Tariffs are all the talk right now. And if there’s one thing “tariff talk” is doing, it’s putting the spotlight on unit economics.
More specifically, it’s putting the spotlight on product-specific unit economics.
And while plenty has been written about their impact, there is one aspect that has been under-discussed: once you figure out your supply chain and once you figure out your pricing, you have to figure out your merchandising.
After all, you can optimize your COGS on products all you want, but if people aren’t buying that product, then the optimization doesn’t matter so much.
Traditionally, it’s the larger brands and retailers who concern themselves with merchandise mix and basket composition. That’s why you often see product-specific sales with larger brands/retailers, but rarely see such a sale (outside of bundles/kits) from DTC brands.
It’s a practice DTC brands could start to use as a last-mile optimization for combatting tariffs. There are also a lot of other levers—outside of product-specific sales—that brands can be pulling.
One of the levers we’re excited about at Stamped (and have on our roadmap) is adding a “goals layer” to Repeat’s product recommendation engine.
That “goals layer” would allow brands to instruct Repeat’s product recommendations to consider certain variables that can impact a brand’s business (like featuring higher margin products, clearing excess inventory, featuring new products, or encouraging cross-category purchases).
Such an improvement would mean brands aren’t just serving recommendations to customers based on what they’re most likely to buy; they could be serving recommendations to customers based on what they’re most likely to buy while also helping the brand to reach a strategic objective.
While it’s an exciting roadmap item, the rest of the Stamped product suite can also serve as a last-mile optimization for unit economics.
A few months ago, we talked in this space about how Lilac St. uses a free gift to drive 90-day repeat purchase rates:
Returning customers who made a “free” purchase of the giveaway product returned within 90 days to make another purchase roughly more than 65% of the time. (Comparatively: Returning customers who weren’t making that same “free” purchase returned within 90 days 54% of the time.)
The free product for them, then, is a lever to improving 90-day repurchase rates. And at a 20% lift in 90-day repeat purchase rate, that can have a material impact on extending customer lifetime value.
A cool play for brands, then, could be to test giving a way a low cost, low margin product, and then bundle that product with higher cost, higher margin products to increase 90-day purchase rates while also capturing some of that “lost” margin from the free gift.
Another: Offer “points boosts” on products with better margins that don’t move as fast, therefore incentivizing customers to consider the under-appreciated products that are best for your business.
If either of these plays (or even the “goals layer” concept) are interesting to you, let me know. We can help you get set up with the loyalty plays and would love to talk to you about how you’d use these enhanced product recommendations.