At ABsmartly, we know that the key to staying ahead as a business isn't just about having great ideas but in validating and refining those ideas through rigorous experimentation. By embracing a data-driven methodology, businesses can uncover invaluable insights that drive and accelerate growth, enhance user experience, and foster an agile environment of continuous learning and adaptation.
Businesses are often caught in a relentless pursuit of innovation to not only meet changing consumer demands but to anticipate them. We firmly believe that experimentation is the bridge between guesswork and evidence-based decision-making, which allows companies to test hypotheses in real-world scenarios and make informed decisions based on outcomes. We’ve walked your path, and in this blog we lay out the steps to start experimenting like Booking.com.
Turning Hypotheses into Business Success Stories
ABsmartly’s founder, Jonas Alves, pioneered Booking.com's foundation of experimentation. The company's commitment to experimenting at scale—running thousands of A/B tests simultaneously—demonstrates a profound understanding of experimentation not just as a tool for optimization but as a fundamental driver of corporate strategy.
This approach allowed Booking.com to meticulously refine every aspect of the user journey. By adopting a willingness to experiment, businesses can create a culture that celebrates curiosity, encourages risk-taking, and systematically leverages data to guide development and marketing strategies.
At the heart of Booking.com's success lies a simple philosophy: every feature, every change, and every innovation is a hypothesis waiting to be tested. This philosophy resonates deeply with us at ABsmartly, where we believe experimentation isn’t just a way to guide decision-making, but an important part of the business strategy.
ABsmartly's Role in Championing Experimentation
We are all about democratizing the process of experimentation, making the sophisticated methodologies used by giants like Booking.com, Netflix and other big tech accessible to businesses of all sizes. Our platform simplifies the complexity involved in setting up, running, and analyzing experiments.
We help you:
Easily Design Experiments: Our intuitive interface allows teams to quickly set up experiments without extensive technical expertise, making the process of hypothesis testing more accessible.
Access Real-time Insights: Businesses can monitor experiment performance in real-time through our dashboard, allowing for swift adjustments and immediate understanding of user responses.
Scale Experimentation Efforts: ABsmartly's collaboration features help scale experimentation efforts from a handful to thousands of tests, accommodating business growth and evolving experimentation strategies.
Leverage Advanced Segmentation: ABsmartly provides advanced segmentation capabilities that offer deep insights into experiment outcomes, helping businesses understand not just what is happening but why it's happening.
When using a centralized approach the more experiments you have running, the sooner you’ll hit the inevitable roadblock of the time data scientists need to analyze the information your experiments provide. ABsmartly helps you democratize experiment set up and decision making across all the product teams by providing collaboration features, a stats engine with efficacy and futility boundaries that make it a lot easier to make decisions without involving the data science team and at the same time bring your knowledge base, messaging and communication into a single place and always in context with the results, the hypothesis and the reports about the learnings and insights generated by each experiment.
The idea is to allow clients to seriously scale experimentation through automation and access reliable statistical analyses. When you manage experiments that way, you totally eliminate that roadblock that relying on human analysts creates. When you give your teams autonomy you allow for experimentation at higher levels..
ABsmartly’s Advanced Statistical Tools - the Only Group Sequential Testing Tool on the Market
We give you the option to keep a close eye on the results of your experiments by reviewing them continuously or when you end the experiment. Our platform solves the peeking problem by using Group Sequential Testing (GST) to maximize power. If you prefer, you can also use fixed-horizon if you need high reliability or have strong weekly seasonality. We give you access to a wide range of statistical tools including variance reduction, multiple testing corrections, and sample size calculations so that you can combine the exact metrics and methods that you need to see.
When you use the ABsmartly platform, analysis doesn’t end with the experiment. For a true experimentation culture to work, users must dig into the details of their experimentation results and share them! If you’ve had a great result that you weren’t expecting you can dig into the details of the customer segment that’s seeing the most impact, or if you’ve found that a change hasn’t had an impact, you can investigate whether there are any specific groups that benefited from the variant you tested and that might spark an idea for the direction you can move in next. Our platform can show you the results of your experiments by the dimensions you create, such as if an order was placed using your website or in your app.
Experimentation in Action
To illustrate the impact of experimentation, let's look at a couple of hypothetical case studies inspired by the types of experiments Booking.com might conduct:
Optimizing Checkout Flow: By experimenting with different checkout flow designs, including the placement of the payment information section and the use of reassuring security badges, a hypothetical improvement in conversion rates by 15% was observed.
Personalizing User Experience: Through A/B testing different homepage layouts tailored to user behavior, an increase in user engagement and a reduction in bounce rates were achieved, demonstrating the value of personalized experiences.
Streamline Experimentation
At ABsmartly, we provide a suite of tools designed to streamline the experimentation process, making it accessible, scalable, and manageable. Our toolkit offers everything from advanced analytics for deep insights to intuitive dashboards for real-time monitoring of experiments. This enables businesses to adopt a data-driven approach to experimentation, much like Booking.com, but with greater ease and efficiency.
By looking to pioneers like Booking.com as a model, ABsmartly is not just advocating for a more experimental approach to product growth; we're enabling it. With our tools and expertise, we're helping businesses unlock their potential, one experiment at a time.
Interested in seeing the tool with your own eyes? Schedule a demo here: https://bit.ly/ExperimentLikeBooking
At ABsmartly, we know that the key to staying ahead as a business isn't just about having great ideas but in validating and refining those ideas through rigorous experimentation. By embracing a data-driven methodology, businesses can uncover invaluable insights that drive and accelerate growth, enhance user experience, and foster an agile environment of continuous learning and adaptation.
Businesses are often caught in a relentless pursuit of innovation to not only meet changing consumer demands but to anticipate them. We firmly believe that experimentation is the bridge between guesswork and evidence-based decision-making, which allows companies to test hypotheses in real-world scenarios and make informed decisions based on outcomes. We’ve walked your path, and in this blog we lay out the steps to start experimenting like Booking.com.
Turning Hypotheses into Business Success Stories
ABsmartly’s founder, Jonas Alves, pioneered Booking.com's foundation of experimentation. The company's commitment to experimenting at scale—running thousands of A/B tests simultaneously—demonstrates a profound understanding of experimentation not just as a tool for optimization but as a fundamental driver of corporate strategy.
This approach allowed Booking.com to meticulously refine every aspect of the user journey. By adopting a willingness to experiment, businesses can create a culture that celebrates curiosity, encourages risk-taking, and systematically leverages data to guide development and marketing strategies.
At the heart of Booking.com's success lies a simple philosophy: every feature, every change, and every innovation is a hypothesis waiting to be tested. This philosophy resonates deeply with us at ABsmartly, where we believe experimentation isn’t just a way to guide decision-making, but an important part of the business strategy.
ABsmartly's Role in Championing Experimentation
We are all about democratizing the process of experimentation, making the sophisticated methodologies used by giants like Booking.com, Netflix and other big tech accessible to businesses of all sizes. Our platform simplifies the complexity involved in setting up, running, and analyzing experiments.
We help you:
Easily Design Experiments: Our intuitive interface allows teams to quickly set up experiments without extensive technical expertise, making the process of hypothesis testing more accessible.
Access Real-time Insights: Businesses can monitor experiment performance in real-time through our dashboard, allowing for swift adjustments and immediate understanding of user responses.
Scale Experimentation Efforts: ABsmartly's collaboration features help scale experimentation efforts from a handful to thousands of tests, accommodating business growth and evolving experimentation strategies.
Leverage Advanced Segmentation: ABsmartly provides advanced segmentation capabilities that offer deep insights into experiment outcomes, helping businesses understand not just what is happening but why it's happening.
When using a centralized approach the more experiments you have running, the sooner you’ll hit the inevitable roadblock of the time data scientists need to analyze the information your experiments provide. ABsmartly helps you democratize experiment set up and decision making across all the product teams by providing collaboration features, a stats engine with efficacy and futility boundaries that make it a lot easier to make decisions without involving the data science team and at the same time bring your knowledge base, messaging and communication into a single place and always in context with the results, the hypothesis and the reports about the learnings and insights generated by each experiment.
The idea is to allow clients to seriously scale experimentation through automation and access reliable statistical analyses. When you manage experiments that way, you totally eliminate that roadblock that relying on human analysts creates. When you give your teams autonomy you allow for experimentation at higher levels..
ABsmartly’s Advanced Statistical Tools - the Only Group Sequential Testing Tool on the Market
We give you the option to keep a close eye on the results of your experiments by reviewing them continuously or when you end the experiment. Our platform solves the peeking problem by using Group Sequential Testing (GST) to maximize power. If you prefer, you can also use fixed-horizon if you need high reliability or have strong weekly seasonality. We give you access to a wide range of statistical tools including variance reduction, multiple testing corrections, and sample size calculations so that you can combine the exact metrics and methods that you need to see.
When you use the ABsmartly platform, analysis doesn’t end with the experiment. For a true experimentation culture to work, users must dig into the details of their experimentation results and share them! If you’ve had a great result that you weren’t expecting you can dig into the details of the customer segment that’s seeing the most impact, or if you’ve found that a change hasn’t had an impact, you can investigate whether there are any specific groups that benefited from the variant you tested and that might spark an idea for the direction you can move in next. Our platform can show you the results of your experiments by the dimensions you create, such as if an order was placed using your website or in your app.
Experimentation in Action
To illustrate the impact of experimentation, let's look at a couple of hypothetical case studies inspired by the types of experiments Booking.com might conduct:
Optimizing Checkout Flow: By experimenting with different checkout flow designs, including the placement of the payment information section and the use of reassuring security badges, a hypothetical improvement in conversion rates by 15% was observed.
Personalizing User Experience: Through A/B testing different homepage layouts tailored to user behavior, an increase in user engagement and a reduction in bounce rates were achieved, demonstrating the value of personalized experiences.
Streamline Experimentation
At ABsmartly, we provide a suite of tools designed to streamline the experimentation process, making it accessible, scalable, and manageable. Our toolkit offers everything from advanced analytics for deep insights to intuitive dashboards for real-time monitoring of experiments. This enables businesses to adopt a data-driven approach to experimentation, much like Booking.com, but with greater ease and efficiency.
By looking to pioneers like Booking.com as a model, ABsmartly is not just advocating for a more experimental approach to product growth; we're enabling it. With our tools and expertise, we're helping businesses unlock their potential, one experiment at a time.
Interested in seeing the tool with your own eyes? Schedule a demo here: https://bit.ly/ExperimentLikeBooking
At ABsmartly, we know that the key to staying ahead as a business isn't just about having great ideas but in validating and refining those ideas through rigorous experimentation. By embracing a data-driven methodology, businesses can uncover invaluable insights that drive and accelerate growth, enhance user experience, and foster an agile environment of continuous learning and adaptation.
Businesses are often caught in a relentless pursuit of innovation to not only meet changing consumer demands but to anticipate them. We firmly believe that experimentation is the bridge between guesswork and evidence-based decision-making, which allows companies to test hypotheses in real-world scenarios and make informed decisions based on outcomes. We’ve walked your path, and in this blog we lay out the steps to start experimenting like Booking.com.
Turning Hypotheses into Business Success Stories
ABsmartly’s founder, Jonas Alves, pioneered Booking.com's foundation of experimentation. The company's commitment to experimenting at scale—running thousands of A/B tests simultaneously—demonstrates a profound understanding of experimentation not just as a tool for optimization but as a fundamental driver of corporate strategy.
This approach allowed Booking.com to meticulously refine every aspect of the user journey. By adopting a willingness to experiment, businesses can create a culture that celebrates curiosity, encourages risk-taking, and systematically leverages data to guide development and marketing strategies.
At the heart of Booking.com's success lies a simple philosophy: every feature, every change, and every innovation is a hypothesis waiting to be tested. This philosophy resonates deeply with us at ABsmartly, where we believe experimentation isn’t just a way to guide decision-making, but an important part of the business strategy.
ABsmartly's Role in Championing Experimentation
We are all about democratizing the process of experimentation, making the sophisticated methodologies used by giants like Booking.com, Netflix and other big tech accessible to businesses of all sizes. Our platform simplifies the complexity involved in setting up, running, and analyzing experiments.
We help you:
Easily Design Experiments: Our intuitive interface allows teams to quickly set up experiments without extensive technical expertise, making the process of hypothesis testing more accessible.
Access Real-time Insights: Businesses can monitor experiment performance in real-time through our dashboard, allowing for swift adjustments and immediate understanding of user responses.
Scale Experimentation Efforts: ABsmartly's collaboration features help scale experimentation efforts from a handful to thousands of tests, accommodating business growth and evolving experimentation strategies.
Leverage Advanced Segmentation: ABsmartly provides advanced segmentation capabilities that offer deep insights into experiment outcomes, helping businesses understand not just what is happening but why it's happening.
When using a centralized approach the more experiments you have running, the sooner you’ll hit the inevitable roadblock of the time data scientists need to analyze the information your experiments provide. ABsmartly helps you democratize experiment set up and decision making across all the product teams by providing collaboration features, a stats engine with efficacy and futility boundaries that make it a lot easier to make decisions without involving the data science team and at the same time bring your knowledge base, messaging and communication into a single place and always in context with the results, the hypothesis and the reports about the learnings and insights generated by each experiment.
The idea is to allow clients to seriously scale experimentation through automation and access reliable statistical analyses. When you manage experiments that way, you totally eliminate that roadblock that relying on human analysts creates. When you give your teams autonomy you allow for experimentation at higher levels..
ABsmartly’s Advanced Statistical Tools - the Only Group Sequential Testing Tool on the Market
We give you the option to keep a close eye on the results of your experiments by reviewing them continuously or when you end the experiment. Our platform solves the peeking problem by using Group Sequential Testing (GST) to maximize power. If you prefer, you can also use fixed-horizon if you need high reliability or have strong weekly seasonality. We give you access to a wide range of statistical tools including variance reduction, multiple testing corrections, and sample size calculations so that you can combine the exact metrics and methods that you need to see.
When you use the ABsmartly platform, analysis doesn’t end with the experiment. For a true experimentation culture to work, users must dig into the details of their experimentation results and share them! If you’ve had a great result that you weren’t expecting you can dig into the details of the customer segment that’s seeing the most impact, or if you’ve found that a change hasn’t had an impact, you can investigate whether there are any specific groups that benefited from the variant you tested and that might spark an idea for the direction you can move in next. Our platform can show you the results of your experiments by the dimensions you create, such as if an order was placed using your website or in your app.
Experimentation in Action
To illustrate the impact of experimentation, let's look at a couple of hypothetical case studies inspired by the types of experiments Booking.com might conduct:
Optimizing Checkout Flow: By experimenting with different checkout flow designs, including the placement of the payment information section and the use of reassuring security badges, a hypothetical improvement in conversion rates by 15% was observed.
Personalizing User Experience: Through A/B testing different homepage layouts tailored to user behavior, an increase in user engagement and a reduction in bounce rates were achieved, demonstrating the value of personalized experiences.
Streamline Experimentation
At ABsmartly, we provide a suite of tools designed to streamline the experimentation process, making it accessible, scalable, and manageable. Our toolkit offers everything from advanced analytics for deep insights to intuitive dashboards for real-time monitoring of experiments. This enables businesses to adopt a data-driven approach to experimentation, much like Booking.com, but with greater ease and efficiency.
By looking to pioneers like Booking.com as a model, ABsmartly is not just advocating for a more experimental approach to product growth; we're enabling it. With our tools and expertise, we're helping businesses unlock their potential, one experiment at a time.
Interested in seeing the tool with your own eyes? Schedule a demo here: https://bit.ly/ExperimentLikeBooking