Product and brand store traffic report analysis methods: strategies to improve operational effects

In today’s highly competitive e-commerce environment, operators often make the mistake of paying too much attention to the fluctuations in daily traffic and orders when processing product listings and brand store traffic reports. When traffic drops, some operators are eager to make up for the loss through advertising promotions. However, this response often appears short-sighted and ineffective. In fact, traffic changes follow certain rules, and sales fluctuate periodically, usually with a cycle of seven days.

Sellers with brand stores can attract relatively stable traffic by creating a brand homepage. Promotion methods such as headline ads can also effectively increase traffic and conversion rates. These flows form the basis of brand communication and, therefore, need to be carefully maintained. Improving brand awareness and increasing product repurchase rates are key steps to successfully establish a branded store. The ultimate goal is to enhance the brand’s premium capabilities and increase store profits.

Operators should use the weekly weight index to conduct in-depth analysis of traffic and sales changes. On certain dates, such as the 4th and 12th, there may be small peaks, indicating cyclical changes in traffic and sales [1]. However, it is often difficult to detect long-term traffic decline trends using single-day data. If it only stays at the daily level, operators may miss the real reasons for traffic decline, such as brand evaluation, price positioning, on-site competition, inventory status, seasonal promotions and other factors. Therefore, in-depth data analysis must be conducted to determine the core influencing factors and carry out targeted operations [1].

In the store Insights panel, it is worth noting the custom source tag function. This function can help sellers track the effects of different traffic channels (such as Facebook, Google, YouTube, etc.) and analyze the traffic and conversions brought by different channels to promote subsequent marketing decisions [2]. This analysis method has similarities in the operation of e-commerce platforms and is an effective strategy for traffic diversion and conversion optimization.

To sum up, combining traffic data with sales data for periodic analysis, and using data on multi-channel traffic diversion effects to optimize operational strategies is an effective way to improve brand and product store operations.