A/B Testing
A/B testing the pricing for your product is a little bit like Goldilocks. Too high, and you could alienate the majority of your potential customers. Too low, and you won’t have enough revenue to sustain your business. So how do you get it just right? That‘s what we’re going to explore in this post. We’ll give you the ins and outs of A/B testing your pricing, plus some alternatives to A/B testing your pricing strategy. Product pricing is undeniably one of the most important decisions for your company. Your price can determine how consumers see you in the marketplace— as a value-based brand or a convenient and cheap alternative. There are a few other factors to consider when choosing a price, including what competitors are charging (competition-based pricing), or how much it will cost you to produce your product or service, plus how much you want to profit (cost-plus pricing).
Every company has a unique set of customers, so there’s no one-size-fits-all formula for designing an optimal website, crafting the most compelling copy, or building the most effective product. This is where A/B testing tools come in, where you can use them to test and optimize your website or app design, copy, product, and, most importantly, create an experience tailored to customer needs. Read on to discover high-quality A/B testing tools that will help you discover what your unique set of customers prefers. What makes a great A/B testing tool? Before we jump into the top A/B testing tools, let’s talk about the features you should look for in an A/B testing tool. Look out for: A/B Tests: The tool should, as a baseline, offer A/B testing. Some have additional capabilities, so consider what else is offered if you’re looking for a more inclusive tool. Required Skills: Some tools require
Do you remember your first A/B test you ran? I do. (Nerdy, I know.) I felt simultaneously thrilled and terrified because I knew I had to actually use some of what I learned in college for my job. There were some aspects of A/B testing I still remembered — for instance, I knew you need a big enough sample size to run the test on, and you need to run the test long enough to get statistically significant results. But … that’s pretty much it. I wasn’t sure how big was “big enough” for sample sizes and how long was “long enough” for test durations — and Googling it gave me a variety of answers my college statistics courses definitely didn’t prepare me for. Turns out I wasn’t alone: Those are two of the most common A/B testing questions we get from customers. And the reason the typical answers from
When marketers like us create landing pages, write email copy, or design call-to-action buttons, it can be tempting to use our intuition to predict what will make people click and connect. However, you’re much better off conducting A/B testing than basing marketing decisions off of a “feeling”, as this can be detrimental to your results. Keep reading to learn how to conduct the entire A/B testing process before, during, and after data collection so you can make the best decisions from your results. A/B testing can be valuable because different audiences behave, well, differently. Something that works for one company may not necessarily work for another. In fact, conversion rate optimization (CRO) experts hate the term “best practices” because it may not actually be the best practice for you. But, this kind of testing can be complex if you’re not careful. Let’s go over how A/B testing works to ensure that…
Contrary to widespread practice, marketing analytics expands beyond email marketing and can be applied to practically every other inbound marketing tactic — social media, blogging, landing pages, lead generation, and lead nurturing. The possibilities for testing your marketing campaigns are virtually endless. While we believe marketers should constantly be testing their marketing efforts, the first step is identifying the different marketing variables you can test. And because so many of these variables are applicable across channels, you’ll likely never run out of tests to run or experiments to try. The following testing variables can reveal valuable opportunities to optimize and improve the performance of your marketing initiatives. 20 Marketing Variables to A/B Test 1. Layout Test the layout within individual content items like blog posts, email marketing messages, lead nurturing emails, and website pages like landing pages, your main website homepage, your blog homepage, etc. Move elements of your pages…
Whether you’re looking to increase revenue, sign-ups, social shares, or engagement, A/B testing and optimization can help you get there.But for many marketers out there, the tough part about A/B testing is often finding the right test to drive the biggest impact — especially when you’re just getting started. So, what’s the recipe for high-impact success? Truthfully, there is no one-size-fits-all recipe. What works for one business won’t work for another — and vice versa. But just because you can’t replicate the same test and expect the same result doesn’t mean you can’t get inspired by other companies’ tests. In this post, let’s review how an hypothesis will get you started with your testing, and review excellent examples from real businesses using A/B testing. While the same tests may not get you the same results, they can get you inspired to run creative tests of your own. A/B Testing Hypothesis…
There’s seemingly no end to what you can test in your marketing — conversion rates, offer placements, and even which titles perform better. There’s also no end to the type of test you can run, but two players take center stage: A/B and multivariate testing. Is there a huge difference between them, though? And will my results be affected if I choose the wrong one? Yes, there is a difference, and yes, your results will be affected. Not to fear, though; in this post, we’re going to break down the difference between A/B tests and multivariate tests and tell you exactly when to use each, so your tests run smoothly and your inbound marketing can go from working pretty well to amazingly well. The critical difference is that A/B testing focuses on two variables, while multivariate is 2+ variables. As the difference between both tests can be seen visually, let’s…
Have you ever presented results from a marketing campaign and been asked, “But are these results statistically significant?” As data-driven marketers, we’re not only asked to measure the results of our marketing campaigns but also to demonstrate the validity of the data — exactly what statistical significance is. While there are several free tools out there to calculate statistical significance for you (HubSpot even has one here), it’s helpful to understand what they’re calculating and what it all means. Below, we’ll geek out on the numbers using a specific example of statistical significance to help you understand why it’s crucial for marketing success. In marketing, you want your results to be statistically significant because it means that you’re not wasting money on campaigns that won’t bring desired results. Marketers often run statistical significance tests before launching campaigns to test if specific variables are more successful at bringing results than others.…