Conversion
Conversion analysis helps you understand how well your app is turning installs, trials, and other engagements into paying users. This feature enables you to track and optimize key user milestones across different stages of the user lifecycle.
By using conversion data, you can uncover answers to important insights such as:
How do conversion rates evolve over time?
This helps you identify patterns, seasonal trends, and the impact of new updates or features.
What role do marketing activities play in improving conversions?
Track how specific campaigns or changes in your app affect user behavior and conversion rates.
Which regions show the best conversion performance?
Analyze regional differences in conversion rates to identify markets with the highest growth potential.
What types of products generate the highest conversions?
Find out which products drive the most conversions over time, enabling you to focus on the best-performing offerings.
These insights allow you to refine your user journey and optimize your strategies for higher conversion rates and revenue.
Why Conversion Analytics Matter
Conversion analytics allow you to monitor how well your app turns installs, trials, and other engagement into paying users. These insights help identify where users drop off and where to optimize the user experience for higher conversion rates. Understanding conversion rates at every stage can help you optimize marketing strategies, product offerings, and user engagement tactics.
Main Controls and Charts
Conversion analysis goes beyond tracking revenue. It helps you visualize how your business operates at different financial scales over time, highlighting how marketing, product updates, and external events impact user behavior. The conversion chart is a vital tool for this.
Conversion Milestones
The main steps of conversion are tracked, starting with Install -> Trial, Install -> Paid, Paid -> 2nd Period, and continuing across different periods, such as 2nd to 3rd, 3rd to 4th, and so on.
Conversion Calculation
For each conversion milestone (A -> B), the conversion rate is calculated based on the number of users who activated the opportunity to convert to the Y stage on the selected date, divided by those who actually converted. The formula is: Conversion = (A / B) * 100%
Example: Install -> Paid
If you had 100 installs on a given date and 20 users made a payment that week, the conversion would be (20 / 100) * 100% = 20%.
Example: Trial -> Paid
If you had 100 trials on a specific day and 30 users converted to paid subscriptions later, the conversion would be (30 / 100) * 100% = 30%.
Time Period and Grouping
You can use the date picker to select the time range you want to analyze, such as daily, weekly, or monthly. The chart displays conversion rates for each period, showing how they evolve over time. You can also group the data by product, country, store, or other factors.
Conversion Insights and Opportunities
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Audience Behavior
Analyzing conversion data helps identify how well different user segments are performing. For instance, by examining conversion rates by country or product, you can uncover which markets or products have the highest potential and tailor your strategies accordingly. -
Product Performance
Conversion rates can reveal how well your products are performing. A high conversion rate may indicate a popular product, while a low rate might suggest the need for improvements. This helps guide product development and marketing focus. -
Marketing Attribution
Conversions allow you to understand how your marketing efforts translate into revenue. Whether it's a seasonal campaign, a new feature launch, or a change in store listings, conversion data helps you measure the effectiveness of these actions.
Curves, Table View, Filters, and CSV Export
Curves and Table View
The core of conversion analysis is the chart, which shows how conversion rates evolve over time. You can compare different metrics (e.g., Install -> Paid, Trial -> Paid) by using different curves on the chart. Below the chart, the table view provides a detailed breakdown of the data. When you hover over a column in the table, you'll see a pop-up summary with the corresponding data on the chart.
Filters and Grouping
You can apply filters to segment the data by product type, country, store, and more. This allows for deeper insights into which factors affect your conversions. You can also group the data to analyze performance in specific regions, for different products, or for particular marketing campaigns.
CSV Export
On the right of the control panel, there's a CSV export button that lets you download the data for further analysis. You can open the CSV in Excel, Google Sheets, or import it into your own system for additional reporting or forecasting.