JP Arnaud-Marquez
·November 22, 2022
In 2021, retailers lost $218B due to customer returns. In fact, on average, roughly 30% of all ecommerce transactions get returned for various reasons.
But what if you could utilize Shopify’s reporting data to gain insights into why certain items get returned? Getting better insights on your returns can help you optimize your processes to lower your return rate.
That’s precisely why we built Loop’s automated survey system – it’s specifically for Shopify customers.
Here are 3 ways you can use Loop’s automated returns survey to harness raw Shopify data and gain unprecedented insight into specifically which customers are returning which items – and most importantly, why.
As great as numbers may be, there is no substitute for qualitative data when it comes to ecommerce.
Many ecommerce professionals employ a mix of chatbots and live agents to unify a 24/7 communication loop for customers seeking returns/exchanges. For the most part, this is helpful. But chatbots have their limits and people aren’t always as responsive and quick as we’d like.
Loop’s automated returns survey system does all that for you and provides customers with instant, automated feedback. In fact, you can customize up to two survey questions with a multitude of options for the customer to choose from.
This structure allows you to evaluate countless data sets for better, more granular insights and inferences. For example, you can ask “Why are you returning this item?” and provide a list of multiple choice options for each individual product SKU.
Customize each answer choice to gain full transparency. Options such as “it was too large,” or “it was too small” inform you of the exact reason for the return. Or, you can choose to get creative with the survey and ask more robust questions to suss out the truth.
Don’t be afraid of asking the tough questions. Both “the product was not as advertised” and “the product isn’t true-to-size” are questions that will help you evaluate overall product quality.
For example, you can sort your return data to determine why individual SKUs get returned. You can also evaluate how often various brands’ items get returned.
For example, suppose 100 people return miscellaneous items from one of your brands – citing “the product isn’t true to size.” This indicates a possible issue with the overall brand’s sizes. With this insight, you may choose to redo your product descriptions with a simple disclaimer: “typically runs a size smaller.”
Sometimes flukes happen as well: some items get sized incorrectly – or a customer decides they just don’t enjoy the quality of the product even though there may be nothing inherently “wrong” with it. However, if you find that customers repeatedly cite issues of poor quality in regards to individual brands, this tells you that you need to switch suppliers, vendors, or manufacturers.
The truth is, there are many reasons for returns. And Loop’s automated survey system can help determine exactly what each problem may be.
Another thought to consider: If customers returning products consistently report that the product wasn’t true-to-size or wasn’t as advertised, this might indicate that you need to revisit your product descriptions. It could also mean that you might want to also re-evaluate your graphic and instructional design.
For example, if customers consistently voice complaints about size, consider adding a size chart on your site if you don’t have one already (which you should).
If you do have a size chart, determine if it’s accurately describing the product(s) in question and if it’s comparing the product – fairly – to inch measurements in height, circumference, and length.
One last thought: consider asking customers if the product(s) arrived damaged – or even, possibly, if the customer received the wrong item.
If you notice that either certain brands or certain items reportedly arrive damaged, you can question the brands from whom you buy in regards to their shipping and inventory processes. Or you may need to review local last-mile delivery services, if products frequently arrive broken or damaged in specific regions.
Don’t take offense when customers ask for refunds – treat it as an opportunity to better understand both your target market as well as each of your individual products.
With an automated returns survey, you gain instant clarity into customer pain points as well as overall buyer motivation. Understanding your customer’s journey more holistically contributes to stronger Customer Experience.
Using returns data, you can also synthesize whether or not customers are satisfied with overall product quality (such as material and durability) at the SKU level. As an example, say you sell a variety of jeans brands, but notice that one brand has a higher return rate than others.
If customers frequently cite “product was poorly made,” it’s easy to surmise that it’s a quality issue. But even if customers aren’t as direct about why they’re returning the product, the data is telling you that it’s time to have a talk with your supplier or manufacturer; or, maybe it’s time to consider another vendor.
Determining whether or not people like a product at the individual SKU level also helps you assess if the company you’re buying from/working with isn’t providing quality products in general – or if some individual products, themselves, are troublesome.
But this isn’t a bad thing! Having these insights empowers you to cancel or change your orders – or even to switch manufacturers/suppliers. Each decision contributes to recouped revenue by using your own returns data to streamline supply chain and inventory.
Lastly, surveys are so granular that they always consider individual customer experiences. If people are telling you that one of your products is made poorly, it doesn’t matter what you or your supplier think.
What matters from here is providing a solid customer experience and saving the sale by offering an exchange – or even a return. Remember: 95% of customers will buy from you again if you offer a seamless returns process. While quality assurance checks help you identify the right suppliers, it also helps to preserve revenue streams.
By unifying your Shopify data with Loop, you get more than just an automated returns/exchange process. You also learn which items you should cut from inventory – and which you should sell more of.
Additionally, Loop offers the transparency you need to determine which channels are your most lucrative. The returns data can show you all the channels that each of your come from: drip campaigns, organic search – and all your paid media ads.
Most importantly, it reveals which channels have the highest and lowest return rates.
On one hand, using Loop gives you data reporting and provides attribution information as well as channel performance data. On the other hand, you can flip this data on its head and glean where to allocate spend and where to cut. Or, possibly where to refocus marketing efforts.
For example, if your data shows that a recent promotion performed better on Instagram rather than in drip emails – for the exact same products – you might examine what’s different between email and social messaging.
Could the copy be stronger? Is the CTA not as clear? Or – if certain channels have higher returns than others – are you targeting the right buyers in each channel? Having full transparency into returns data will allow you to evaluate each channel’s return metrics, thus empowering you holistically to comprehend your marketing strategy, spend and channel attribution.
Loop does more than automate the returns process for ecommerce brands.
It empowers you to leverage your Shopify data to gain macro and micro-insights into customer behavior. Loop’s automated survey system helps you instantaneously determine why a customer is making a return – and, more importantly, why.
Book a demo today to see how Loop can help you optimize return costs and retain more revenue.
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With Loop, your brand can offer everything from refunds to direct exchanges to shopper incentives and more. Even better? These exchanges build your business.