You can’t manage what you don’t measure

It’s not really a sale until a customer decides to keep it. Returns add up to almost 12% of revenue lost each year, on average, with an even bigger hit to profits. But retailers don’t really know the causes of those returns, their impact on conversion and how they affect customer profitability.

Every click the customer makes before they buy is scrutinised with digital analytics tools, whereas the causes of returns are typically assessed from a few codes on a returns form. Marketing efforts may actually drive up returns and costs. And effort gets focused on tackling the symptoms – not the causes. This impacts customer experience and lifetime value.

Returns can only be managed and reduced once they are measured and understood – which is where the Clear Returns Intelligence Console fits in. We measure the keep, not simply the sale and incorporate costs and gross profit. Meaning you understand how product, marketing, suppliers and customers are really impacting your business performance.

And once fully understood, returns can then be reduced without impacting top-line growth. This means increased profits, improved marketing efficiency and increased customer loyalty.

You wouldn’t run you sales and marketing activities without data – so why ignore the more critical information of all, what your customer actually keeps

Schedule your returns intelligence demo now!

It’s not you, it’s me.

How customer behavior is the biggest influence on retail return rates

When I founded Clear Returns, I did so in the guilty knowledge that I return at least 70% of what I buy. The purchase is only the start of the process for me – my buying decision only really starts when the goods arrive. And then the bulk of my order almost inevitably goes back.

As a data analyst, I knew that if enough others shopped liked me, then the numbers on which retailers base their marketing, policy, and stock buying decisions are fundamentally flawed.

Five years on, this company’s ability to predict and prevent returns continues to astound me. The only thing I underestimated was the extent to which the problem would worsen and the impact that would come have on retail profits. Many ecommerce retailers just experienced their highest return rates ever, and for some that is jeopardizing their commercial survival.

And yet, still, when the retailer thinks about tackling returns they typically look at product, fit, images, and operations. They assume the cause lies with them and can be fixed in the supply chain.

The critical question should really be

“did my customer ever intend to keep their purchase?”

Why? Because 75% of returns come from shoppers who may never have intended to keep all their order, they were simply choosing at home – often in direct response to marketing efforts that encourage them to do exactly that.

 

Why customer intent matters

Whether a shopper intends to keep or return their order is a highly complex, but highly predictive indicator.  And the proportion of “keepers” vs “returners” in the overall base of customers determines not only the likely return rate, but also stock efficiency and overall profitability. This is a worked example, based on real patterns, for a clothing retailer making £5.2m of ecommerce sales:

 

 

 

 

 

 

A keeper may still return – usually because something went wrong with the process or product. But they spent what they could afford and intended to keep their purchase when they made their buying decision.

A returner, on the other hand is likely to spend more and buy more often than a keeper – because they do not intend to keep everything they buy. They may overspend in response to discounts or to get free shipping. They are making their purchase selections at home – a very costly behavior.

As more of this group appear in the customer base – and the overall proportion of keepers falls – return rates and returns costs rocket. BUT, total revenue grows too. So, at first glance these returners seem like great customers and marketing attention flows towards them. Returners nearly always push keepers out of ad targeting and high priority segments, because they are responsive and spend more. But they can be less profitable than their keeping counterparts once costs are factored in. This gets compounded if stock is unavailable for keepers to buy, because it is locked up with high returners.

Unless a retailer has visibility on the costs of returns and the split of “returners” vs “keepers” in their base, their efforts to grow revenue can ultimately make the business less and less profitable.

 

 

 

 

 

 

 

 

 

 

Forget fit, focus on customers

The current fixation on fit and size is not going to transform retail return rates – you’re preaching to the choir when you focus remedial efforts on those who intended to keep anyway. Especially if at the same time your marketing efforts are disproportionately aimed at returners.

75% of refunds are typically coming from customers who didn’t intend to keep their whole order. And that is not necessarily bad. These returners include your most valuable shoppers of all, but they also include customers who cost you money every time they buy.

At Clear Returns we know the customer is the most significant place a retailer should focus in order to make significant improvements in return rates. Talk to us now about optimizing your retail business for keeps.

Returns policy personalisation – why one size never fits all

Many of the retailers Clear Returns indexes have just had their highest returning season ever. This doesn’t just damage profits, it hits customer experience and future revenue too.

The problem has become too big for retailers to ignore – which is why there has been a recent flurry of changes to overly generous returns policies.  John Lewis, for example, recently reduced its policy from 90 days to 35 days – a commercial necessity in an environment where a product cycle may be as short as 8-12 weeks. Other retailers e.g. Nordstrom and LL Bean, are rightly asking the question around whether it is sustainable to continue their free shipping and, “return anything you want, when you want to” policies, in an environment where returns rates are 30%+.

 

Returns have a disproportionate impact on the bottom line, so reducing a return rate by just 1 percentage point can boost gross profits by 1.6% and operating profits by a massive 15%.

 

At Clear Returns, our ground-breaking returns technology has helped retailers understand that returns are a fundamental, but overlooked, component of online shopping, and that different customers respond to returns in different ways.

Some shoppers happily buy first, choose later – their high returning behaviour is costly, but it doesn’t impact loyalty.  A very small minority abuse returns policies by returning worn, fake or stolen stock, or by deliberately damaging product – the retailer and the rest of their customers pay a very high price for this. Then there are the customers who hate to return and only do so if the retailer messes up – if they are not identified and treated differently to the ambivalent returner, they will likely take their business elsewhere.

A one size fits all approach to returns policy and customer service isn’t helping customers or the retailer, and is the area where there will inevitably be seismic shifts in thinking in the coming year.

 

The biggest challenge is knowing where to start. This is why Clear Returns now offers ecommerce and multichannel retailers a standalone Returns Insight package as a roadmap.

 

  • Uncover the real drivers behind your returns so you focus spend and effort.
  • Learn how your business compares against the industry so you can judge urgency.
  • Get robust data on the costs of returns to your business, and their impact on profits and customer experience, so you can measure the cost of inaction and identify priorities.
  • Understand your core groups of customers in terms of their attitudes and sensitivity to returns, so you can plan a more targeted service and policy approach.
  • See the areas of returns improvement and keep optimization that your competitors are already addressing.

 

Returns are not inevitable or unavoidable – if measured and understood correctly they can be managed and reduced, resulting in increased profit and increased customer satisfaction and loyalty. With Returns Insights you’ll be on the path to tackling the real causes of your returns in just 6 weeks.

 

How to ‘rescue’ your customer after a return.

Thunderbird’s Tracy Island in 1992, Buzz Lightyear in 1996 (and again in 2010), Tamagotchi in 1997, Furby in 1998 and Bratz Dolls in 2002 – all the ‘must-have’ toy for Christmas. For retailers and manufacturers, it is notoriously difficult to predict which toy will surge in demand in the few weeks before Christmas and they will be frantically reordering and restocking to try to maximise sales at this crucial trading time.

This year the much-hyped Christmas sensation was the “Hatchimal”, (rrp £59.99) an interactive furry bird that hatches from a plastic egg and responds to children’s affection with flashing eyes and sounds, to the delight of the recipient.

Only, in many cases, it didn’t!

Unsurprisingly many, many disappointed parents of disappointed and upset children have expressed their frustration on retailer’s website review pages and on social media. Often, having invested considerable time to track down this toy, as it became scarcer and scarcer in the run up to Christmas, they have spent an emotional Christmas Day with a child who had a less than ‘magical’ experience with their lifeless gift.

Cue ‘Dead Hatchimal Owners United’ a Facebook ‘support group’ where exasperated customers have shared their experiences to try and find a resolution. And, despite the frustration, most customers have been reasonable: –

“I know stuff happens and as long as the company takes responsibility and addresses the issue, I have no problems. I write many reviews on websites, including many social media sites…. I will say I had a problem and the company resolved the problem to my satisfaction” Facebook

However, customers are less understanding when they feel that their problem is not handled correctly. One customer in the UK expressed frustration when a retailer responded to her tweet with a website link for tips and tricks on how to get the egg to hatch. She had already explained that she had broken the egg open, so not only was this unhelpful but exposed the fact that the retailer hadn’t taken the time to read her message. Since it’s likely that they couldn’t replace the item (most retailers are currently out of stock) and could only offer a refund, perhaps an apology would have helped or maybe a discount on her next purchase.

Most customers dislike returning purchases and a return can feel like the retailer has let them down and inconvenienced them. For some customers, a refund isn’t enough –they want a personal response and they want to feel valued. If they are angry they may go to great lengths to avoid the retailer in the future.

So, what happens when the problem product isn’t a ‘must-have’ toy like ‘Hatchimal’, with a peak selling period, but one that is steadily dispatched to valuable customers who hate the inconvenience of having to return? Clear Returns predictive technology can provide retailers with a product alert ‘early warning system’. This picks up products that are returning at a higher than usual rate providing retailers with an opportunity to investigate and correct the problem before it escalates.

In addition, Clear Returns ‘Returns Rescue’ solution alerts customer service to valuable customers that are ‘at risk’ following a return, prompting a personalised ‘save’ response.

Clear Returns award winning returns intelligence platform merges key data from ecommerce, stores, and warehouse systems to target, retain and serve customers. When the information is available, it makes sense to use it.

 

Think all returns are a good thing? Think again!

There are two statements from retailers that we hear at Clear Returns, which always raise alarm bells:

1) “We love returns”

2) “Our customers get more loyal the more they return”

Why the red flags? Returns are very complex – and the data almost never backs these statements up. Secondly, they assume that all customers are equally relaxed about returns and that high spend means high value.

Retailers need to understand the shopper’s intent at the point of purchase. If they dislike returning and intended to keep their purchase at the point of sale (and most shoppers do) then a return means the relationship is at risk.

Whereas if a customer intended to return all or most of their order when they bought it, essentially making their selection at home, or wearing and returning, the risk is that the basket profit margin is lost entirely and stock is unavailable to those shoppers who would have bought and kept it.

Assuming a fair returns policy and quick refund equals happy shoppers is not enough – for some shoppers that assumption risks customer satisfaction and future lifetime value. For returns sensitive shoppers, if they have returned an item, then you’ve really messed up in their opinion and a refund alone doesn’t cut it.

A personalised response, following the return, is essential to save the future relationship, which is where Clear Returns Rescue comes in. We focus customer service responses toward those who are most of risk of abandoning.

For example, a previously loyal customer who returns because the retailer has made a mistake, for example due to an error with their order, feels very differently about a return than a shopper who casually bought the same item in two sizes, as this customer explains: https://www.youtube.com/watch?v=csqIx86u7W0&t=78s

Some of the most common customer segmentation methods not only fail to spot the costliest serial returners, based on their spend, they place them amongst the most loyal and valuable customers. As a result, many retailers then actively prioritise their marketing spend towards customers who, once costs and profit margin are factored in, actually cost them more money every time they buy.

A small core of serial, high cost returners typically lock up stock, incur high costs and also draw in discretionary discounts and offers. So, despite their very high spend, they consistently lose the retailer money.

So are all high returners a problem? Not at all – “good” returners should be encouraged, as a return is a step that predicts they are on a path to becoming more profitable as they branch into new brands or categories and over time will begin to keep more of what they buy.

But telling the “good” and “bad” returners apart is simply not possible when analysis is focused solely on spend not profit.

Without the complex proprietary predictions at the heart of Clear Returns big data technology, that factor in customer profitability and sensitivity to returns, plus profit margin and stock availability, retailers can’t be confident that they have a handle on returns or understand the effect they have on an individual shopper’s future buying behaviour.