This guide will walk you through creating your first chart, step by step. You’ll learn how to prepare your data and turn it into clear, effective visualizations to share your insights.
- Log in to your SKALE Enterprise Platform account.
- Hover over the left side panel and select Data Analytics.
- Select a Data Tab.
What are Data Tabs?
These Data Tabs offer a detailed breakdown of your campaign’s performance, with each tab highlighting specific data sets. This allows you to track key metrics, analyze user behavior, and uncover valuable insights to optimize your strategies.
What are the available Data Tabs?
| Data Tab | Explanation |
| Generic | It provides a comprehensive overview of user information, including demographics, behavior, and engagement. |
| Event | It tracks specific user actions and interactions within the campaign. |
| Vouchers | It tracks tracks the creation, distribution, and redemption of vouchers. |
| Spin Wheel | It tracks user interactions with spin wheel games, including spins, rewards won, and user demographics. |
| Challenges | It tracks user participation in challenges, including challenge completion rates, rewards earned, and user demographics. |
| Receipts | It tracks user-uploaded receipts, including purchase information and reward claims. |
4. Select a Data Set.
What are Data Sets?
Data Sets are targeted collections of data points within a larger data tab, each highlighting a specific aspect of user behavior or campaign performance to enable detailed analysis.
What are the available Data Sets per Data Tab?
Generic Data Sets
| Generic Data Sets | Explanation |
| Users | These are data on individual users, including demographics and registration details. |
| User Sessions | These are data on user sessions, including duration and frequency. |
| Daily Check-ins | These are data on user daily activity and engagement. |
| Referrals | These are data on users who were referred by other existing users. |
| Exclusive Rewards | These are data on users who have claimed exclusive rewards. |
| QR Scans | These are data on QR code scans and user interactions. |
| Point Transactions | These are data on points earned and redeemed by users. |
| Chance Transactions | These are data on user participation in chance-based activities. |
Event Data Sets
| Event Data Sets | Explanation |
| Event | These are data on user interactions with your campaign. Learn more about Events here. |
| In-Game Action Event | These are data on user interactions within the campaign or game. |
Vouchers Data Sets
| Vouchers Data Sets | Explanation |
| Users | These are data on the user demographics and their voucher download details. |
| Voucher Series | These are data on the different voucher series or batches that have been created. |
| Downloads | These are data on voucher downloads such as who downloaded the voucher, the date of download, and the voucher series. |
| Transactions | These are data on voucher redemptions such as who redeemed the voucher, the date of redemption, the amount of the discount or reward, and the store where the voucher was redeemed. |
Spin Wheel Data Sets
| Spin Wheel Data Sets | Explanation |
| Rewards | These are data on the rewards that can be won on the spin wheel. This includes information such as the reward name, description, type, spin dates, and more. |
| Users | These are data on the users who have spun the wheel. This includes information such as user ID, name, email, and mobile number. |
| In-Game Activity | These are data on user interactions with the spin wheel. This includes information such as the number of spins, points won, the time spent on the spin wheel, and more. |
| Receipts | These are data on receipts uploaded by users to claim rewards. This includes information such as the receipt image, the amount spent, and the reward claimed. |
Challenge Data Set
| Challenge Data Set | Explanation |
| Users | These are data on the users who have participated in the challenge. This includes information such as user ID, name, email, and mobile number. |
Receipts Data Sets
| Receipts Data Sets | Explanation |
| Receipts | These are data on the receipts uploaded by users. This includes information such as the receipt ID, upload date, and user ID. |
| Products | These are data on the products purchased by users and claimed as part of the receipt submission process. This includes information such as the SKU name, brand, and price. |
5. Skip the Select View Columns and Data Filter.
Why can I skip the fifth step?
If you’re looking for a quick overview of your data without diving into specific details, skipping the “Select View Columns” and “Data Filter” steps can save you time.
6. Select the Create a View from the dropdown menu.
7. Provide a title and description for your chart.
8. Drag the columns you want from the available list and drop them:
- Under the “Count” column to display them as rows.
- Beside the “Count” column to display them as columns.
Remember: The hierarchy of the columns you drag and drop will affect how the data is grouped and displayed.
For example:
If you drag Event under Goal, the data will be grouped by Goal.
Within each Goal, you will see the count of different Events.
If you drag Goal under Event, the data will be grouped by Event.
You might see the same Goal repeated across different Events.
9. Optional: Customize your Data Display.
How can I customize my Data Display?
You can do this by selecting different aggregation functions for your columns from the Count dropdown menu.
For Example: If you add the “User UID” column, you can change the aggregation from “Count” to “Count Unique Values” to see the number of unique users.
What are the available Data Display options?
| Data Display | Best Used To: |
| Count | Count the number of occurrences of a specific value. |
| Count Unique Values | Count the number of distinct values in a given column. |
| List Unique Values | Display a list of all unique values in a column. |
| Sum | Calculate the total sum of numerical values in a column. |
| Integer Sum | Calculate the sum of integer values in a column. |
| Average | Calculate the average value of numerical values in a column. |
| Median | Calculate the middle value in a sorted list of numerical values. |
| Sample Variance | Measure how spread out the data is from the mean. |
| Sample Standard Deviation | Measure the amount of variation or dispersion of a set of values. |
| Minimum | Find the smallest value in a column. |
| Maximum | Find the largest value in a column. |
| First | Select the first value in a sorted list. |
| Last | Select the last value in a sorted list. |
| Sum over Sum | Calculate the ratio of two sums, often used to compare proportions or rates. |
| 80% Upper Bound | Calculate the value below which 80% of the data falls. |
| 80% Lower Bound | Calculate the value above which 20% of the data falls. |
10. Optional: Customize your charts.
What are the available chart views?
Table: It is best used to view data in tabular format.
Table Barchart: It is best used to combine table and bar chart for visual representation of data.
Heatmap: It is best used to visualize data intensity using color-coded cells.
Row Heatmap: It is similar to a heatmap, but with rows representing data points.
Col Heatmap: It is similar to a heatmap, but with columns representing data points.
Horizontal Bar Chart: It is best used to visualize data using horizontal bars.
Horizontal Stacked Bar Chart: It is best used to compare multiple categories within each bar.
Bar Chart: It is best used to visual data using vertical bars.
Stacked Bar Chart: It is best used to compare multiple categories within each bar vertically.
Line Chart: It is best used to visualize trends and patterns over time.
Area Chart: It is best used to visualize trends and patterns over time while highlighting the area under the curve.
Scatter Chart: It is best used to visualize the relationship between two variables.
TSV Export: It is best used to export data in a tab-separated value format for further analysis.
How do I choose the right chart type for my data?
The choice of chart type depends on the type of data you want to visualize and the insights you want to gain. Here are some general guidelines:
- Scatter Plots: Ideal for identifying relationships between two numerical variables.
- Heatmaps: Useful for visualizing large datasets with color-coded cells.
- Bar Charts: Best for comparing categorical data.
- Line Charts: Ideal for visualizing trends over time.
10. Click the Save this View button in the upper-right corner to save your chart.
