To maximize your Average Order Value (AOV) and drive greater profitability, you need to understand the concept of Average Order Value optimization. This metric is essential for retailers to track and measure as it helps offset customer acquisition costs, accelerates your payback time, and improves ROI.

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However, simply tracking AOV isn't enough to ensure success. To maximize your AOV, you need to gain insight into Global Maxima vs Local Maxima, Testing Velocity, and Hypothesis-based testing. Let's take a look into each of these concepts in more detail:

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When it comes to the concept of global maxima versus local maxima, it’s important to understand the basics. Global maxima is the absolute best that is possible, while local maxima is the current limit of your design.

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Essentially, if you want to move past this limit, you must break some boundaries and come up with an entirely new solution.

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First, you need to determine the boundaries of your design. This can involve understanding the conditions and constraints of your problem and deciding how far you can push the boundaries of the design.

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Once you have these boundaries in place, you can start to understand what is a feasible solution and what is a global maxima. From there, you can also determine the local maxima of your design, as this is the current limit of what you have created.

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By understanding these principles, you can begin to see the potential of global maxima versus local maxima. By pushing the boundaries of what is possible, you can create solutions that are better than the current limit. If you can do this consistently, then you can start to create solutions that are far better than what is currently available.

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Testing velocity is an important concept in the CRO process. It is the measure of how quickly an experiment can move from research and conception to launch.

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The faster you can test, the faster you can learn, and the more successful your CRO program will be. With a higher velocity, you can increase your return on investment (ROI) with fewer experiments.

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When trying to increase the speed of testing, the goal should always be to increase the speed of startup while keeping the experiment quality (aka the “value”) high. A good testing velocity can range anywhere from once per day, to once per week, to once per month. The faster you can test, the more valuable insights you can garner.

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The third concept of A/B testing is hypothesis-based testing. This involves forming an educated assumption based on data and research—we expect that by taking action X, we will be able to achieve result Y.

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This hypothesis can then be tested using a variety of methods and sources to give a clear picture of areas of improvement on your website.

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This process eliminates bias and the highest paid person's opinion, and ensures that A/B testing is based on the user experience. By relying on data-driven research rather than guesswork, you can ensure that you are making the most of your A/B testing efforts.

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Now that you're aware of these basic concepts, let's bring them together in the context of store optimization. You have your current store, your hypothesis—how it could be improved—and a goal of increasing your conversion rates and testing velocity.

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Estimating a three-month testing window is too long. So, use the concept of global maxima versus local maxima to accept some imperfections in the variant to speed up the testing process. This means testing only to prove or disprove the hypothesis, rather than perfect the variant. Furthermore, remember that most store tests fail—but that's the name of the game.

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By synthesizing the concepts of global maxima versus local maxima, you can speed up your store test and increase your chances of success. Use this knowledge to create the perfect variant and reach your goal of higher conversion rates and faster testing velocity.

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For example, if you know that the design will be 20% worse and the copy will be 10% worse than their optimal implementation, you can use a mathematical model to calculate the cost of these drawbacks. Multiply 0.9 and 0.8 to get 0.72, which means you accept a 28% decrease in the variant's effectiveness compared to the control.

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Run a test to determine the actual effect of this decrease. If the variant only loses by 10%, it still performs 18% better than the control. This suggests that if you make the variant as perfect as possible, it could be a winner.

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To confirm your findings, run the test again with the adjusted variant. By conducting these quick tests, you can determine the potential of the variant and decide whether it's worth investing in further refinement.

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Understanding the interconnectedness of these factors is key. Improving one will often have a knock-on effect on the other, or both. It is important to consider how each factor can be improved in order to achieve the best overall outcome. By taking a holistic and interconnected approach to improving these factors, you can ensure that you are getting the most out of your efforts.

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Success in the ecommerce world revolves around several key metrics, one of which is the Average Order Value (AOV). This metric, simply put, is the average amount a customer spends per transaction on your website. The higher the AOV, the higher your profits. But, to significantly increase the AOV and, consequently, the profitability of your online store, it's essential to delve into three vital concepts: Testing Limits, Testing Speed, and Educated Guess Testing.

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When we talk about testing limits in ecommerce, it’s much like trying to beat a personal record in high jump. You have a current best jump height, and you have an ultimate jump height you aspire to reach. In this context, your current performance is your "local maxima," and the peak performance you can potentially reach is your "global maxima."

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Just as you’d need to train and adopt new techniques to leap higher, optimizing your online store requires pushing beyond current boundaries and innovating. This process might involve creative problem-solving, unique marketing strategies, and even revamping some aspects of your website’s user interface. Remember, every inch towards your global maxima contributes to a better-performing, more profitable online store.

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Another concept central to ecommerce optimization is "testing speed." This term refers to how quickly you can learn which changes benefit your online store and which ones don't. The faster you can carry out these tests and interpret the results, the quicker you can make improvements.

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Imagine a racing pit crew. Their efficiency and speed in tweaking a car during a pit stop can make the difference between first and second place. Similarly, an ideal balance between testing speed and maintaining high quality of changes is crucial for enhancing your store's performance rapidly.

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Educated Guess Testing is essentially about making smart, data-driven predictions. For instance, you might predict that "if the checkout process is simplified (Action X), then the overall sales will increase (Result Y)." This hypothesis is then tested to verify if the predicted result is achieved.

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This kind of testing is crucial because it ensures any changes you make are based on solid data and not just on a whim or gut feeling. It's like having a roadmap for your journey, rather than wandering aimlessly. With every correct prediction, you get a step closer to an optimized, more profitable online store.

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By understanding these concepts, you can take a proactive approach towards making your online store more successful. Identify areas for improvement, develop strategies to enhance your sales, and implement these strategies swiftly. 

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Remember, in the ecommerce landscape, time is indeed money. Rather than waiting for months to see if a plan works, it's advisable to test rapidly. It’s okay if everything isn’t perfect; the goal is to confirm the general effectiveness of the plan, not to achieve perfection in every minute detail.

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For example, you might predict that changes to your store design and copy could initially make them 20% and 10% less perfect than they could be. However, if these changes only cause a 10% reduction in performance during testing, they're still performing 18% better than before. Following such encouraging results, you can refine and retest your changes to confirm and further optimize them.

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Recognizing that everything in your online store is interconnected is key. A small adjustment in one area can significantly impact other areas and overall performance. As such, look at your store holistically when making changes and consider how each alteration contributes to improving overall success.

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This comprehensive guide has attempted to break down some crucial concepts related to A/B testing and store optimization, demystifying them for beginners. By understanding

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