Conversion Rate

In E-commerce Metrics
Conversion rate is the percentage of website visitors who complete a purchase, calculated by dividing the number of orders by the number of unique sessions over a given period.

Conversion Rate

Conversion rate is one of the three numbers that decide e-commerce revenue: traffic, conversion rate, and AOV. Move any one of them and revenue moves. Conversion rate is usually the noisiest of the three and the hardest to influence reliably, which is why most stores spend disproportionate energy on it.

The formula

Conversion Rate = (Orders ÷ Unique Sessions) × 100

If 10,000 sessions produce 250 orders, conversion rate is 2.5%. The benchmark varies wildly by category, traffic source, and price point. A general rule: 1-3% is normal, 3-5% is strong, anything above 5% suggests either a very loyal repeat customer base or a niche category with high purchase intent.

What pricing has to do with it

The relationship between price and conversion rate is mostly obvious (higher prices typically reduce conversion) but the magnitude is rarely intuitive. A 5% price drop might lift conversion 2% on one product and 25% on another. Price elasticity dictates the ratio.

The other half of the price-conversion relationship is comparison. Customers do not evaluate your price in isolation; they evaluate it against a reference, often a competitor's listing they had open in another tab. If your price drifts above the reference range, conversion drops not because the price is objectively too high but because it feels too high relative to alternatives.

Where to look when conversion drops

  • Pricing position has shifted. Competitors moved down and you did not.
  • Stock issues. Out-of-stock variants kill conversion across the parent product, even on the in-stock options.
  • Traffic mix changed. A higher proportion of cold traffic from a new ad campaign converts worse than warm returning visitors. The product page did not change; the audience did.
  • Reference price moved. A new entrant in the category dropped their price and reset what customers think the product "should" cost.

Example: A homewares store sees conversion drop from 2.8% to 2.1% over six weeks on a popular planter. Pricing analysis shows their price held at $42 while three of four tracked competitors moved from $42 to $36. The merchant updates the repricing rule to follow the average competitor price, the gap closes, and conversion recovers to 2.6% within three weeks.