There are no industry averages. They don’t exist. I wish they did, but they don’t. Discussions about conversion rates often begin with the notion of an industry or category average.
I’m frequently asked: “What’s the standard conversion rate for my category?” Or, in some cases, the retailer informs me: “The standard conversion rate for my category is X%.”
While traffic counter penetration rates have never been higher, we estimate that 40-50% of retailers still don’t track traffic in all their stores. Without traffic count data, you can’t calculate conversion rates. Furthermore, even among the retailers who do have traffic/conversion data, it’s often not shared outside of the organization, so “industry averages” just don’t exist and probably won’t for a long time, if ever.
Not all retailers track traffic
I find it amusing and ironic that when I inform executives that formal industry averages don’t exist, they are often surprised and incredulous: “What do you mean industry averages don’t exist? That can’t be!” When I point out that they don’t measure conversion rates in their own stores and that’s partly why an industry average doesn’t exist, I get blank stares and after a brief, awkward silence, the topic changes.
Conversion rates can vary significantly across categories, within categories and even across stores in the same chain. When you start to map conversion rates across a large number of retailers as I have, it becomes apparent why precise “industry averages” don’t exist. The table below shows conversion rate ranges across a number of retail categories.
These are not formal averages or firm industry or category indices, but rather general guidelines based on retailers I have worked with.
Deloitte published a white paper on customer conversion; the paper reported ranges that were substantially similar to these.
The general category ranges can provide at least a basic idea of conversion rate ranges. When I share this with retailers, some are underwhelmed. “Kind of broad, isn’t it?” I’m not sure what these retailers expected the category ranges would be, but I think at least some of them expected me to say, “The average conversion rate for your category is precisely 25%.” Unfortunately, it doesn’t work that way.
It is not useful to represent the averages by category, because there can be significant variances among retailers in any given category. In women’s apparel, we have tracked conversion rates anywhere from 5% or less to over 25%. To say the average is 15% would be misleading.
Wide variations in conversion rate
When you consider the wide spectrum of women’s apparel retailers, it’s not hard to understand the variations in conversion rate. Take two women’s apparel stores in the same mall. One store sells high-end, exclusive designer labels, and the other sells trendy, affordable and highly promoted apparel.
The traffic and conversion rate profiles for these two stores would be very different merely by virtue of their offerings. The high-end store likely has a significantly lower conversion rate than the trendy store, as prospects visit the store looking to see the latest fashion — but ultimately are not in a position to pay the price.
The trendy store probably has much higher traffic and higher conversion, as women stream into the store to look and buy. It’s irrelevant to compare the conversion rates of these two stores – they’re too different; they’re incomparable.
But what about stores in the same chain?
While it is entirely reasonable to expect that conversion rates across chains, even chains in the same category, might have a wide range of customer conversion rates, it would seem quite reasonable to expect the conversion rates of stores within the same chain to be relatively consistent. Here we would expect to see fairly narrow gaps between low and high conversion rates.
The table below shows the actual conversion rate ranges for a number of retail chains. As you can see, the conversion rate ranges can be significant, even for stores in the same chain. In a specialty electronics chain, we observed a seven-point variance from highest converting store to lowest, with an average for the chain of 14%. The biggest variance was in a home improvement retailer, where there was a whopping 34-point delta in conversion rate from highest to lowest store.
Variations in conversion rates can occur for a multitude of reasons including:
- Store formats (mall versus street)
- Micro-economic factors
- Local demographics of shoppers
- Competitive Landscape
- Differences in the effectiveness of store managers and associates who operate the store
Given all these variables, generalizing results into ‘industry averages’ seems pointless.
As excerpted from “Conversion: The Last Great Retail Metric”, written by Mark Ryski. Mark Ryski is also the author of ”When Retail Customers Count” and is the CEO and Founder of HeadCount Corporation (www.headcount.com)