Shoplytics benchmark helps you quickly understand how your store performs in the market. Powered by AI, it compares key metrics with stores of the same kind, revealing your strengths and areas for improvement to enhance performance and competitiveness.
This article will cover the following:
1. How to view benchmark
In the SHOPLINE Admin, go to [Reports & Analytics] > [Shoplytics]. On the homepage, click the benchmark tag.
A pop-up window will appear after you click the tag, showing the industry benchmark comparison for key metrics.
To view performance for a specific channel, click the corresponding channel tab. Relevant metrics will be shown based on the selected channel. For details on metric definitions, please refer to: Home | Shoplytics.
To change the analysis range and view data for a different time range, use the date picker on the top right of this page.
*Notes:
- It only supports analysis range starting from 1 January 2024.
- Benchmark data is updated weekly. If the selected range is later than the latest update date, the following message will appear. It is recommended to adjust the analysis range to match the latest update.
2. Comparison grouping logic and store restrictions
Comparison grouping logic
The benchmark feature compares your store with stores of similar type and scale. The following section explains the grouping logic:
| Grouping Dimension | Group |
| Country/Region |
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| Product category |
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| Gross Orders |
Gross orders are calculated based on the number of orders placed within the same country/region and product category over the past 90 days.
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*Notes:
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Comparison groups are updated on the 1st of every month.
For example, Store A is classified under "Taiwan, Fashion & Apparel, and Gross Orders M". This month, Store A will be compared with other stores in the same group. If Store A performs well and its gross orders increase to "L", it will be compared with stores in the "Taiwan, Fashion & Apparel, and Gross Orders "L" group next month.
The product category is classified based on the store's primary product, not the store category setting in the Admin.
In the selected analysis range, if your store falls into multiple groups, the group with the longest time proportion will be used for comparison. If the time proportions are equal, the most recent group will be used for comparison.
Store restrictions
- This feature is only available for Taiwan/Hong Kong stores.
- This feature is only available to stores that can be classified into the groups listed above. If your store is currently paused, it may not be assigned to any comparison group.
- This feature is only available to stores with at least one completed order (excluding OpenAPI or import orders) within the selected analysis range.
You must have admin permissions for the corresponding channel to access this feature. If you only have permissions for the Online Store, you can only view the benchmark for the online store. To view the benchmark for the Retail Store, you must have permission to access all branches. If you only have access to some branches, the benchmark will not be available.
This feature is available to stores with the "Shoplytics(Pro)" module. If you are using the Standard or Lite version, you can only view the benchmark with sample data. Please upgrade your module to access the actual data.
3. Tag definitions
Benchmark summarizes the performance of key metrics and highlights weak-performing tags on the homepage for each channel.
For example, if two of your metrics are marked as "Outstanding" and two as "Fair," the homepage will display a message: "You have 2 fair metrics."
Tag definitions are as follows:
- Lagging: The metric value is negative, or falls within the 0% to <25th percentile of the group.
- Fair: The metric falls within the 25th to <50th percentile of the group.
- Good: The metric falls within the 50th to <75th percentile of the group.
- Outstanding: The metric falls within the 75th to 100th+ percentile of the group.
Hover over each bar in the chart to view the benchmark range for each tag.
4. Use case
How to review performance data?
- Review the data on a weekly or monthly basis. Compare your store's performance with similar stores to understand whether you are falling behind and to evaluate growth progress.
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Metrics can be grouped into two categories:
- Traffic and revenue: Gross orders, average order value, total sessions, and conversion rate.
- Customer management: Returning shopper rate and newly added members.
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For O2O merchants, review performance through the following perspectives:
- Omni-channel overview: Assess overall business performance compared with similar stores across all channels.
- Single channel analysis: Switch to the "Online Store" or "Retail Store" tab to review channel-specific metrics and identify weaknesses.
- Online versus offline comparison: Compare the performance of online and offline channels during the same time period. For example, review data from an anniversary promotion launched both online and offline to identify patterns such as strong online conversion rates while in-store orders lag behind.
Common scenarios and examples
i. Identify the cause of stalled sales
- Scenario: When monthly sales fall short of expectations, use data to quickly determine whether the issue is traffic-related or conversion-related.
- Key metrics (online store): Total sessions and conversion rate.
Key Metric Overview and Insight |
Example |
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Key metric overview:
Insight: There is room to improve traffic acquisition through advertising, marketing, or SEO. Once users arrive on the site, performance is generally solid. |
Traffic needs improvement |
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Key metric overview:
Insight: Traffic acquisition performs well, but conversion drops after users enter the site. This points to a conversion bottleneck. Improvements may be needed on the landing page, pricing, and checkout flow. |
High traffic, low conversion |
ii. Customer growth and audience health
- Scenario: Evaluate whether the customer mix is healthy and determine whether to adjust strategies for acquiring new customers or retaining existing ones.
- Key metrics: Newly added members, returning shopper rate, and average order value.
Key Metric Overview and Insight |
Example |
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Key metric overview:
Insight: New customers make up a large share of the customer base, but their value is low. Focus on increasing the average order value of new customers. |
Low-quality new customers, low retention |
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Key metric overview:
Insight (early-stage stores): A returning shopper rate below the median of similar stores is normal at this stage. As the business grows and operations scale, this ratio should gradually increase. Insight (mature stores): A stable base of returning shoppers is expected. At the same time, continue to monitor new customer acquisition. If the returning shopper rate is outstanding, meaning it outperforms more than 75 percent of peers, new customer growth may be insufficient and should be reviewed. |
Relying on returning shoppers, weak new member growth |
iii. Campaign review and performance evaluation
- Scenario: After a campaign ends, review the results and compare your performance with similar stores to understand how effective the campaign was.
- Key metrics: Gross orders, average order value, conversion rate, and newly added members.
Insight |
Example |
Select the campaign period as the analysis range. Compare your store's performance with similar stores during the same period to assess whether you captured the campaign opportunity. |
Similar stores, very different Mother's Day results |
iv. Review product strategy positioning
- Scenario: Validate whether your business model, such as high price positioning versus volume-driven sales, is working as expected.
- Key metrics (online store): Average order value and conversion rate.
Insight |
Example |
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Same store type, different product strategies |
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