Why returns could be a blind spot for your customer lifetime value

Retailers are rightly focused on customer lifetime value as a means of segmenting shoppers, driving additional growth and ultimately adding profits to the business. However, there is a common issue for many retailers in the methodology they’re using to estimate the lifetime value of customers – they find it hard to account for returns. Here’s why that’s a problem, why it’s happening and how retailers can fix it.

Why returns needs to be in the CLTV calculation

Shoppers with a high propensity to return items are likely to show up as disproportionately valuable, but in reality will be incurring hidden costs that reduce their true profitability to the retailer. That’s because shoppers who return the most also purchase the most, whether that is because they are purchasing a variety of products and picking the one they like the most to keep, or because they are simply genuinely high-frequency, high-value shoppers who are also picky about what they’ll keep.

Statistically, 29% of all shoppers surveyed by Barclaycard admitted they order items they intend to return, and that number rises to 48% for the 25-34 year-old demographic. We also know that there is a segment of ‘professional shoppers’ with high purchase frequency and high net sales value who return items frequently. ReturnLogic data mapped out this high-value segment where return rates were around 32% - not as high as many businesses face, but higher than many would be comfortable with. However, these are the most profitable shoppers – they return a lot but the value and frequency of their purchases outweigh the cost.free returns ebook download

The problem group is the segment which is not bringing in high value baskets but is still returning at that rate. Frequent low-basket value shopping makes a 32% return rate much harder to stomach for retailers. Yet, if they cannot factor in the impact of that return rate to CLTV metrics, these customers will appear desirable and profitable even as they cost the business money and time.

If retailers can’t see which customers return which products and tie that to the rest of their lifetime value metrics, they can’t tell how much customer segments are really worth to them. That leads to marketing campaigns drawing in unprofitable or less profitable customers, at the cost of missing shoppers who may be more profitable. The cost of acquisition as a percentage of sales also increases.

Returns visibility is poor

There are several reasons retailers are finding it so hard to get returns data into their lifetime value reporting. Returns is typically seen as a cost centre, despite its clear impact on acquisition, customer experience and marketing. That has lead to a cost-reduction focus, where the impetus is towards reducing expenditure, rather than increasing investment.

As a result, many retailers still use paper-based, manual returns processes which make stock visibility and tracking slow and difficult, and prevent them from collating good data on returns, period – let alone tying this data to CRM data.

Digitising the returns process not only makes it visible - it makes it more effective

This lack of visibility can be addressed. By digitising the returns process, retailers not only get better data and give customers more options, they also allow the possibility of personalising their returns proposition to an individual depending on their value. This is already happening: Amazon targets high value customers and enables them to receive instant refunds on returns.

By using a returns platform which can be accessed through the retailer’s site or even through messaging apps, customers book their return and can then bring the product (unpackaged if necessary) to a store or drop-off point. Again, Amazon is leading in this area and has allowed customers to return package-less items in Kohl’s stores in the US and through Doddle in the UK.

Most importantly for retailers from the marketing perspective, making returns digital makes them visible and trackable. Customers can be grouped by their returns data and segments become much more closely aligned with actual profitability after returns are accounted for, which allows marketing spend to be more efficient.