Butter raises $10M to combat failed payments

The Butter Team

May 13, 2024

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Customer Retention

Hairstory Customer Story

The Butter Team

May 13, 2024

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Hairstory, a DTC beauty brand, keeps 18% more subscription revenue 

Hairstory, the maker of New Wash, is a direct-to-consumer ecommerce beauty brand that’s redefining hair care and setting the standard for sustainable business practices as the first brand to exclusively offer a full recyclable product package. While New Wash captured the market, Hairstory was capturing market share. Since its founding in 2015, Hairstory has seen impressive revenue growth, with about 40% of overall revenue coming from their subscription business. Every subscription business understands the pain of failed payments, and  Hairstory was no different. Tim Moore, Head of Finance at Hairstory knows this well:   

“It's an incredibly frustrating problem because you're looking at lost revenue every single day from people who want to continue to receive your product and know that they're legitimate customers…just looking at that number day in and day out and that you're just missing revenue that otherwise would be money in the bank is brutal.” 

To maximize profits and their ability to drive revenue growth Hairstory knew it needed to address involuntary churn. Easier said than done. 

The path to increased profits 

Hurdle one: Billing migration caused disruption in payment processing and time-consuming efforts to only partially recover failed payments.

When Hairstory started out it was using a solution, Oscar, to manage its subscriptions and Stripe to process payments. Their first attempt at scale was a migration to Recharge. 

If you’ve ever done any tech migration, you know it’s complicated. Moving from Oscar to Recharge caused an influx of payment failures. The issue? Recharge wasn’t recognized by their payment processor. The interim solution? Manual downloads and uploads from Recharge into Oscar to successfully process those payments. This effort required hours each week to manually go through the list of failed payments to download, then upload to reprocess. Not a long term solution - and not effective either: this manual process only recovered some of those failed payments. Tim was looking for anything that would help them crack this problem. 

Hurdle two: Undelivered Dunning emails contributed to diminished recovery rates.

Hairstory wasn’t using payment retry alone. Dunning communications were running through Recharge: post failure a customer would receive a notification requesting payment update. If that update was made, a retry would be attempted. Even following this multi-prong approach, Tim highlighted he knew Hairstory wasn’t recovering all the failed payments they knew they could, ”a lot of people get a thousand emails a day and I'm sure that email is spam for a lot of people so, you're not able to really get that much lift from that.”

Hurdle three: Data overload and a manual retry process cost time and money, diminished profit margins and prohibited an optimized recovery strategy.

With payments you're dealing with a massive data set, across different systems, that aren’t built to deliver the insights needed to make the correct updates and effectively retry a payment. Making changes to retry schedules was still a manual guessing game for Hairstory, as Tim explained, “Recharge lets you select the Dunning cycle [to] retry a failure three times, four times, five times or six times. Basically, [that’s] the only input that you get, and I'm looking at a list of hundreds of failures a week - there's no good way to sort of wrap your hands around [are] there any consistency of the failures to understand what would work better? [It] requires a more sophisticated learning model to kind of just figure out what the best path forward is. We were getting some success from Recharge's native functionality, but their system doesn't really have any sort of nuance to it. You tell it I want to retry failures, three, four, five, or six times and Recharge will go and on weekly intervals at the exact same time of day just retry those payments and…just felt like there had to be some better way.”

Hairstory x Butter

What Hairstory was looking for was proven payment expertise to help drive increased revenue capture and financial performance, and a solution that could successfully automate and navigate the complexity of payments; something that just works. That’s when Tim came across Butter, “[Butter] was the first system that I had read about that directly addressed this problem.” 

Butter is a machine-learning (ML) payment optimization platform that creates an optimal recovery strategy based on your unique payment data—your offers, your customers, your payment stack, payment methods, timing of retries, and more— that is most profitable to you. And because of Butter’s native ML, it continuously optimizes your payment recovery and your overall payment health to maximize the amount of revenue delivered. “Butter very clearly addresses that issue by having an algorithm and a model that basically determines when is the best time to go and retry a failure. It was an easy decision, ” Tim stated about why Hairstory selected Butter.  

And Butter was easy to implement and runs in the background, automatically optimizing retry schedules to maximize profits for Hairstory, said Tim, “Honestly, it's [Butter] been very plug and play and I haven't really had to spend too much time trying to keep track of what's going on.” Within the first months Hairstory saw ROI working with Butter. Tim had done the napkin math—tracking incremental revenue and profitability, minus Butter platform fees. With Butter, Hairstory saw an 18% lift in revenue recovered over what Hairstory was seeing with Recharge, and Butter recovered failed payments 25% faster. 

“Yeah, I mean the biggest takeaway is that we are keeping more subscribers active and we are increasing our revenue every single month relative to what it would have been had we stuck with Recharge’s solution. So that is a huge win for us. I would recommend Butter. I think that it is just a much better way of capturing lost revenue than exists natively in recharge. I mean it's just a better way of capturing lost revenue from failed payments. “ — Tim Moore, Head of Finance, Hairstory. 

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