- 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
Tracking Goals Against Performance Metrics
Most clients would like to track their business goals, but do not realize this is possible in Adobe Commerce Intelligence. This topic demonstrates how to set up a dashboard that will help you track your business goals against your actual data - including revenue, new registered users, and orders over time. You also learn how to compare year over year performance, all in a dashboard like this:
Before getting started, you should review the file uploader and make sure you have defined your business goals for a given period.
Getting Started
You need to first upload a file containing specific daily/monthly/quarterly targets for your business.
You can use the file uploader and the image below to format your file. The most common targets that clients track in Commerce Intelligence include Orders, Revenue, and New registered accounts.
Metrics
Create one new metric for each target. For example, if you upload monthly revenue and orders targets, you need to create two new metrics:
-
Monthly revenue target
-
In the
Monthly goalstable -
This metric performs a Sum
-
On the
Revenue targetcolumn -
Ordered by the
Monthtimestamp -
Monthly orders target
-
In the
Monthly goalstable -
This metric performs a Sum
-
On the
Orders targetcolumn -
Ordered by the
Monthtimestamp -
Monthly new registered accounts target
-
In the
Monthly goalstable -
This metric performs a Sum
-
On the
New registered accounts targetcolumn -
Ordered by the
Monthtimestamp
Reports
It is helpful to have a mix of static values and visual charts when analyzing your targets. Below are three example reports to get you started tracking your revenue performance.
-
Revenue left to achieve target
-
Metric
A:Revenue -
Metric:
Revenue -
Metric
B:Target Revenue -
Metric:
Monthly Revenue Target -
Formula:
Revenue left to achieve target -
Formula:
(B-A) -
Format:
Number -
Time period: (Whatever relevant time period you want)
-
Interval:
Month -
Chart Type:
Scalar -
Revenue targets
-
Metric
A:Revenue -
Metric:
Revenue -
Metric
B:Target Revenue -
Metric:
Monthly Revenue Target -
Metric
C:Revenue (amount change since previous year)(hide) -
Metric:
Revenue -
Perspective:
Amount change vs. Previous year -
Formula: (This month last year)
-
Formula:
(A-C) -
Format:
Currency -
Turn off
Multiple Y-Axes -
Time period: (Whatever relevant time period you want)*
-
Interval:
Month -
Chart Type:
Line Chart
Once you have completed the above reports for revenue targets, you can create identical reports for goals around orders, registered accounts, or any other values you have included in your goals file upload.
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.
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