In a previous update, we introduced trend analysis for unique sessions and unique users in the Events Analytics section. Building on that foundation, we’ve now added a new set of trend options focused on the aggregate values of event properties. These enhancements allow you to gain deeper insights into numerical data and identify meaningful patterns across user interactions.
To use these new trend options, navigate to the Analytics > Events. Select your preferred date range and choose an event you wish to analyze. You can also include specific attributes if needed. Next, click on the Select Trends dropdown. From here, you can choose from various aggregation options to filter and analyze integer attributes of the event data.

For example If you want to know the total price of items added to your cart in the past week, you can choose the “Last 7 days” from the date filter, select the ‘Add to Cart’ event, pick ‘Sum of Property’ as your aggregate option, and set the attribute value to price.
In the select trends dropdown we have the following aggregate options:
Sum of property: As defined in the example above, this property determines the total numeric value of a property across all event instances.
Average of property: This helps you determine the average numeric value of a property across all event instances. For instance, you could analyze the Purchase Completed event and select the Average of Property trend for the Order Value property. This would reveal the average spend per transaction.
Minimum of property: This allows you to identify the lowest value recorded for a specific property. For example, if you’re tracking the Product Purchased event and apply Minimum of Property to the Discount Applied property, you’ll see the smallest discount value that was given on any purchase during the selected period.
Maximum of property: This highlights the highest recorded value for a numeric property. You could use this to track the most expensive item added to cart by selecting Add to Cart as the event and Item Price as the property.
Median of property: This option is useful for identifying the middle value in a dataset, which can be more accurate than the average when data contains outliers. For example, analyzing the Transaction Completed event with the Median of Property for Transaction Amount will show you the typical transaction size, excluding the effect of very large or very small values.
Percentiles: This option lets you understand how your numeric values are distributed. For instance, using the Loan Application Submitted event and selecting 90th Percentile for Loan Amount will reveal the value below which 90% of the loan applications fall—helpful for spotting high-end trends.
Distinct count: This option calculates the number of unique values for a given property. For example, selecting the Product Viewed event and applying Distinct Count on Product ID will show how many unique products were viewed in the selected time period.
These aggregate trend options bring a new level of flexibility and precision to event analytics, empowering you to analyze user behavior and product interaction through data-rich insights.