I was recently pondering on a problem experienced by one of our clients – and the apparel industry more broadly – how to maintain profitability with very high returns rates? As costs increasingly spiral, this is becoming even more important. Many ecommerce retailers have now started charging for returns, and the customer reaction has been rather negative. What about a mechanic to incentivise keeping goods rather than penalising for returns?
This blog posts explores ways to encourage higher basket sizes with intelligent discount mechanics. The application is much broader than returns, and so important in today’s challenged economic times: how can we protect profitability while giving value to customers?
We propose The Alpine Ridge Strategy1 – an increasingly stepped discount rate to build baskets. It is well known that customers love free delivery and will basket build to just over the threshold, but this builds an incentive to continue basket building beyond that point: providing cash margin for the retailer and cheaper goods to the customer. An example Alpine Ridge Strategy would be:
- Free delivery when you spend £40
- £5 off when you spend over £60
- £10 off when you spend over £80
- £20 off when you spend over £100
- You should carefully explore the interaction between promotions and returns rates, and how to nudge customers to items they won’t return
- Alpine Ridge Strategy is named for the road in Colorado’s Rocky Mountain National Park we were driving through as I debated the finer points of the approach with a good friend of mine who also works in eCommerce pricing.
Of course, there is nothing new here – stepped discount mechanics have been used intermittently by many retailers for years. What is important now is:
- We are operating in a highly challenging environment for both customers and retailers. Distribution costs – and the cost of living – are growing rapidly. Retailers who can give value to their customers and protect margin will win share
- The exact nature of the mechanic for your business requires great precision based on: distribution of basket sizes; gross margin by category; returns rate; share of wallet; customer frequency; expected customer elasticity and many others
Some examples of when the Alpine Ridge Strategy is best applied
| Times to apply Alpine Ridge | Times to be careful |
| High gross margin | High customer frequency and risk of ‘pull forward’ |
| High returns rates | Categories with lower than average gross margin (e.g. high priced electricals) |
| Low customer frequency or share of wallet | High spread of basket sizes – risk of ‘cannibalisation’ |
DVS are expert in understanding each of these and working with you to refine, launch and test your Alpine Ridge Strategy. We combine data analytics expertise with the strategic mindset to ‘think bigger’ and understand the wider implications for your business. We can support you to build a launch mechanic and also to measure the effectiveness and impact on your customers and profitability.