Whether you’re operating a cross-border e-commerce store or an online mall, it’s crucial to pay close attention to data. Not only do you need to learn how to view data, but you also need to learn how to analyze it. Today, I’d like to introduce you to how to analyze data in a cross-border online mall.
Data plays a crucial role in every aspect of marketing. We use data to identify problems and effectively attribute them, with the ultimate goal of finding solutions.
What data should we focus on?
With the objective of paid conversions in mind, we analyze each marketing stage through the entire conversion funnel of the online mall. This allows us to easily identify and attribute problems when data anomalies arise and accurately locate the specific issue.
Based on the online mall’s purchase conversion funnel, we clearly define a core metric for each stage. For example:
Exposure (Aware): Website traffic is the measuring indicator, with core being UV (Unique visitor).
Interaction (Act): Interactions between visitors (UV) and the website, such as registration/lead numbers, UV numbers added to cart, etc.
Conversion (Convert): Interacted users, paid amount, etc.
Repurchase (Engage): Average revenue per customer (ARPU) over a certain period of time, etc.
An analysis of competitors’ online mall results can help us surpass them. Hence, how to outperform peers in the online mall is the most important aspect.
Summary of a simple strategy:
- Emulate content from peer websites with strong marketing logic to improve the conversion rate of inquiries from visiting customers on your own website. This includes, but is not limited to, sales scripts, services, custom modules, banner design, and professional introductions to production processes.
- Choose suitable keywords from peer websites to create product category pages or article pages that surpass their content. This will increase traffic to your own website.
- Carefully collect and categorize the content of peer websites’ high-traffic pages. The titles and descriptions of these pages are responsible for at least 30% of the traffic they attract.
- Select high DA websites relevant to your industry for link building from the peer websites’ external links.
- There are many tools available to research online store data. Sellers should analyze the data obtained and make adjustments to their strategy for better results.