This topic contains instructions for clients that are using the original architecture and new architecture. You are on the new architecture if you have the Data Warehouse Views section available after selecting Manage Data from the main toolbar.
The report builder allows you to easily see trends over time and change perspective for time periods you may want to compare. This topic demonstrates how to set up a dashboard to go a level deeper to allow you to create reports for week over week, month over month and year over year analysis.
Before getting started, you should review explore perspectives in more detail here and independent time options here.
This analysis contains advanced calculated columns.
Calculated Columns
-
Sales_flat_ordertable -
Original architecture: the below columns are created by an analyst as part of your
[YoY WoW MoM ANALYSIS]ticket -
created_at (month-day) -
created_at (month) -
created_at (day of the month) -
created_at (day of the week) -
created_at (hour of the day) -
New architecture: SQL listed below with a photo of an example for how to create this calculation
created_at (month-day)Calculation: to_char(A, ‘mm-dd’)created_at (month)Calculation: to_char(A, ‘mm-month’)created_at (day of the month)< Calculation: to_char(A, ‘dd’)created_at (day of the week)Calculation: to_char(A, ‘d-Day’)- **
created_at (hour of the day)Calculation: to_char(A, ‘hh24’)
Metrics
None.
Make sure to add all new columns as dimensions to metrics before building new reports.
Reports
-
YoY chart
-
Metric:
Number of orders -
Metric:
Number of orders -
Time options:
Time range (Custom):2 years ago to 1 year ago -
Show top/bottom: Top 100% sorted by
created_at (month-day)*
-
-
Metric
A:This year -
Metric
B:Last year -
Time period:
1 year ago to 0 years ago -
Interval:
None -
Group by:
created_at (month-day) -
Chart Type:
Line -
MoM chart
-
Metric:
Number of orders -
Metric:
Number of orders -
Time options:
Time range (Custom):2 months ago to 1 month ago -
Show top/bottom: Top 100% sorted by
created_at (day of month)*
-
-
Metric
A: This month* -
Metric
B: Last month* -
Time period: one month ago to 0 months ago
-
Interval: None
-
Group by:
created_at (day of month) -
Chart Type: Line
-
WoW chart
-
Metric:
Number of orders -
Metric:
Number of orders -
Time options:
Time range (Custom):2 weeks ago to 1 week ago -
Show top/bottom: Top 100% sorted by
created_at (day of week)
-
-
Metric
A:This week -
Metric
B:Last week -
Time period:
1 week ago to 0 weeks ago -
Interval:
None -
Group by:
created_at (day of week) -
Chart Type:
Line -
DoD chart
-
Metric:
Number of orders -
Metric:
Number of orders -
Time options:
Time range (Custom):2 days ago to 1 day ago -
Show top/bottom: Top 100% sorted by
created_at (hour of day)
-
-
Metric
A:Today -
Metric B:
Yesterday -
Time period:
1 day ago to 0 days ago -
Interval:
None -
Group by:
created_at (hour of day) -
Chart Type:
Line
After compiling all the reports, you can organize them on the dashboard as you desire. The result may look like the image at the top of this page.
Resources
Adobe Account
