Hi there. It's Rachel of HubSpot Academy. Today we're going to talk about bringing data-driven decision-making to your marketing team and beyond. But to unpack that, first, we need to understand the purpose of the attract phase. In the attract phase, you attract visitors with useful content and eliminate barriers as they try to learn about your company. This is where your marketing team can truly shine. The best marketing teams explore new ideas and use data on a regular basis. That's because experimentation is a key component to marketing. Marketing experiments are a cost-effective way to get a picture of how new content ideas will work in your next campaign, which is critical for ensuring you continue to delight your audience. Experiments help you find new ways to delight your audience. The impact of experimentation is diluted when teams start looking for shortcuts to success, and no video on marketing experimentation would be complete without unpacking the concept of growth hacking. What is growth hacking? Essentially, growth hacking involves experiments and processes aimed at building and maintaining a company's customer base. Growth hacking is great in theory. After all, experimentation is one of the best ways marketing teams can leverage their data. But what started off as a movement to identify creative, low-cost strategies to help businesses acquire and retain customers has become the breeding ground for the marketing equivalent of get rich quick schemes. Some experts theorized that this is due to the use of the word hacking. As Andy Ramm, President and CEO of Alexa Internet at Amazon, puts it in his article is it time for a growth hacking rebrand, "Hacking implies shortcuts and quick fixes." Reading articles that show you how to do things like 100 extra social following in less than a month can be fun and informative. It's true, but always have a healthy amount of skepticism for content like that. It's likely clickbait and we'll probably do more harm than good. Why? When you become laser-focused on outputs, you may prioritize vanity metrics that don't actually help your business grow. Instead, think in terms of sustainable outcomes that align with your business goals. Best-case scenario, tactics like that will give you short-term success. Worst-case scenario, your team generates an unsustainable amount of growth, which overwhelms your services teams and creates friction in the customer experience. How can you bring the power of experimentation to your team without falling into the trap of black hat tactics. Structure your experiments based on the scientific method. The scientific method is a process for experimentation that is used to explore observations and answer questions. The steps to the scientific method for marketing experiments in particular include, one, determine your objective, two, develop your hypothesis, three, create a prediction, four, design your experiment, five, run your experiment, and six, interpret your results. Let's review these steps together. First, always design your marketing experiments with a clear objective in mind. In one sentence, you should be able to summarize what you're looking to learn or the core business metric you're looking to improve. Next, develop your hypothesis. A hypothesis is the cornerstone of your experiment. That's because a hypothesis is how you'll test your assumptions using qualitative data. In this case, as a marketer, you'll likely be testing assumptions around your users or website visitors' behavior. As Tal Raviv, Product Manager at AppsFlyer, formally a patreon, puts in his article that's not a hypothesis, "Product growth comes from fumbling around in the dark, trying a lot of new things and improving our aim over the course of months and years. In other words, this is a long game that is ultimately about learning. Clear learnings come only from clear hypotheses." Use the following sentence as a template for your hypothesis. We believe that assumption in present tense because supporting evidence. Here's a pro tip. Your hypothesis should be rooted in a specific user problem at a specific point in time and from a customer perspective. Next, create a prediction. A prediction is what you believe will happen if your hypothesis is true. It's an if then statement. There can be many predictions from one hypothesis. Use the following sentence as a template for your production. If we experiment idea, then we predict result from metric. Next, design your experiment. Look at the various assets on your website and brainstorm alternatives for design, wording, and layout. Other things you might task include e-mail, subject lines, sender names, and different ways to personalize your e-mails. Keep in mind that even simple changes can drive big improvements. Although you'll measure a number of metrics for every one test, choose a primary metric to focus on before you run the test. In fact, do it before you set up your dependent variable or variant that you're experimenting on. Here are some things to consider when designing your experiment. Are there any technical or operational assumptions being made in this experiment? How would the results of this experiment impact other areas? What built-in assumptions are potential factors that may influence results? Now, it's time to run your experiment. Running your experiment is the easy part as long as you planned out what you want to test. The next step is to wait. You need to get the traffic volume to your page high enough to declare a winner with confidence of the test statistical significance. A statistical significance calculator, like the one listed in the resources, can help with this step. If you're a little rusty on statistical significance, you're not alone. Check out the resources for determining the statistical significance of your test. Keep your data sound by not touching your test. You don't want to interfere with your results. If something on the variant or control is broken, for example, the form submit button doesn't work, fix whatever it is and restart the test. Otherwise, your data will not be sound. Finally, interpret your results. Summarize each of your success metrics in the table for your team. Depending on your exact experiment, this could include metrics such as page visits, e-mails delivered, open rate, form submissions, opportunities created, close rate, and influenced MRR. Include a summary of one to two sentences , highlighting key findings. This will help you highlight key information for your team without forcing them to read through your entire data table. Answer questions like, was your hypothesis correct? Do the results of this experiment change your perception of your customers? Why or why not? What are the implications, limitations, and potential factors that may have impacted results? What about the results if anything surprised you? That was a lot to work through. Still not sure where to get started when it comes to implementing an experimental mindset as a marketer, lean in to A/B testing. During an A/B test, two or more versions of a web page or e-mail are presented to different segments of your audience. This test determines which version performs better with your audience. The great thing about A/B test is that they're very versatile. You can test both large and small elements in your marketing campaigns. You can test something as small as the color of a CTA to something as big as an entirely redesigned page. The only thing that you need to remember as you add more differences between the two pieces of content is that you can only attribute the results to each piece of content you're testing as a whole, not individual differences. This means that if you're testing two versions of one landing page against each other and you've changed the CTA copy, the form length, the image you've added, and the headline copy on one of the landing pages, you can't attribute that landing page's success to the form itself. You'd have to attribute success to all four of those elements. Can you A/B testing HubSpot? Of course, you can. HubSpot's website pages, e-mail, and CTA tools offer A/B testing and variant testing features for professional and enterprise users.
