Digital Analytics Review— Week 5
Welcome to a new article on my blog. During this week, I learned together with the specialists of the CXL Institute more details about digital analytics, specifically how to use analytics to find conversion opportunities, what are the fundamentals to do an A / B Test and I learned a little about the fundamentals of great tools calculation for marketers: Excel and Sheets. Thanks to CXL Institute for giving me the opportunity to be a better professional and to learn more about how to help organizations make better decisions. Next, I will tell you what information I discovered in these three learning units:
Together with Jeff Sauer, I discovered how to identify conversion opportunities via digital analytics. In the first video, we leveraged the capabilities of Google Analytics to determine appropriate goals & filters. It’s so important to identify what the organization is looking for. We needed to set conversion goals and review the numbers to recognize how to understand the audience. The traffic we receive through our website must be measured, but we must also know the quality of visits, so Jeff explains to us which filters we must use to make the best decision, as well as review the implications of key metrics such as bounce rate & page value. Finally, we must audit the analytics of the web and interpret possible errors in the information.
Why should we take this into account? We need to interpret our analytics with a fine-tooth comb to make sure we’ve set the right number of relevant goals, checking the admin settings, and ensuring the data logically makes sense according to the number of page views we get.
In the second unit with Peep Laja, I learned about what should be the fundamentals that we should consider before doing an A / B Test, how to run statistically valid A / B test and what to test at an introductory level.
What is Testing for? Testing is a measurement methodology. It is not prescriptive in what you can or cannot test. The alternative to A / B is not a harmless A, but a risky B. Change is inevitable, A / B testing makes changes safer for consumers and businesses alike. So, what’s the opposite for measurement? The opposite of testing is “intuition”. The idea that someone magically ‘knows’ what works and what doesn’t is stone age product development.
Whenever someone says “A / B Testing is for spam”, you should consider that if you don’t want dark patterns, then stop shipping dark patterns. A / B Testing just measures what has been built. It is important to consider Storytelling because you might have a winning test, but you still don’t know why.
Regarding A/B testing, the most important part is the content to be tested, because we can test all kinds of random things all day long, and they are powerless. Testing is a cost. There may be tool costs, personnel costs, time costs, someone is designing something, some ideas, a developer writes test code or spends time thinking. Then, you need to spend a few days and weeks to run the test, which is the full cost. Therefore, the tests you perform are very important. Moreover, if you test useless things, you will get useless results.
Most importantly, consider testing as a way to solve problems. Therefore, testing is testing whether there is an idea for a solution that will solve the problem we know. We are measuring the business impact. Therefore, in order to do this, in order to design a solution that we can test, we need to understand the source of the problem. Therefore, the difference between an uncertain test (which will be most of the tests) and a test that will really be hit hard and ultimately win and provide the results we are after is hypothetical, the test you are doing . So, the first thing you need to know is what went wrong? Because you want to test in the correct location, the correct location is the correct page and the correct area of the correct page.
How do I choose which tests to run and where do I start? Therefore, Peep’s suggestion is to assume that our website is like this pyramid and consists of various types of ideas. Therefore, we always have to start with low-key goals. An identified problem, which is a problem that we discovered through user researchers or any other known methodology. People did not get a copy. We know that, and by clarifying our copy and adding more details, we have also encountered some clarity issues and we can get more money. Therefore, we want to start with the test of the obvious problem, a very obvious solution. We still don’t know which solution is the most effective, so we need to test it, but it’s obvious. Once you have killed all the low-hanging fruits, you know it, you have dug them out, and you have nothing.
Then we can start testing such as creativity and persuasive strategies. So we can move to that thing. Maybe we can do some competitive benchmarking. If we see some good ideas about UX somewhere and want to test them. We do this in the second stage. The final stage is innovation testing. Therefore, innovation testing is basically testing major changes and major changes. So, a complete website redesign will become a model for innovation testing, or you completely change your messaging, positioning, and display methods, completely redesigning the homepage, or we have a new checkout experience.
This is the test of all innovation. Therefore, innovative testing has great risks. It means that if it fails, it does. This is where the conversion takes place twice and three times, and it doesn’t happen under any circumstances. It will never happen. Innovative testing is the only thing that can bring us fruitful results. Therefore, proceed with caution, this is not the starting point you want.
At the end of the week, I started watching the first videos of the Excel and Sheets for Marketers course. I am sure that everything I am learning in these classes will help me a lot to have more clarity when making decisions and how to share my knowledge with the team. Thanks CXL Institute!
