Using Insight Analysis

Insight Analysis Usage Tips

This document provides tips for examining your product from various perspectives and analyzing data using Hackle's Insight Analysis.

1. Product Acquisition

Want to check the number of product visits and unique visitors?

Select Any Event in Analysis Items, or a visit event such as 'view home'.

Select the first item as 'Count' and click Add Analysis Item to select the second item as 'User Count'. This lets you view both PV and UV simultaneously.

Want to check the week-over-week trend in the number of new users?

Select the event that measures sign-ups, signup, in Analysis Items.

Select 'User Count' as the calculation method.

Select Weekly as the interval, then choose the desired period (e.g., weekly, 8 weeks).

• Click Compare Period and select vs. Previous Week

Review the query results and change the query period to view the weekly trend in new sign-ups.

Want to check product acquisition channels by marketing channel?

Set the desired event in Analysis Items and select marketing tracking properties (utm source, medium, resource, etc.) in the Group By feature to group items by channel.

View users by utm source

View by specific period with a vertical bar chart.

View share with a pie chart.

Note

• [Analysis Items] and [User Groups] show properties that are being aggregated as shown below.

• If there is data you want to analyze, check in Event Management that the event names and properties for that data are being aggregated! UTM must be coming in as a User property.

2. User Behavior Data

Want to know how often users click on a specific product?

To view clicks on a specific product, check click_product.

Go to Data Analytics > Insight > and configure Analysis Items, User Groups, etc.

• Analysis Items: Set the event name to click_product and the calculation method to Count. This configuration lets you view the click count.

Select the criteria for grouping data in [Group By].

• Group By: select product_name

  • The list inserted as properties of the selected event is shown.

  • You can choose whether to view data by product ID, product name, or category.

As shown below, you can see the product click count by product name and the click count trend over the configured period. You can use this by choosing the query period, interval, or chart type to suit your purpose.

Want to know the number of users who added to cart and completed purchase among those who viewed a product, along with the conversion rate?

1. Go to Data Analytics > Insight > and configure the analysis items.

• Analysis Items: Event for viewing a product (view_product), Event for adding to cart (view_cart)

1. Review the queried data.

• As shown below, you can confirm that on August 4th, approximately 203 users viewed the product detail page and 52 users added items to their cart (approximately 25%).

1. Analyze the data in more detail. Once you have checked the numbers, also view the [conversion rate] for users who [added to cart] or [completed purchase] among those who viewed the product detail page. In Conversion Rate at the bottom of Analysis Items, select [numerator / denominator]. Configured as in the example, you can view the add-to-cart conversion rate.

   • Numerator: Add to Cart / Denominator: View Product Detail

In 30 days, approximately 24% of users who viewed the product detail page added items to their cart.

1. After confirming the average conversion rate and trend, use the Group By feature to check which product has the highest conversion rate.

Group by product name (product_name)

You can check the list of products with the highest conversion rates.

3. Payment and Revenue Data

After selecting the payment event, choose the calculation method to view the following data:

• Selecting 'Count' shows order count (Order)

• Selecting 'User Count' shows number of purchasers (Purchaser)

• Selecting 'Sum' shows revenue (Revenue)

  • For 'Sum', you need to select what to sum; for revenue, select the order amount property, such as value or order_amount, that corresponds to the order amount.

• For 'Average', you need to select the basis: 'Average value' shows Average Order Value (AOV), 'Average count per user' shows purchases per user, and 'Average value per user' shows Average Revenue Per User.

Want to see the payment conversion rate?

• Taking conversions from 'Homepage visit visit' to 'Purchase order_complete' as an example: select 'Count' if the conversion calculation basis is PV, or 'User Count' if it is UV.

• Then select the appropriate events for the numerator and denominator in the conversion section to get the conversion rate automatically.

Want to check order count and revenue at the same time?

First, select the event that tracks purchase completion in Analysis Items. Select the first item as 'Count' and click Add Analysis Item to select the second item as 'Sum'. This lets you view both items simultaneously.

• Want to compare results limited to a specific region?

  • In User Groups, set the first item to Location > Seoul and the second item to Location > Gyungi. This collects only data matching each respective condition for comparison. In this case, changing the chart type to a horizontal bar chart makes it easy to see data broken down by analysis item and user group.

Want to see the top products/categories by total revenue at a glance?

• Using the Group By feature, select a product or category in 'Properties' to view data for all sub-items grouped by that property. In this case, changing the chart type to 'Pie Chart' lets you see the top data at a glance based on the total for the entire period.

Group By product name 'product_name'

Curious about the average payment amount per paying user? (ARPPU)

ARPPU stands for Average Revenue Per Paid User, meaning the average payment amount per paying user.

To view this metric, you need to analyze the average payment amount of paying users. Following these steps one by one makes it easy to query.

1. Select the payment event and calculation method to check ARPPU.

   • Event to analyze: Payment event (order_complete)

   • Calculation method: Average > Average value per active user

   • Property: Payment amount (order_amount)

2. Select paying users.

   • User Group event: Users who triggered order_complete at least once

   • Period: Set desired period (example uses the last 30 days)

1. View data

   • For the last 30 days, you can view the average payment amount (ARPPU) for paying users.

Curious about users' dwell time?

You can easily understand how long users have stayed in your service.

To query this metric, you need to collect the $engagement event that the Hackle SDK automatically collects. Unlike traditional session-based analysis, you can check dwell time in detail and with precision down to the page level!

Following these steps one by one makes it easy to query.

1. Select the event and calculation method to check dwell time.

   • Event to analyze: Dwell time event

   • Calculation method: By user > Average value

   • Property: Desired page name ($page_name)

1. View data

   • For the last 7 days, you can view the average page dwell time for all users who visited that page.