Split and AB Tasty both offer feature management and experimentation capabilities to optimize digital experiences.

While Split focuses on feature flags and observability for product development teams, AB Tasty provides a broader suite of tools for web experimentation, personalization, and AI-driven optimization across various industries.

What is Split?

Split is a feature management and experimentation platform that enables software development teams to release features faster with less risk. By decoupling deployment from release, Split allows teams to ship updates more frequently while instantly detecting the impact of every feature they release.

The platform provides feature observability, which powers automated rollout monitoring and A/B testing capabilities. This eliminates guesswork and enables product development teams to make data-informed release decisions and continuously improve their features.

Split's core offerings include:

• Feature flags: Deploy code when you want and release when you're ready

• Targeting rules: Gradually release features to segments of your user base

• Automated rollout monitoring: Detect issues during progressive delivery that traditional monitoring tools can't catch

• Feature experimentation: Test in production and make changes without pushing new code

Split's Feature Data Platform is designed to solve specific problems for complex and highly regulated organizations. It ensures governance, flexibility, and automation of processes across industries such as financial services, healthcare, media, and software.

What is AB Tasty?

AB Tasty is a digital experience optimization platform that helps businesses improve their online presence and drive growth across all digital channels. The company offers a comprehensive suite of tools designed to enhance user engagement, increase conversions, and maximize return on investment.

AB Tasty's platform provides a wide range of solutions for businesses looking to optimize their digital experiences:

• Web experimentation: A/B testing capabilities to make data-driven decisions and reach conversion goals

• Feature experimentation: Test new features and functionalities with targeted user segments

• Personalization: Create tailored experiences for each individual to boost engagement and loyalty

• AI-powered recommendations: Deliver relevant product suggestions to enhance the customer journey

• Intelligent search: Improve product discovery and search experiences with AI-driven optimization

With over 13 years of experience, AB Tasty has become a trusted partner for more than 1,000 brands worldwide, including notable names such as Clarins, L'Oreal, Sephora, Club Med, USA Today, and Eurosport. The company's success is built on a foundation of collaboration and a customer-centric approach, working closely with clients to achieve their optimization goals.

Pricing comparison

Split offers a flexible pricing model with a free plan and paid plans starting at $35 per seat per month. The free plan includes basic feature flag capabilities, while paid plans provide access to all features and scale based on monthly tracked keys and events.

AB Tasty's pricing model is not explicitly stated on their website. Pricing is likely custom based on each customer's specific needs and usage requirements, so interested businesses would need to contact AB Tasty directly for a personalized quote.

Considerations and limitations: Split

Split is well-suited for complex and highly regulated organizations that require governance, flexibility, and automation of processes. The platform's advanced feature management, observability, and experimentation capabilities make it an ideal choice for teams in industries such as financial services, healthcare, and software. Split's architecture, designed for performance, security, and resilience, ensures that it can handle the unique challenges faced by these organizations.

However, Split's focus on specific industries and use cases may limit its applicability for teams with different requirements. The platform's extensive feature set and advanced capabilities could be overkill for smaller teams or projects with simpler needs. Additionally, the scalability of Split for large-scale deployments may be a concern for some organizations, as the platform's performance could be impacted by the volume of data and the number of users.

• TL;DR: Split is better suited for complex, highly regulated organizations that require advanced feature management and experimentation capabilities, but may not be the best fit for teams with simpler requirements or concerns about scalability for large-scale deployments.

Considerations and limitations: AB Tasty

AB Tasty is a comprehensive digital experience optimization platform that offers a wide range of tools for experimentation, personalization, and AI-driven optimization. The platform is designed to help businesses improve their online presence and drive growth across all channels. AB Tasty's user-friendly interface and extensive features make it accessible to businesses of all sizes, from startups to large enterprises.

However, potential limitations of AB Tasty may include challenges in integrating with existing systems, particularly for businesses with complex or custom technology stacks. Additionally, while AB Tasty offers a wide range of capabilities, some organizations may find that certain advanced features are not as robust as those offered by more specialized platforms.

• TL;DR: AB Tasty is well-suited for businesses looking to optimize their digital experiences across all channels, but may face limitations in integrating with complex systems or delivering certain advanced features compared to more specialized platforms.

An alternative: Statsig

Statsig is an all-in-one platform that offers feature flags, product analytics, and experimentation in a single tool. We scale with you from startup to enterprise, with customers like Notion, Whatnot, and Atlassian relying on our platform.

Our transparent pricing and startup program make us accessible for teams of all sizes — contact us to learn more and get started.