Google Shopping

Overview Google Shopping Trends track the relative interest in specific products across Google’s shopping ecosystem over time. In TickerTrends, this data reflects consumer purchase intent and product level demand, making it a direct signal of real world buying behavior across retail, eCommerce, and branded DTC products.

Historical Length Available from 2004 to present, depending on product category and keyword coverage.

Granularity Weekly data is the default, with some shorter time ranges supporting daily granularity. In TickerTrends, we standardize this feed to ensure consistent long term historical tracking across all product categories.

Update Frequency Data is updated weekly. Users typically see a roughly one week lag between real world shopping activity and TickerTrends availability.

Methodology Google Shopping Trends provides indexed popularity scores rather than absolute transaction volumes. We rely on Google’s underlying normalization methods and display the data as provided. This allows users to compare relative shifts in product demand across time rather than exact unit sales.

Example Visualization

Use Cases

• Track consumer demand for specific products ahead of earnings.

• Identify breakout product categories in real time.

• Compare product level momentum across competing brands.

• Monitor seasonal shopping behavior such as holidays, back to school, or promotional events.