Why Returns Data Is Crucial to Customer Experience
Data can change your business, if it’s used in the right way. It should be used as a way to replace guesswork and give predictability and concrete actions, it should be expertise that’s digital, making it instant and scalable.
I want to talk about how a specific subset of retail customer data is insanely important and underutilized to deal with one of the biggest cost pressures in retail: returns.
Asking the Right Questions
Having the right data can help you answer some really important questions. Here are a bunch of questions retailers probably ask themselves already when it comes to returns:
- Why is this customer returning this product?
- Is the product frequently being returned for the same reason?
- Is the customer frequently returning products?
- Are we losing money on this customer?
- Can we recover some costs from this customer? (e.g., by making them pay for returns)
- Can the product be resold locally in store?
- What is the margin potential of this product?
- Therefore, how quickly do we need to get it back into stock?
- Can we encourage this customer to exchange instead of returning?
- Can we encourage this customer to return the product in-store to recover revenue?
- Is the customer high-value?
- Should we offer them a discount if they return in-store on their next purchase?
- How long do returns take on average?
- Is this list too long?
- Do returns come back faster if we encourage returns in-store?
- Do returns come back faster if we offer drop-off at third-party locations?
- How do customers feel about the return experience?
- What volume of returns does the sorting center need to be prepared for this week?
- Will people stop reading this blog because it’s got a long list of questions in it?
- Which logistics service is most appropriate to bring returns back to the sorting centers and/or stores?
- Can we add “propensity to return” to our customer lifetime value formula to more accurately represent lifetime value?
If you’re not asking some or all of these questions, you either have a pretty great returns platform sorted already, so you don’t need to worry about any of them, or you’re missing some big opportunities. If you can answer some, even better.
The Right Answers
To harness the potential of returns as a loyalty driver, you’ve got to be able to measure your performance, tie customer’s previous purchase history to their return profile, and process them as efficiently as possible.
Doing that requires returns data to be captured digitally and integrated to your other customer data tools. Too many retailers let returns be the ugly duckling of the business, cast aside and isolated from other departments and roles. To be fair, returns are not in a pretty state right now for most retailers. They’re pure cost, negative sales dragging on the bottom line. At least, that’s the perception.
However, using a proper platform to support returns can turn that ugly duckling into a beautiful swan, encouraging customers to come back to you again and again with a seamless experience and the right options at the right time. A returns platform allows customers to book their return in through an online portal, hosted in your website. You can offer them an exchange based on what they’re returning – 60% of returns are due to fit, size or color issues. Try experimenting with exchange offers to see what converts best. Exchanges are way better than returns for customer satisfaction and your bottom line.
Then, customers choose how to return – through the post or bringing it into store or to drop-off locations. You can highlight in-store returns as a default option to bring in more customers to your stores, helping recover more revenue from the returns process.
Seeing the Full Picture
With a digital returns platform, you’re seeing so much more of the customer journey, and you can translate this visibility into actionable improvements quickly. Right now, if I appeared in your office and asked you what you’d most want to change about your returns process, would you know the answer? The correct answer, of course, is, “Who are you and how did you get into this office?” but even if you do have an answer to that question, is it backed by a clear view of the options and quantifiable results? Usually the answer is, “Not really.”
This is what I mean about data being about turning guesswork into information and expertise into something that scales. You probably have one or two people who are super brain geniuses about reverse logistics and know the whole thing back to front, but they can’t possibly know how every customer interacts with your returns processes. That’s what the platform is for.