Using Digital Transformation to Solve Pain Points - Customer Returns
By on 3rd Feb 2020
The fourth industrial revolution is moving forward at an unstoppable pace, so if the market demands the convenience of online shopping and delivery to their door, businesses must adapt.
Of course this comes with several potential problems for the consumer, there are many conveniences that a customer can access in-store that they cannot online. That said, should customers return to legacy ways of shopping, or should businesses innovate and use technology to eliminate the pain points?
A failure to adapt and just hope that consumers will change their habits can be foolhardy.
Sadly, due to the difficulting in judging fit and other product specifications online, one of the biggest problems facing businesses who conduct a large portion of their sales online is returns - according to Gartner, Americans returned $260 Billion worth of goods back to retailers last year, and less than half of those goods are re-sold at full price. Research on Oracle also states that 77% of people asked in 2019 planned to return at least one of their Christmas gifts.
Online retailers suffer the burden of customers returning items due to incorrect fit, poor quality, a perceived difference in style from the online photo, and those are just some of the legitimate reasons - ecommerce retailers have also identified a worrying trend called ‘wardrobing’.
This is when people order items online with no intention of keeping them - they might want to wear an item once for an event, or use it for a single instance.
There’s also a few customers who will likely order one item in multiple sizes and styles to try things on, with the intention of sending back items that don’t fit their needs. This is especially prevalent (and perhaps even encouraged by retailers) now many of them are adopting ‘buy now, pay in 30 days’ schemes like Klarna, which eliminate all financial risk for the customer.
However, it’s extremely important to remember, that although articles are quick to blame customers for a rise in returns, research actually shows that the majority of returns are the fault of the retailer, not the buyer. This is often down to retailers sending out the wrong item or wrong size, missing a deadline with a delay in delivery, the item not being as described online, or the quality not meeting the customer’s standards.
23% of returns are because the customer received the wrong product.
22% of returns are due to the product being not as described.
20% of returns are due to items being damaged or defective.
The process of customer returns are killing the profitability of businesses more than you might expect.
The first problem is that many ecommerce brands already operate on a very small margin, and might sell items which are already very cheap. If you are selling a dress for £10, and it costs the business £3 for return postage and £3 for the cost of production, you don’t have much to work with when you have to sell the item for less than the original price, because it is now off-season.
Items being out of date or off-season happens extremely quickly, with many retailers offering a ‘fast’ product, which is designed to sell out of inventory as rapidly as possible, to be replaced by new season stock. The law around returns for ecommerce means consumers have a full 14 days to initiate a return once they receive their goods, then a further 14 days to send the item back once the retailer has been notified.
High volumes of returns mean it could even take two further weeks before the item is registered as back in stock.
So how are retailers supposed to combat the problem of increasing customer returns? Let’s take a look at the solutions:
TrueFit, AI Suggestions and Big Data
TrueFit are a company to watch in the next few years. Our bet is that we’ll start seeing them working with most of our favourite online retailers.
The platform is designed for fashion and footwear ecommerce retailers, and it leverages big data for a project it calls the ‘Fashion Genome’. The idea is simple, TrueFit seek to create the world's largest data set of fit information for clothing and footwear. They can then use this data in tandem with AI to build a profile for each user, that helps them choose items that will best fit their personal measurements and body type.
As TrueFit grows, its algorithms will be able to learn and provide better recommendations based on the thousands of retailers providing garment data and the millions of customers providing fit data about those garments.
Chances are we’ll start seeing this technology in interactive dressing rooms in-store too.
AI Responses to Customer Orders
Using AI, programs can analyse the data from your sales and returns portals and quickly identify serial returners vs those who make returns legitimately. This data can then be used to block the worst offenders, but it can also be integrated with marketing automation platforms to avoid sending deals and offers that might provoke a return in people who are more likely to be dissatisfied with an impulse purchase.
Using AV screens, many brands are now creating interactive in-store and online systems that allow customers to see what an item might look like on their body. Even furniture stores are utilising AR apps to ensure that customers have a good idea of what an item might look like in their home prior to purchase - especially important for large bulky items, where the returns process can be extremely expensive to the retailer.
Click and Collect and In-Store IT Infrastructure
Using IT infrastructure, there’s a lot of potential for brands to make their returns process as simple as possible, which of course helps the customer, but most importantly, helps the brand save money on returns.
Click and Collect is probably the biggest disruptor in this space. Digitizing a click and collect process means returns are extremely convenient for the customer, as it’s much easier to nip to a local store or pick-up point and use a digital interface than it is to arrange a courier pickup or post office trip that fits around a customer’s daily schedule. Especially if they work a traditional 9-5.
Click and Collect offers another benefit to retailers - if the click and collect point is based in their own store, it’s quite simple to quickly put a returned product back out on to a shop floor; much easier than accounting for it in an online digital inventory. It means brands aren’t waiting for logistics infrastructure either, the turnover time is significantly reduced.
If brands equip their staff with handheld computers and tag their items with RFID, the item can be almost instantly accounted for as soon as it hits the return counter. Time is money after all.
Enhance Product Information Using Technology
We’re already starting to see more retailers enhancing the in-store experience with digital interfaces that offer detailed product information at the touch of a button. Customers can even scan the item, meaning they don’t need to waste time searching a database.
To limit customer returns, information is key. Customers need to be able to see every facet of their potential purchase to the same extent they can explore an item in-store.
Social signals are one of the best ways to do this. Seeing a product being used in the real world, and recommended by someone the consumer trusts can increase a customer’s likelihood to keep hold of an item.
Another technology ecommerce retailers should consider to reduce return rates is an omni-channel cloud contact centre. Having features like live chat and an active social media presence offers customers the chance to ask questions about items and get them quickly answered, lessening any mystery behind their purchase, and therefore decreasing the chance of a return.
Customers can even get frustrated and ‘give up’ on an item if they find it difficult to use, but if your company has an active support network with multiple contact options, customers may be able to solve their problems before they become disillusioned with the product.
Monitor Customer Feedback and Practice Continuous Improvement
Although most brands recoil at the thought of allowing customers to leave feedback and ratings on products, it’s actually been proven that brands who leverage this information go on to make much more optimised future products and listings, reducing return rates.
For example, if most feedback says that an item is not the colour they expected, retailers will know to provide clearer imagery and multiple forms of media for a product description, such as Instagram photos from customers and videos.
Can we help to stop your business losing money in the returns process? Streamline your supply chain with digital transformation. Talk to us today.
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