Challenge

Invideo was founded in 2017 with a simple premise: to democratise video creation by making it easy for any user, regardless of experience, to create a professional-quality final product. The emergence of more powerful generative AI tools helped supercharge Invideo’s offerings, allowing users to create videos with as little as a text prompt.

As Invideo’s offerings gained traction with customers around the world, the company’s revenue soared, growing more than three-fold in 2024 from the previous year. However, that rapid growth put pressure on Invideo’s billing and payment systems. One major red flag was a rise in transaction failure rates as Invideo attempted to renew users’ subscriptions. That billing system also lacked the flexibility for Invideo to easily change its pricing and subscription models in support of its continued growth.

On the payment side, Invideo was experiencing challenges in authorisation rates for cross-border payments as its Singapore-based operations handled payments from more than 30 countries across Europe, Asia, and the Middle East; meanwhile, its US-based operations largely handled payments from North American customers. Invideo needed a more agile payment processing system to help reduce the complexity of these cross-border payments. At the same time, the company wanted to add more payment options to support the preferences of its global customer base – but in a way that didn’t require its development team to manage the integration process for each new payment option.

“Handling payment systems across the world is extremely, extremely complex,” said Sanket Shah, Invideo’s founder and CEO.

Finally, the company also needed stronger fraud management tools, as Invideo’s increasingly global operations opened it up to more potential for fraudulent transactions.

Solution

In late 2023, Invideo consolidated its payment and billing stack onto Stripe Payments and Stripe Billing. The company had used Stripe as one of its payment vendors since 2020, and its developers were impressed by the ease of working with Stripe technology compared to other vendors.

“We felt a notable difference mainly due to Stripe’s better support ecosystem along with its documentation and API support,” said Shah.

The move to Billing gave Invideo access to advanced features that could help reduce its renewal failure rates. For example, Smart Retries used machine learning algorithms trained on billions of data points across the Stripe network to help determine the best time to retry failed payments. The adaptable design of Billing – which supports various pricing models including usage-based billing – also provided a flexible platform to enable the continued evolution of Invideo’s pricing and subscription models.

Stripe Payments also helped Invideo address authorisation challenges and optimise payments across its user base, whether they came from customers in North America, Europe, or Asia. For example, Invideo gained access to Adaptive Acceptance, which uses machine learning technology to optimise authorisation requests and mitigate the potential for false declines. In addition, Invideo began using network tokens and Stripe’s real-time card account updater technology to address payment failure rates.

To further improve its frontend payment experience, Invideo also adopted the Optimized Checkout Suite, which includes embeddable UI components and the ability to turn on additional payment methods without having to complete individual integrations. The transition to the Optimized Checkout Suite allowed Invideo to begin offering Cash App Pay – which allows users to pay directly with a Cash App balance or debit card – and Link, which auto-fills customer’s payment information to create an accelerated and secure checkout experience.

For improved fraud management, Invideo implemented Stripe Radar for Fraud Teams. Radar’s machine learning–powered fraud prevention is trained on transaction and fraud data from millions of global companies on the Stripe network to more effectively block fraud attempts while allowing legitimate transactions. After implementing Radar for Fraud Teams, Invideo worked with the Stripe professional services team to analyse its fraud metrics and develop custom rules that specifically evaluate users’ IP addresses and billing locations, as those are indicators of fraud Invideo has seen in the past. This helped Invideo increase payment success and reduce fraudulent transactions, with a particular focus on first-party abuse such as friendly fraud. Stripe professional services also helped Invideo implement dispute deflection, including Verifi and Ethoca, which enables issuers to identify and block fraudulent disputes before they are made.

Results

Completed migration to Billing in one month

The process of migrating customers from its old billing platform to Billing took roughly one month. A key factor in that fast transition was the clear support and documentation Stripe provided to Invideo. “That made for a seamless migration,” said Shah.

The flexibility of Billing is also now giving Invideo the ability to adjust its subscription models. For instance, the company is exploring the option to add usage-based models to its tiered subscription plans. For SaaS companies, it can be challenging to balance the need for revenue with the goal of having users actually use the product.

“There is so much zombie SaaS revenue across the world that the right and fair thing to do is charge for usage,” said Shah.

Failed payments recovery rate improves by 30%

Stripe Billing optimisations such as Smart Retries improved Invideo’s failed subscription renewal recovery rate from 23% to 30%. That improvement also enabled Invideo to replace another provider of dunning software.

“It made no sense to have multiple tools and reporting systems,” said Shah.

Payment optimisations drive more than $1 million in revenue growth

The addition of optimisations such as Adaptive Acceptance, network tokens, and the card account updater improved authorisation rates and generated an increase of more than $1 million in revenue across Invideo’s Singapore and US entities. That represents a year-over-year revenue uplift of 4%.

Nearly 40% of transactions occur via Link

Transitioning to the Optimized Checkout Suite has made it easier for Invideo to add new payment methods, saving Invideo “thousands of hours of developer time,” said Shah. Since going live, Invideo has processed 37% of its transactions via Link.

Improved fraud management saves more than $1 million

With Radar for Fraud Teams, Invideo has complemented Radar’s machine learning with custom rules specific to the fraud scenarios its business faces. This has given Invideo a more powerful way to reduce transaction fraud. As a result, Invideo’s US and Singapore entities have realised combined savings of more than $1 million in one year by accurately identifying and blocking fraudulent transactions.