Do discounted products rank higher in Google Shopping?
Discount status vs. relative depth heatmap
This heatmap shows the relationship between whether a product is discounted and how far down the page it appears (relative depth scaled 0–100% per SERP). The visualization compares products with no discount versus products showing any discount amount. Darker colors indicate higher density at that position.
Data based on the last 30 days of data from Productrise.
The discount and ranking connection
The presence of a discount—showing a strikethrough regular price alongside a lower sale price—is a powerful signal to consumers. But does Google's algorithm favor discounted products in organic rankings? Understanding this relationship can help sellers make informed decisions about their pricing and promotional strategies.
Google's organic ranking algorithm doesn't explicitly prioritize discounted products. Instead, the algorithm focuses on relevance, quality signals, and user engagement metrics. However, discounts can indirectly influence rankings if they lead to improved click-through rates, conversion rates, and positive user signals that Google's algorithm picks up over time.
Understanding the data
The heatmap above shows a simplified comparison: products with no discount (where regular price equals current price or no regular price is shown) versus products with any level of discount (where the regular price exceeds the current price). This binary comparison helps isolate the effect of showing a discount versus not showing one.
Lower relative depth percentages indicate higher positions on the page. By examining the density patterns across these two categories, we can see whether discounted products tend to cluster higher or lower in search results.
Context matters for discounts
While the presence of a discount can be important, context matters significantly. Some queries are discount-driven—searches like "cheap laptops" or "kitchen blender under $30" signal value-seeking behavior, and it makes sense that Google would rank discounted products higher for these queries since they directly match user intent. However, Google can be suspicious of massive discounts, particularly on new websites, as one Reddit user noted that "Google treats them as suspicious, particularly on new websites." Extremely high discount percentages (often 70% or more) can trigger quality filters and may result in reduced visibility or account suspensions, as they may be perceived as potential scams or pricing errors.
Explore our related pricing insights to get the complete picture:
- How many products are discounted in Google Shopping organic results?
- How are products priced in Google Shopping organic results?
- Does product price impact organic ranking in Google Shopping?
Key takeaways
- Discounts alone don't guarantee higher rankings in organic results
- User engagement with discounted products may indirectly influence visibility over time
- Focus on strategic pricing that balances competitiveness with profitability
- Consider discounts as part of a broader pricing and marketing strategy
- Quality, relevance, and user experience remain the primary ranking factors
How we normalize page depth per SERP
Some search result pages are far taller than others because of extra SERP elements. To compare positions fairly, we normalize depth within each SERP: Relative Depth = (pixel_y - min_pixel_y) / (max_pixel_y - min_pixel_y) * 100. This scales vertical position to 0–100% per SERP and avoids skew from unusually tall pages.
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About this data
This data is sourced from anonymized SERP data collected through the Productrise application. It represents real, organic (non-synthesized) search results from Google Shopping across queries worldwide.
Data details:
- Time period: Last 30 days
- Refresh cycle: Every 24 hours
- Source: First page of Google search results only
Important note: While this data represents genuine search results, it may be influenced by the specific queries and industries tracked by Productrise users. The insights shown here reflect real-world patterns but may be biased toward the product categories and markets most actively monitored within our platform.
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