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FlyCode — Stop losing revenue to failed payments on Stripe
FlyCode's payment optimization and failed payment recovery technology is powered by ML and AI to stop payment failures before they happen, recover lost revenue, and reduce passive churn. Start increasing revenue today with zero integration!
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@jake_vacovec @etai @ynextz few of the founder friends are now irritated by service and loss of revenue by Stripe, will definitely share this. A heating usecase I think
All the best for the launch 🚀
@jake_vacovec @etai @ynextz Huge congratulations on the launch! Wishing you all the success in the world. What feedback have you received so far?
@kjosephabraham thanks. Good feedback on the onboarding and clear ROI
@etai @ynextz @prad_vv much appreciated! My calendar is open to anyone to share strategies to improve whether or not they move end up using us https://calendar.app.google/Huyu...
Launching soon!
@jake_vacovec @etai @ynextz Wondering about integration - besides Stripe, do you have plans to support other payment processors in the future? It could be handy for businesses using multiple platforms.
I read through the website and one of the case studies, and I bewilders me that a really good payment recovery product can improve revenue by that much! It makes sense to me that the model can leverage customer’s historical payment data to make decision on when, how often the system will retry payment and communicate. I’m curious to learn more what separates FlyCode from other payment recovery apps out there? Is the background retry without communication the real game changer?
Congrats on the launch @ynextz and team!
@tonyhanded the game changer is how the models/agents work together. It's a very complex problem behind the scenes to solve when treating each customer and their payment issues uniquely, especially because they often change mid-recovery. Part of what separates us from others is that we started FlyCode when more sophisticated AI/ML capabilities were available, which allows us to be far more dynamic and customizable in our approach.
Hi Tzachi, Jake, and Etai! FlyCode's Stripe app sounds like a game-changer for businesses dealing with failed payments. It's impressive how you've tackled such a common pain point. How does the ML/AI component adapt to different types of payment errors?
@web3_antivirus the models/agents work together and it's because of this that it can dynamically adapt mid-recovery when for example an error code changes, billing details are updated, or even a backup payment method is substituted. There are also limits set by the networks so the adaptability is as much of a safeguard as it is a competitive advantage.
The Stripe app looks solid, and I love how it handles failed payments without spamming customers with emails on every retry. Makes total sense to automate recovery in the background and focus on getting revenue back faster. Curious tho, does it work well for smaller businesses too? Would love to know if there's any upfront setup needed. Thanks for sharing this!
@danielharrison we help businesses of all sizes. The automation value proposition for smaller businesses is critical as they can shift resources toward revenue generating activities instead of revenue saving ones. The set up takes 5-10 minutes max. We share a DNS record and confirm Stripe settings and you're ready to go!
@sr24 Sure. You go to our app at Stripe here: https://marketplace.stripe.com/a... and install it. that's it (no dev work from your end)
Hey Tzachi,
How well does the solution handle international transactions, particularly with varying payment gateways?
Congrats on the launch!
@kyrylosilin the models take into account the different payment gateways authorization rate and the local time of the customer. Happy to show you how it works. Feel free to DM me or email us hello at flycode thanks!
When using Stripe for payments, the transaction will only fail if the bank card triggers the risk control model. How do you manage this?
@bensongao One of the biggest challenges is that payment providers, issuing banks, and card networks do not have unified error codes and write their own risk-rules. Each may have errors classified into different categories, which adds complexity and leads to many errors getting bucketed together, such as ‘Do not honor’.
We built decisioning models, taking into account payment metadata and internal classifiers of error codes, as well as an email product that coordinate emails and retries per transaction.
With FlyCode you can recover more payments with (1) the least number of retries (2) as quickly as possible and (3) with the fewest customer communications (4) compliant with the Card networks rules (5) coordinate the communications with the retries automatically for each customers payments. On top of that, solutions like Card Account Updater (CAU) and Network Tokens help to replace old details like expiration date automatically.
@bonvisions we can definitely get you set up! It takes a 5-10 minutes of effort from you and we handle the rest.
The idea of increasing MRR and LTV on autopilot is super appealing. It seems like that could make a big difference in recovering lost revenue!
The ability to recover lost revenue is a huge benefit i have lost a lot of sales due to failed payments
@jone_denherder nothing is worse than closing deals only to end up chasing them months later for a new card.
Tailoring retries to specific customer patterns is a great way to ensure payments go through smoothly.
Intriguing solution for Stripe users. How effectively does FlyCode's AI predict payment failures? Zero integration is appealing, but I'm curious about the accuracy rate. Would love to see concrete data on revenue impact and churn reduction. Passive churn is a tricky problem - interested to know how FlyCode's approach compares to manual recovery efforts.
@andyroamer thanks. Our product is ROI based and directly design to improve your recovery rate % MoM. Happy to saw you how it works. For case studies you can see more here: https://www.flycode.com/case-stu...
Congrats on the launch 🚀 Absolutely love the zero-integration Stripe app!
@antonzag shoutout to Stigg, a great product for the modern enterprise billing stack
The fact that you’re using AI and ML to stop payment failures before they happen and recover lost revenue is truly impressive. It’s a game changer for businesses looking to reduce passive churn effortlessly. Best of luck with this innovative solution.
FlyCode’s zero integration model is brilliant but an idea to make it even more impactful would be to add a predictive analytics feature that forecasts potential future payment failures. This way businesses could take proactive steps beyond just recovering failed payments.
@alexandergreen we actually have this feature already : ) we help segment which customers have high vs. low risk of failure and the outcome. This helps companies analyze where higher vs. lower quality customers are acquired from, their characteristics and even the types of product/offers that are attracting them.
@ynextz @haris_gul we localize to adapt to different geo's and languages! We support the vast majority of global payment systems and if a specific one isn't we can quickly add it for a customer.
Launching soon!
@jake_vacovec that's a great way of handling it. Also If you have a moment, please hover over the 'Coming Soon' badge next to my name and click 'Notify Me' on InterWiz AI—I’d appreciate your support and look forward to your feedback when we launch!
FlyCode Stripe app for Failed payments