The more people buy, the more products they return. But why don’t more marketing and advertising teams measure e-commerce returns? What can businesses do to assure their marketing metrics reflect their actual income and expenses?
Teams often overlook returns in their marketing metrics simply because they’re not exposed to the data, and the tools they use don’t have a model to even work with the data.
Google Analytics, Facebook Ads Manager, Google Ads Manager, Email Service Providers, Retargeting Providers, Mobile App Marketing Partners, and App Store Marketing Partners don’t ask you about returns rate. They don’t ask for the data; they just tell you what they’re taking credit for in terms of sales and performance.
How big a problem is this? “Shoppers return 5 to 10 percent of what they purchase in store but 15% to 40% of what they buy online,” David Sobie, co-founder and CEO of Happy Returns told CNBC.
Let’s delve into this high rate of online returns and what it means for advertising and marketing metrics.
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In the US, customers buying online return a whopping 30%-40% more of the product they buy.
In Germany, many consumers “buying” online choose to pay cash on delivery, meaning the order isn’t actually a sale until the customer holds the product in their hands and decides whether or not they want to keep it. Yup, they don’t even pay for it until they see it and decide if they want it.
Since they haven’t paid a cent until they actually have the product in their hands, there’s a high rate of e-commerce returns: 32% and 17% respectively for clothing and shoes. Many small German brick-and-mortar stores are reluctant to open online stores because of this.
They’re expected to account for 10% of all UK e-commerce sales by 2024, according to data compiled by Worldpay. The UK’s e-commerce market, currently the third largest in the world, is predicted to reach £264 billion by 2024, a 37% increase from 2020, according to Finextra.
Cash still matters. According to the Global Payments Report, PostPay and Cash on Delivery make up more than 13% of e-commerce payments in Latin America and are expected to remain relevant over the next three years.
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So why do we measure the performance of our digital marketing advertising every day, and how often are these costs factored into our approach to modeling customer acquisition costs and customer lifetime value?
Is the way we’re measuring digital marketing actually helping us drive predictable profitable growth?
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Example: “We have improved our seven-day view through rate of display ads by 30% by using a more specific set of behavioral criteria to narrow down our audience, refine the targeting and improve the performance.”
I heard this (or something close to it) at a client’s internal digital conference about six years ago. A very passionate and talented digital marketing manager for a global consumer electronics business was trying to educate the business on how digital marketing can help drive predictable, profitable growth.
The managing director of one of their European markets, who was sitting next to me, turned and said, “this marketing stuff is complicated, isn’t it!” My reply was, “Yes, it is for them, it doesn’t need to be for you.”
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What this business had done was use their warranty data to better understand who was buying their products indirectly through retail partners and using that to suppress audiences from their display marketing and retargeting campaigns. This meant their ads weren’t being shown to people who had just bought (direct or in-direct), and also that they were getting better returns from their ad and marketing budgets with a 30% uplift in revenue from the channel from the same budget. It’s a massive improvement, but just not framed through metrics that matter to the business.
Something else I hear as a point of friction is again around this measurement theme. Many times I see that the reports as to how well marketing is performing come from the insights team or the finance team, not from marketing or marketing tools.
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What we’ve seen from analyzing billions of orders is that in fashion retail, the rate of return in most major markets sits at around 25%. It varies by market and by category – footwear is higher than men’s wear, which is lower than women’s wear, which is massively higher than home furnishings, but it’s rare that people return a laptop or mobile phone.
Let’s say you spend $10 per acquisition in Facebook Ads and Google Ads and you’ve just achieved a new milestone of 100,000 orders at an average order value of $100. Congratulations! You spent $1,000,000 and you made $10,000,000!
You log into your dashboards (below is the Facebook Ads and Google Ads data pulled into the Emarsys Customer Engagement Platform) and you see:
One level deeper, you’ll also see:
A few years ago, I spoke with an executive at a well-known fashion brand that sadly has now gone into bankruptcy, closed all their stores, sold all their stock, and sold their brand, assets, and customer database to a successful retail brand. The conversion was as follows:
This is a real issue; it had a real business impact into their reporting lines and came from one key difference.
When they switched from a well-respected email service provider to take a new approach to customer engagement across channels and better understand their customers, we started working with their online data, their offline data, and their returns data.
There was a gap in the order of £30 MILLION for the quarter from what was reported in Google Analytics – that’s substantial. The reason? About 40% of their products bought online were returned, with a much higher e-commerce return rate for first-time buyers (who didn’t understand the size and fit) versus their most loyal customers, who bought through their stores and mobile app (and returned at around 15%).
When the differences were explained using the dashboard above, their answer was, “OK, we now understand the issue and we can talk to the merchandising and web teams about it.”
Online sales soared during the holidays and so have online returns, driving up costs for retailers and frustration for consumers.
It seems so obvious when you see it through the data that some people know their size and fit, but others don’t. Certain product lines like jeans and shoes have twice as many e-commerce returns, which will come to absolutely no surprise to anyone who has ever gone jeans AND shoe shopping with their spouse or friend!
E-commerce returns are one of the biggest problems plaguing CEOs, CIOs, COOs, and store operations directors, but often they’re not even visible to the marketing teams driving digital demand and customer loyalty.
We’re not engaging in meaningful cross-departmental discussions around the impact of returns on individual business areas, and as a result those areas aren’t leaning into the problem to drive better business value or better experiences for customers. After all, customers don’t like returns either. They want a product with as little hassle as possible.
It’s about time we as a marketing community working with customer data started surfacing up these insights and align to business priorities. We need to hold our internal teams and external providers accountable to help address this very expensive problem for the industry.
