The Analytics page provides essential business metrics for your store, including sessions, sales, orders, and conversion funnel. It also presents other commonly used metrics such as paid amount, refund amount, and sessions by traffic source clearly and intuitively. These metrics can be viewed in real time and analyzed for any specific period.
Here are some specific customer examples:
- Monitor sales for today or a specific time frame, observe changes and trends, and compare with previous periods.
- Analyze traffic composition based on channels, countries/regions, and device types.
- Track changes and trends in average order value and returning customer rate.
- Discover popular items by exploring the top product rankings.
The Analytics page displays the most valuable metrics, allowing you to gain deep insights into store performance and customer behavior. The metrics are presented in numerical format and, where appropriate, can be visualized through charts. Additionally, each metric shows the percentage change relative to the previous date range.
In This Article
Overview of the Analytics Page
To access more detailed data reports, you can click on the metric cards to view report details. For example, you can click the View report button located at the upper right of the Top products card to access the report page. Here, you will find metrics such as sales, percentage of sales, and sessions for top products.
The following are instructions for some basic operations on the Analytics page:
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Navigation: From your SHOPLINE admin panel, click Analytics. By default, it shows data for Today and compares it with yesterday. You can adjust the time frame as needed.
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Adjusting the time window: To view data for different date ranges, click the date input box and select your desired range. You can choose preset ranges like Last 7 days or set a custom range by selecting specific dates from the calendar. This allows you to easily view the data for the desired dates.
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Data comparison: If you want to compare data with the same date range from the previous date or the previous year, select the appropriate date range and value, then click Apply.
- Automatic updates: When you open the Analytics page, you'll see the latest data within approximately 1 minute. If the date range is Today, you can refresh the page manually or tick on the box next to Auto refresh in the top right corner to view the newest data. Metrics related to online store sessions won't be displayed if you don't use an online store channel.
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Customization: The customization feature allows you to arrange the position of cards and determine which ones should be hidden. Click the Customize button to access the card editing page. Here, you can drag cards to different positions and use the close button in the upper right corner to hide specific metrics. Hidden cards are stored in the Metrics library on the left side of the editing page. If necessary, you can easily restore any hidden cards from the library to the Analytics page. It's worth noting that the system will display card positions based on the last saved configuration for your login account.
Introduction to Metric Definitions
Once you've familiarized yourself with the basic operations, you can refer to the following metric definitions to help you understand the metrics:
Metric | Definition |
Sales | It displays the amount of orders successfully placed. This metric applies to orders from all sales channels, including imported orders.
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Paid amount | It displays the total payment received for partially paid and fully paid orders.
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Sessions |
It shows the number of sessions in your online store. This metric is specific to your online store channels. A visitor may have multiple visits. Visitors are counted separately if there has been no activity for 30 minutes or until midnight (UTC). For more information about sessions, please refer to Store Sessions and User Activity. |
Conversion rate |
The percentage of total sessions who completed checkout. This metric is specific to your online store channels.
To make a purchase, visitors need to add products to their online shopping carts and proceed to the checkout page. This is commonly referred to as the conversion funnel, where the number of people decreases at each step.
For example, if a visitor accesses your website at 10:00 AM and visits multiple pages between 10:00 AM and 10:30 AM, the sessions will only be counted as 1 at 10:00 AM.
This number is usually smaller than the total number of store sessions, as some visitors only browse products without adding any items to their shopping carts.
This number is usually smaller than the number of sessions who add items to their carts, as some visitors may add products to their carts but don't proceed to checkout or submit their contact information. In some cases, this number may be higher than the number of visitors who add to the cart, as some visitors may directly access the checkout page (e.g., through a recall link) without clicking the Add to cart button on the product detail page.
This number is typically smaller than that of sessions who completed the checkout, as some visitors may fill in their information but don't proceed with payment or complete their orders.
This number is usually smaller than that of sessions who completed the checkout, as some visitors may not proceed with payment or complete their orders after selecting a shipping method due to high shipping costs or other reasons.
This number is typically smaller than that of sessions who completed the checkout, as some visitors may not proceed with payment or complete their order after providing customer information and adding the shipping method.
This number may not match your total number of orders, as visitors may place multiple orders during one visit. This number is usually smaller than that of added payment info, as some visitors may encounter issues during the payment process and fail to complete the checkout. |
Average order value | It displays the average value of all orders (excluding gift cards).
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Orders |
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Top products |
The best-selling products in your store. The Top products card shows the top five products ranked by sales, including the number of units sold and the conversion rate. Click View report in the card's upper right corner to access product data details and view the sales performance of the top 2,000 products by sales (units sold). |
Sessions by different themes | This feature analyzes the composition of sessions to your online store based on different themes such as region, traffic source, and device type. This metric is specific to your online store channels.
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Top landing pages by sessions |
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Popular referral websites | This card displays the top five referrer sites that generate the most traffic to your store. It presents the top five referrer sites with the most sessions. It shows which websites visitors come from before landing on your store. If you are running ads for your store, these referrer sites are typically media platforms such as facebook.com. Click View report to access detailed reports on all referrer sites. |
Popular sales by different themes | View the composition of sales by different themes, such as referrer sources and social channels.
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Sales attributed to marketing | This card only displays the total sales generated from your marketing efforts. They include marketing campaigns and activities managed through the Marketing section of the SHOPLINE admin panel, as well as external methods utilizing Urchin Tracking Module (UTM) parameters. |
Pageviews |
Total page views for sessions in your store. Visitors are counted separately if there has been no activity for 30 minutes or until midnight (UTC). Since a visitor may view multiple pages, page views are typically higher than the sessions. Example: Visitor A views a product in your store once and then returns to the homepage 10 minutes later. In this case, it will be reported as 2 page views and 1 visitor. |
Refund Amount | The amount for which the order was refunded. It is recorded based on the time when the refund occurs. |
Customer group analysis |
The percentage of customers who returned to your store and made a purchase in the specified period. Customers are grouped by their first order date. For example, if Cindy made her first purchase in your store on February 23, 2023, she would belong to the customer group for February 2023. The system presents a customer retention table based on the repeat purchase behavior of each customer group. For instance, let's say you started operating your store in 2023. In January, you had 100 new customers, and in February, you had 150 new customers. Out of the 100 new customers in January, 13 continued to make repeat purchases in February. Out of the 150 new customers in February, 35 continued to make repeat purchases in March. Based on this example, The month-to-month retention rate for January 2023 is 13/100 = 13%. The month-to-month retention rate for February 2023 is 35/150 = 23.33%. When looking at the data in the summary row, the overall month-to-month retention rate for January and February 2023 is (13+35)/(100+150) = 19.2%. |
Sales from all POS store channels
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It displays the sales of each POS store location, specifically showing the sales from POS channels. If you haven't enabled offline store sales channels, this card will indicate "No Data Available."Sales of all POS stores, only display sales with the channel as POS. |
Returning customer rate | It shows the percentage of customers in your store who have placed multiple orders.
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Frequently Asked Questions
Store Sessions and User Activity
Visitor count statistics are based on sessions, tracked using cookies to monitor the duration of visits. Cookies are small files that are stored in the browser of a customer's device, such as a desktop computer, tablet, or smartphone.
There are two scenarios where updates occur and new sessions are created when customers visit your online store. (1) If there is no activity after 30 minutes of visiting, and (2) at midnight (UTC 0) or when it reaches 0:00 in the store's time zone. Therefore, it is normal for multiple visitors to be generated from a single device.
For example, a customer views products in your store for five minutes and then leaves. If he or she returns within two hours to continue browsing for another 10 minutes, it will be counted as two sessions or two visitors. However, if the customer returns to the store within 30 minutes of their initial visit, it will only be counted as one session or visitor.
Please note that preview visits generated by clicking the eye icon on the right side of Online store will also be included in the count.
For more information on the differences with other analytical tools, please refer to Differences with Other Analytical Tools and Impact of Customer Data Collection Policy on Analysis.
Differences with Other Analytical Tools
There are reasons behind the disparities in statistical results between SHOPLINE and third-party tracking services, such as Google Analytics:
- Inconsistent time zone settings between SHOPLINE and third-party service providers.
- Variances in counting visits and sessions. This requires referring to the metric explanations provided by third-party service providers. For example, Google calculates page loads separately, making it not directly comparable to the sessions offered by SHOPLINE.
- Differences in defining bot traffic. Various algorithms used by different third-party tracking providers to identify bots may differ from SHOPLINE's methods, resulting in discrepancies in session calculations.
- Google relies on JavaScript and cookies to track visitors. However, some customers may have disabled cookies or JavaScript in their browser settings.
- Disparities in the mechanism of recording sessions through cookies, including variations in cookie expiration periods, can also affect session discrepancies.
Impact of Customer Data Collection Policy on Analysis
Cookies are small text files that are stored on a customer's device when they browse a website. Web browsers manage and store these files. They are essential tools for collecting and reporting analytical data, particularly regarding customer behavior on websites, such as page views, visited pages, and clicked links. Cookies can store a significant amount of data and sometimes identify specific customers.
There are laws and regulations in many parts of the world regarding what information can be collected and when it can be collected. The EU General Data Protection Regulation (GDPR) and the ePrivacy Directive are two crucial regulations that dictate how business activities are conducted within the European Union (EU) and the usage of customer data. If you are a merchant operating in the EU, European Economic Area (including all EU countries, Iceland, Liechtenstein, and Norway), the UK, or Switzerland, or if you sell products to customers in these regions, you may already be aware of this issue and have made corresponding adjustments to your customer privacy settings.
If you choose the options Collect data after getting customer’s permission or Collect partial data before getting the customer’s permission, your data based on visits may be impacted when customers decline the use of cookies for analysis or marketing purposes. In short, once you modify these settings and adjust other metrics that rely on visitor data (such as conversion rate) may result in decreased metrics such as page views and sessions.
Viewing Data for Migrated Orders
Orders imported from other platforms or through custom applications may take up to 24-48 hours to fully appear in your system's analytics data after the import is complete. This delay in data display will not affect your customers' checkout process or your ability to manage orders (like editing, shipping, etc.) from the order list page.
However, please note that changes made to a migrated order after import (e.g., adding or removing items, issuing refunds, canceling, or deleting) will also take 24-48 hours to reflect in your analytics data.
Example
If you import 10,000 orders at 10:00 AM on January 1, 2024, and the import finishes by 10:30 AM that day, you can expect to see this data in your analytics or sales reports by 10:30 AM on January 3, 2024 at the latest.
If you issue a $5 refund for one of these orders at 10:00 PM on January 10, 2024, the refund will appear in your analytics reports after 10:00 PM on January 12, 2024. The refund will be timestamped as 10:00 PM on January 10, 2024, reflecting when the refund was processed.
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