Jessica Murphy, cofounder of consumer-facing fitting solution True Fit, knows what’s on the mind of retailers: returns.
“I’m getting a lot of calls from retailers about return rates, which are seemingly higher than normal,” Murphy said. Similar to other speakers, she said to understand what’s going on, it’s important to focus on some math.
This story first appeared in the March 30, 2016 issue of WWD. Subscribe Today.
Murphy’s lesson examined how companies calculate returns, which is done in a variety of ways that include units received and sales within a month.
“But a better method is to look at the return rate as returns in a given month divided by the weighted trailing average of sales,” she said, adding that the advantages include real-time measurement of returns and a four-time reduction in return-rate variability.
“It is more correlated to the sales that created those returns,” she said.
But that’s only a part of the equation. “We also need to understand consumer behavior,” Murphy said.
That’s where data plays a role. True Fit’s data are drawn from 10,000 apparel and footwear brands offering millions of styles and hundreds of attributes per style, involving 100 million consumers with a variety of body stats, brand and style affinities, Murphy noted.
The process also requires looking at order sampling from a size, style and color perspective, as well as “sequential order sampling” that occurs across multiple orders. The analysis also includes “sample consumer clusters” from “the ‘super shoppers’ to the ‘one-and-done’ consumer,” Murphy explained.
As a result, she said the “data reveals what actually works for a particular consumer.”
Moreover, once the data is analyzed — to include returns, styles, sizing, etc. — “You can start to see some trends.”