The critical customer insight gap that is killing retail profits

The most dangerous information gap currently facing retailers is a robust and realistic view of why a customer really returned their purchase. Not why they said they did. Or why you suspect they did – but robust, quantifiable and most importantly actionable insight.

Ecommerce return rates of 30% to 40% are common for some retail categories, with tens of millions of pounds of stock locked up every day for large retailers. It is not a sale until the customer decides to keep it. But whereas pre-purchase literally every click the customer makes is scrutinised, the causes of returns are typically assessed from a few codes on a returns form, along with an organisational assumption of the product or delivery likely being at fault.

The purchase to return insight black hole is intimately connected to damaged profitability. 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%.

Returns are not inevitable or unavoidable – if measured and understood they can be managed and reduced, resulting in increased profits and increased customer satisfaction and loyalty. And once fully understood, they can be reduced without impacting top-line growth.

But trying to solve the problem without deep insight around cause and customer motivation is inefficient, speculative and risks that the customer’s profitability is jeopardised.

Specialist returns insight is essential, because this is a highly complex interplay of customer, product and marketing causes requiring cutting edge big data analytics. Clear Returns have done nothing but returns data modelling and analysis for almost 5 years and we’ve learned a few important things I’d like to share for those thinking about tackling this in house.

With the DIY approach to returns analysis, 3 things typically happen:

  1. The retailer usually looks to the product and its depiction first – because looking to the customer is far harder and complex. Low hanging fruit can be found, but change can be slow and insights can’t usually be generated and actioned fast enough for a big commercial impac
  2. A lot of effort then goes into attacking the symptoms not cause – eg fault testing, new returns reason codes, delivery or policy changes, sizing and fitting room technologies. This can be costly, time consuming and yet the ROI remains elusive. You’re very busy dealing with returns but still not seeing those efforts translate to the bottom line
  3. Most marketing efforts continue to focus solely on the sales conversion without realising the real point of purchase – the new final stage of the sale – is the keep/return decision that is made in the customer’s home. Therefore marketing efforts can drive returns even higher and profitability downwards. And at the same time, there is often internal resistance to targeting for keeps or enforcement of returns policy in case you’ll damage the top line and send customers elsewhere.

Not true……you can improve both the top line and operating profits if you truly understand the causes and impacts of returns.

We’ve learned – after trillions of data points and hundreds of thousands of iterations of our predictive models – that the secret to solving returns and boosting profits is shedding illumination into the knowledge black hole that represents the customer and product interplay that occurs between purchase decision and return decision.

Clear Returns uniquely and specifically focuses here because prediction and very early warning means that once fully understood, returns can be strategically and proactively managed to boost customer profitability without impacting top-line growth.

Talk to us to learn more about Clear Returns Insights and data technology – Our CEO Vicky Brock will be demo-ing in London on the 8th and 9th February so drop us a note if you’d like to meet up!

 

 

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.

Why is Black Friday making retailers blue?

Originating in the U.S. as part of the Thanksgiving holiday celebration, Black Friday discounting arrived in the U.K. in 2013 via Walmart affiliate, Asda, and, as other retailers followed suit, has quickly become a key date in the UK shopping calendar, with electronics and fashion items especially popular. This year it falls on the 25th November with bargains available online from midnight, but for retailers the one day shopping bonanza is not entirely welcome and debate continues about the sustainability of this annual event.

In the U.S., where it all began, there is concern over Black Friday ‘creep’ in which the focused day of shopping after Thanksgiving has begun to spread into Thanksgiving itself as retailers attempt to win as much market share as possible. Others, such as Mall of America are making a virtue of closing on Thanksgiving, showing respect for the holiday and for their employees, to win public approval. Sports retailer REI will close on Black Friday itself, encouraging customers to “#optoutside”, and hopefully make their purchases for ‘opting outside’ throughout the rest of the month.

In The Guardian newspaper, David McCorquodale, head of retail at KPMG, explains the negative impact of building up customer expectations for a big discount day at the end of the month – “Last year, Black Friday was bigger than Christmas, with promotions running over four days, so people are holding off spending and that diminishes retailers’ sales in the weeks before and after”

In the U.K. retailers are aware that it is a difficult trend to reverse with so much revenue generated in one day. Fashion retailer Jigsaw, not wishing to participate, but recognising that there is customer expectation, has explained their position in their pricing manifesto. By sticking to traditional bi-annual retail sales they hope to reassure their customers that the quality products bought at full price one week will not be slashed the next and that reductions in the sale will be end of season stock only. Ted Baker boss, Ray Kelvin, was quoted in Retail Week saying “No-one wants Black Friday” – they would prefer not to be involved but their concessions in participating department stores makes it difficult for them to avoid.

The concern, particularly with fashion retailers, is that customers have been educated to expect discounting when they could previously rely on full priced sales, and to maintain momentum up until Christmas, promotional discounts will need to continue throughout December. With the weak pound affecting consumer confidence, customers are also more likely to be seeking out bargains and shopping around for the most competitive prices.

Also, heavy traffic in stores – sometimes requiring crowd control measures – resulted in an increase in online shopping in 2015, putting pressure on websites (slow or crashing) and pressure on distribution centres across the country. In addition, the spike in sales produced by the ‘flash sale’ nature of Black Friday also resulted in a spike in returns adding to supply chain pressures with extra handling and fluctuating stock levels.

As Vicky Brock, CEO of retail technology firm, Clear Returns, explains “The result is businesses frequently face a period of time in which they are short of stock while it is out in the supply chain or being considered by customers. The challenge with Black Friday is where it sits in the year – that final weekend of November. Typically, the cycle of returns becoming available to sell again is 15 to 21 days, so that stock, if everything went well, would just about be re-available to the retailer to sell on 20 December – past peak Christmas trading.”

As Black Friday looks set to remain a prime shopping day, and spreads around the world – Souq.com in the Middle East runs its version ‘White Friday’ and Alibaba in China has the massive Singles Day – it seems unlikely that this trend will reverse any time soon. So how do retailers retain their most loyal and most profitable customers and avoid a deluge of costly, margin-shredding, returns at their most important trading time? Retailers can reduce the impact if they think carefully about the products they are promoting – returns are higher risk in certain categories and sub-categories than in others. They should also consider that products are likely to go out of stock as a consequence, and, considering customer time to return and the retailers processing time for returns, unlikely to become available for sale in time for the Christmas peak. Future sales to customers who would keep these purchases are then lost and the returned stock ends up in the post-Christmas sale, with a low margin and all the added operational costs – including premium Christmas delivery and expensive warehousing.

Clear Returns award-winning predictive data technology focuses marketing on the customers who will keep their purchases. Keep optimisation is a solution that eliminates marketing driven returns by encouraging costly customers, who sit on premium stock, away from these purchases towards products they will keep and releases the stock for profitable customers thereby preventing returns, reducing costs and increasing margins.

Everyone knows a serial returner

Why are retail returns such a great conversation starter?  I start by telling someone about my new job at Clear Returns and invariably receive a response such as “You should speak to my mum, she orders stuff constantly, keeps nothing, returns the lot”.  It seems everyone knows someone who is a serial returner.

 

Customer-focused retailers have educated and incentivised this behaviour, with free shipping and returns and direct mail campaigns with sales, promotions and voucher codes.  Now they are waking up to 1 in 3 items being returned and all the associated loss of profit margin, operational costs and fluctuating stock levels.

 

When I talk to my friends about their online shopping intent, they reflect back the shopping behaviours retailers have encouraged:-

 

“When  I buy from ASOS, I’ll buy much more than I’m intending to keep as if you spend over a certain amount, you get free delivery. And I like trying it on – even though I don’t keep it!”

Jo, Glasgow

 

“Emails with extra discount always good….Nike are great for it. Usually order a couple of sizes as can’t be bothered doing an exchange. Order much more than I ever keep!”

Nina, Glasgow

 

“I’ve just bought a dress for black tie event – ordered 6, kept 1”

Jen, Edinburgh

 

“I also buy items in different sizes, and return some/all. I’m a sucker for a sale.”

Lesley, High Wycombe

 

“Love click & collect too! To return stuff. Won’t buy if returns not free”

Lindsay, Glasgow

 

For some customers though, returns are just an inconvenience-

 

“I buy everything online and usually not more than one of the same thing cause I hate having to go to the post office to return it.”

Kate, London

 

But there are also products that customers never, or rarely return-

 

Ever return beauty stuff? “Nope because I always buy the same brands”

Lisa, Glasgow

 

“Homewares is a different scenario altogether. You know exactly what you’re going to get cause you’ve seen it in nearly every shop but can’t be bothered carrying it around. Home-wares 0% return”

Julie, Dundee

 

Now imagine, a retailer having this level of insight on every customer who buys online. Instead of marketing campaigns focusing on sales only,  products can be targeted to the customers that will keep them.  Because it’s not a sale until the customer keeps it.

 

Using big data analytics, Clear Returns matches customers to the products that they keep, reducing returns and saving profit margins.  Clear Returns can predict, before the point of purchase, the likelihood of the customer keeping the product with 96% accuracy.   

 

So not only will the retailers reduce costly returns but they will increase personalisation, improve the lifetime value of their customers and ensure that stock is available for the customers that will keep what they buy.  

 

Kay YoungKay Young
Senior Account Manager
Tel: 0141 554 4175
Email: Kay@clearreturns.com