The insights report provides insight into the connection and correlation between products through customers’ browsing and purchasing behaviors in online stores.
In This Article
- Shopping Cart Analysis
- Shopping Cart Abandonment
- Product Connection Insight
- Product Lead Insight
- Bundled Purchase
- Out-of-Stock Alert
- Product Fluctuation
- Traffic Insights
Shopping Cart Analysis
Shopping cart analysis helps you to understand customers’ purchasing behavior. It will show you the product bundles that the customer has added to the shopping cart in the past 30 days and the add-ons of product A and product B, and the likelihood of them being added together.
The report shows only the product bundles with strong correlations. The algorithm calculates the correlation. You can conduct related marketing campaigns based on the calculation results, such as product recommendations, discount codes, and bundle promotions.
If you see the message Insufficient data for analysis, it means that the products added to the customer’s shopping cart were insufficient in the past 30 days (including today), therefore a statistically significant relationship cannot be obtained. This situation may happen when you have few visitors, or some products are still new.
Shopping Cart Abandonment
The Shopping cart abandonment report can help you understand which products are most likely to be placed in the shopping cart but abandoned at checkout in the past 30 days and the value of the abandoned products. Based on the data, you may determine and adjust your product strategy to increase the conversion rate.
You may view statistics up to an hour ago in this report, and you can reopen or refresh the report to display the most updated data. This report uses the following relevant metrics:
| Metric | Definition |
| People of abandonment | Users who have added products to the cart in the past 30 days while not placing orders in the following 24 hours after adding to the cart |
| People of adding to cart | Users who have added products to the cart in the past 30 days. |
| Abandoned product value |
Product value once a product is added to a shopping cart without checking out within 24 hours after adding to cart in the last 30 days. Calculated as (Selling price × No. of pieces added to cart). The selling price will be the data of the previous day. |
| Abandonment rate | (Abandoned users / Add-to-cart users) × 100% |
Product Connection Insight
The report shows the connection between the product bundles visited or added to the cart by the same user in the past 7 days, which can help you gain insights for product recommendations.
- Visit connection: If the same user has visited more than one product detail page in the past 7 days, there is a visit connection between the visited products.
- Add-to-cart connection: If the same user has added more than one product to the cart in the past 7 days, there is an add-to-cart connection between the add-to-cart products.
- Main product and related products: The products with visit connection are called main product and related products respectively.
Here, the report shows only the products (up to 50 products) that have been visited by visitors in the past 7 days and shows only those with a visit connection rate and an add-to-cart connection rate greater than zero.
Based on the analysis results of the Product connection insight report, you can analyze user preferences and make recommendations to them via email to improve visitors’ retention and repeat purchase rates. You can also bind products in marketing campaigns (e.g., buy X and get Y free), advertisements, landing page scenarios, and product applications (such as variant combinations and product bundles) to increase conversion rates and achieve sales. If there are not enough products browsed or added to the cart, you may encounter situations where the page displays No data available.
The Product connection insight report displays data from 24 hours ago, and the time filter in the report refers to GMT+8:00 (Beijing time) data.
When it is GMT+8:00 (Beijing time) on February 20, 2024, you can view the data before GMT+8:00 (Beijing time) on February 19, 2024.
Fields used in visit connection reports are described as follows:
| Field | Description |
| Main product name | The name of the main product with the visit connection |
| Users of main product | Number of users who have visited the main product in the past 7 days |
| Connected product name | The name of the product having a visit connection with the main product |
| Users of connected visit product | Number of users who have visited the connected products in the past 7 days |
| Visit connection rate |
Visit connection rate = Users of connected visit product / Users of main product × 100% It measures what percentage of the users who have visited the main product in the past 7 days have also visited a related product. A higher visit connection rate means a stronger visit connection between the products. |
Fields used in add-to-cart insight reports are described as follows:
| Field | Description |
| Main product name | The name of the main product with an add-to-cart connection |
| Users of adding main product into cart | Number of users who have added main product into cart in the past 7 days |
| Connected product name | The name of the product having an add-to-cart connection with the main product |
| Users of connected add-to-cart product | Number of users who have added connected product to cart in the past 7 days |
| Add-to-cart connection rate |
Add-to-cart connection rate = Users of connected add-to-cart product / Users of adding main product into cart × 100% It measures what percentage of the users who have added the main product to the cart in the past 7 days have also added a connected product to the cart. A higher add-to-cart connection rate means a stronger add-to-cart connection between the products. |
Product Lead Insight
The report shows the connection between the products that the same user has visited and added to the cart successively in the past 7 days, which can help you understand the potential product bundling strategy.
- Lead-in visit connection: It is considered that product A has visits lead for product B if any user visited the product detail page of product A and then jumped to that of product B in the past 7 days, that is, some traffic flows from A to B.
- Lead-in add-to-cart connection: It is considered that product A has an add-to-cart lead for product B if any user added product B to the cart on the product detail page of product A, or if any user visited the product detail page of product A and then jumped to that of product B and added product B to cart in the past 7 days.
- Main product: the product leading visits or add-to-cart.
- Lead-in product: the product being led to visits or add-to-cart.
Here, the report shows only the products (up to 50 products) that have been visited by visitors in the past 7 days and displays only those with a lead-in visit rate and a lead-in add-to-cart rate greater than zero.
Based on the data shown in the Product lead insight report, you can bind products with high lead-in rates to boost the store’s conversion rates. If there are not enough products browsed or added to the cart, you may encounter situations where the page displays No data available.
The product lead insight report displays data from 24 hours ago, and the time filter in the report refers to GMT+8:00 (Beijing time) data. When it is GMT+8:00 (Beijing time) on February 20, 2024, you can view the data before GMT+8:00 (Beijing time) on February 19, 2024.
Fields used in Visits lead report are described as follows:
| Field | Description |
| Main product name |
The name of the main product with lead-in visit connection Product A can be used as the main product if any user visited the product detail page of product A and then jumped to that of product B in the past 7 days. |
| Users of main product | Number of users who have visited the main product in the past 7 days |
| Lead-in product name |
The name of product having a lead-in visit connection with the main product Product B can be used as the lead-in product if any user visited the product detail page of product A and then jumped to that of product B in the past 7 days. |
| Users of lead-in visit product | Number of users who have visited the lead-in product in the past 7 days |
| Lead-in visit rate |
Lead-in visit rate = Users of lead-in visit product / Users of main product × 100% It measures what percentage of the users who visited product A went to product B in the past 7 days. A higher lead-in visit rate means a stronger lead-in visit connection between products A and B. |
Fields used in Add-to-cart lead report are described as follows:
| Field | Description |
| Main product name | The name of the main product with an add-to-cart connection |
| Users of main product | Number of users who have added main product into cart in the past 7 days |
| Lead-in product name |
The name of the product having a lead-in add-to-cart connection with the main product Product B can be used as the lead-in product if any user visited the product detail page of product A and then jumped to that of product B and added product B to the cart in the past 7 days. |
| Users of lead-in add-to-cart product | Number of users who have added lead-in product to cart in the past 7 days |
| Lead-in add-to-cart rate |
Lead-in add-to-cart rate = Users of lead-in add-to-cart product / Users of main product × 100% It measures what percentage of the users who added product B directly or added product B after going to the product detail page of product B after visiting product A in the past 7 days. A higher lead-in add-to-cart rate means a stronger lead-in add-to-cart connection between products A and B. Product A also has the lead-in effect for product B if the user adds product B directly and rapidly on the product detail page of product A, by recent browsing or product recommendation. However, in this case, the users of product B are 0, namely, products A and B have a visit connection rate of 0% as the user does not visit product B. The report will not show the product bundle with a visit connection rate of 0%. |
Note:
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Bundled Purchase
This report shows the bundled purchase status of products in the selected time frame. The bundled purchase means that multiple products are added to the same order at the same time. Based on this report, you can know the bundled purchase status of products.
This report displays all the orders from your store from 24 hours ago. The metric statistics will be recorded by the time the order was created.
Fields used in this report are described as follows:
| Field | Description |
| Product Name | Title of the product. If the product name is changed after customers place orders, the new product name will be displayed in the report. If you have not inserted any picture for the product, the image in this field is null. |
| Associated product name | A product that is purchased along with the product displayed in the same row. For example, if products A, B and C are purchased by customers at the same time, they are associated products for each other. |
| Orders |
Number of orders containing both product A and product B within the selected period. They are counted based on the time when an order is successfully created. For example, at 10:00 AM on January 1, 2023, Jennie created an order in your store containing two products (A and B). At 12:00 PM on January 2, 2023, you added one product (C) to Jennie’s edited order. In the report, you can see that the number of common orders is 1 for products A and B, products A and C and products B and C when you select the date range as January 1, 2023, and that the data will be displayed as empty (an extreme assumption is made here that your store generated no new orders during this period) when you select the date range as January 2, 2023, as the order was not created on January 2, 2023. |
Out-of-Stock Alert
The report shows the products with less than 15 days of inventory remaining, which enables you to timely adjust the product inventory management and set other strategies.
Possible out-of-stock can be predicted based on sales performance in the past period of time. The report shows only the products with a sales volume of greater than zero in the past 28 days, and the days of inventory remaining can be estimated based on the average selling speed of the products in the past 28 days.
If there are not enough products to generate sales in the last 28 days, you may encounter situations where the page displays No data available.
This report displays data from 24 hours ago, and the time filter in the report refers to GMT+8:00 (Beijing time) data. When it is GMT+8:00 (Beijing time) on February 20, 2024, you can view the data before GMT+8:00 (Beijing time) on February 19, 2024.
Fields used in reports are described as follows:
| Field | Description |
| Product Name | Product title. |
| Vendor | Brand name of the product |
| Multivariant specification | SKU specification of the product, e.g., red L |
| Sales volume of the past 28 days | The total sales volume in the past 28 days. If you edit an order to reduce the number of products, sales volume may be negative. |
| Reporting days |
The number of days that have been reported in the past 28 days for products that have already generated sales records. (only products with a sales volume of greater than zero in the past 28 days will be shown in the report).
For example, if it’s October 31, 2023, and in the report, we can see the latest data as of October 30, 2023. For product A, the first order was placed on September 1, 2023, and the second order on October 15, 2023. This means that product A was one of the objects analyzed in the report for the past 28 days, that is, the number of its Reporting days was 28. For product B, the first order was placed on October 15, 2023, and its Reporting days are counted from October 15, 2023, to the current day, that is, the number of its Reporting days is 15. |
| Remaining inventory quantity | Total quantity of products currently in inventory |
| Average pieces sold per day |
The number of products sold per day in the past 28 days. Calculation formula: Average pieces sold per day = Sales volume of the past 28 days/reporting days |
| Days of inventory remaining |
Number of days for products available for sale, estimated based on the remaining inventory quantity and the selling speed. If negative, it will be displayed as 0, indicating that the product is out of stock, and the inventory needs to be replenished as soon as possible, or an oversold strategy is required to ensure the normal transaction. Calculation formula: Days of inventory remaining = Remaining inventory quantity/Average pieces sold per day |
Product Fluctuation
SHOPLINE defines product fluctuation as a variation of more than 30% in Day-to-day growth rate of sales, sessions, and conversion rate. You can monitor the product fluctuation by going to Analytics > Reports > Insights > Product fluctuation. The report analyzes fluctuation in three dimensions.- Sales: The report shows only the products with sales of the last day greater than zero. If a product’s sales have significantly increased, it may indicate a potential best-selling item. If the sales have significantly decreased, you may consider increasing advertising, implementing marketing campaigns, and offering promotional discounts on product bundles to encourage customers to make purchases. The metrics used in the report are defined below:
Metric Definition Sales of the last day Sales of the products on the day before the selected time. If there are any order edits, the sales amount may be negative. Sales of the day Sales of the products for the selected day. If there are any order edits, the sales amount may be negative. Day-to-day growth rate (Sales of the day - Sales of the last day) / Sales of the last day × 100% - Sessions: The report shows only the products with sessions of the last day greater than zero. If there is a significant increase in sessions, it may indicate the effectiveness of your advertising efforts. If there is a significant decrease in sessions, you can further optimize product titles and descriptions, as well as engage in more off-site promotions to make improvements. The metrics used in the report are defined below:
Metric Definition Sessions of the last day Sessions of the products on the day before the selected time. If there are any order edits, the sales amount may be negative. Sessions of the day Sessions of the products for the selected day. If there are any order edits, the sales amount may be negative. Day-to-day growth rate (Sessions of the day - Sessions of the last day) / Sessions of the last day × 100% - Conversion Rate: The report shows only the products with conversion rates of the last day greater than zero. If there is a significant increase in the conversion rate, it may be the result of adjustments in your business strategies. If there is a significant decrease in the conversion rate, you can promote customer conversions by utilizing promotional offers such as coupon codes. The metrics used in the report are defined below:
Metric Definition Sessions with completed checkouts of the last day Sessions who complete checkout for the product one day before the selected time Conversion rates of the last day Sessions with completed checkouts of the last day / Sessions of the last day × 100% Sessions with completed checkouts of the day Sessions who completed checkout for the selected time for the product Conversion rates of the day Sessions with completed checkouts of the day/Sessions of the day × 100% Day-to-day growth rate (Conversion rate of the day - Conversion rate of the last day) / Conversion rate of the last day × 100%
Traffic Insights
The Traffic Insights report provides a visual representation of the relationship between sessions and conversion rates across various dimensions such as country/region, campaign, device type, and operating system. This helps you identify trends and opportunities for improvement. To view the report, go to Analytics > Reports, locate the Insights section, and select Traffic Insights.
Unlike Traffic Acquisition Reports, Traffic insight uses a two-dimensional graph to display data. The X-axis represents session count and the Y-axis represents conversion rates. Each dot on the graph corresponds to a specific data point, allowing you to visualize the correlation between sessions and conversions. For example:
- Low Sessions, High Conversion: Dots in the upper left corner indicate a small number of sessions but a high conversion rate, suggesting an opportunity to increase traffic to boost overall conversions.
- High Sessions, Low Conversion: Dots in the lower right corner indicate a large number of sessions but a low conversion rate, suggesting potential issues with your website or marketing strategy.
Understanding Report Dimensions and Metrics
| Dimension | Metric Description |
| Date Range | Select from predefined ranges like Yesterday, Last 7 days, Last 30 days, and Last 90 days. The report provides the most recent data up to yesterday. |
| Country/Region | Choose to view data for All Countries/regions or a specific location. |
| Campaign | Analyze data based on specific campaign metrics using UTM parameters:
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| Device Type | View data segmented by device type (e.g., desktop, mobile). |
| Operating System | View data segmented by operating system (e.g., Windows, iOS, Android). |
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