Customer Change Analysis – SHOPLINE Help Center

SHOPLINE's Customer Change Analysis provides valuable insights into your store's traffic fluctuations. By tracking these changes and analyzing their underlying causes, you can make data-driven adjustments to your marketing strategy. This article will guide you through the report, explaining key metrics to help you gain a deeper understanding of your customers.

Introduction to Customer Change Analysis

The Customer Change Analysis helps you accurately track fluctuations in your store's traffic and leverage insights to optimize your marketing strategies. Here's how to understand the report's benefits:

Understanding Customer Traffic Changes

When you notice significant increases or decreases in your store's visitor count, potential causes may include changes in traffic from specific referral sources or regions. For instance, referral sources might include Google Ads, Instagram, TikTok, etc. If your store's visitor count has decreased by 50% month-over-month, you can analyze the following metrics in the Visitor Change Analysis cards:

Trend-boosting referral sources: Displays the number of sources whose trends align with the overall store trend.
Trend-reducing referral sources: Displays the number of sources whose trends are opposite to the overall store trend.

Detailed Insights into Visitor Contributions

Clicking on the analysis cards provides access to the Actions: View traffic and sales contributions by referrer report, allowing you to examine visitor change contribution data in more detail. This data reflects the extent to which fluctuations in visitor numbers from specific channels or regions impact the overall store:

Higher percentage: Indicates a more significant impact on store traffic from that channel or region.
Lower or negative percentage: Indicates a smaller or negative impact from that channel or region.

Viewing Customer Change Analysis

To view the Customer Change Analysis report, follow these steps:

From your SHOPLINE admin panel, go to the Analytics module.
In the Visitor change analysis section, you can:

- View data on trend-boosting and trend-reducing referral sources. By default, the data for today will be displayed and compared to yesterday.
- Select a desired time range from the predefined options (e.g., Last 7 days) or customize a range using the calendar.
- Choose a comparison time from the predefined options (e.g., Previous day) or customize it using the calendar.
  
  Note: Data updates in real time. If no trend changes are detected within the selected time range, data won't be displayed.
- Customize the report sections by clicking the Customize button to move or hide sections as needed.

Click the referral source cards to access the View traffic and sales contributions by referrer report. Explanations of the analysis dimensions and common metrics are provided in the sections below.

Key Dimensions in Customer Change Analysis

The table below explains the dimensions used in the Customer Change Analysis report:
2.0.png

Dimension	Description
Referrer name	The name of the source that directed customers to your store (e.g., Google, Facebook, Instagram, TikTok). If the referrer cannot be identified, the source name will display as "N/A" for direct traffic.
Referrer source	The origin source where customers access your store, which may include: Social Networks: Accessed through a social media link. Direct Traffic: Accessed by entering the URL directly in the browser. Search Engine: Accessed from a search engine results page. Others: Includes unknown sources and cases where the referrer cannot be identified.
Country/Region	Represents the visitor's location, as determined by their IP address, both when they visit your site and when they place an order. Since a visitor's IP may change during browsing, the IP in the visit record may differ from that in the order record. The report will display "1 visitor from the US completed 1 order" only if the IP country/region matches in both records.

Decoding the Analysis Metrics

Here's a breakdown of the key metrics used in the Customer Change Analysis report:
3.0.png

Metric	Description
Trend-boosting referral sources	Referral sources that are "moving in the same direction" as your overall store traffic. For example, if your overall store traffic is decreasing, and a particular referral source like Google Ads is also decreasing its traffic to your store, it is considered a trend-boosting source.
Trend-reducing referral sources	Referral sources that are "moving in the opposite direction" as your overall store traffic. For instance, if your overall store traffic is decreasing, but Instagram is increasing its traffic to your store, it is considered a trend-reducing source.
Sessions	Sessions that enter your online store. This metric is specific to your online store channel. A session (unique visitor, UV) may involve multiple actions (page views, PV). A visitor session ends after 30 minutes of inactivity. For example, if Customer A visits your store through social media and then returns a few days later, it counts as two sessions. A session also ends if it spans midnight in the time zone where the store is located or midnight in UTC. For example, if Customer A visits your store at 11:30 PM on January 1 and leaves at 12:20 AM on January 2, the visit on January 2 is counted as a new session. Therefore, when you view session metrics, there will be one session recorded for each of these two days.
Contribution to visitor change	This metric shows how much a specific dimension, such as a referral source or region, is contributing to the overall change in your store's traffic. For example, If a specific referral source accounts for 50% of the total increase in your store's traffic, its contribution to visitor change is 50%.
Added to cart	The number of sessions in which visitors clicked the Add to cart button. Visitors who click the Buy Now or PayPal Express Checkout button are not counted.
Reached checkout	The number of sessions in which visitors reached the checkout page.
Completed checkout	The number of sessions where visitors successfully placed orders.
Conversion rate	Conversion rate = Completed checkout sessions / Sessions × 100%.