Chapter 5

How to Gather Data

How to Gather Data, Part II

Video Transcription<

Chapter 5, Video #1:

Hi there, and welcome to the skills lab for chapter 5 of Convert Every Click. In this lab, we’re going to show you some ways to use heat maps and Google Analytics to gather important data. This data will help you make better decisions when building your funnel and optimizing for better conversion rates.

Now it’s your turn. Click on the links below to set up your free Crazy Egg and/or ClickTale accounts and start collecting data on your own web pages.

That’s it for now. See you in the next lab!

Click here to get access to FREE 30-day trial of Crazy Egg.

Click here to get access to FREE ClickTale account.


The Test Before You Test Method:

For a long time, I worked on my own with CRO. The field was so new, it didn’t even really have a name anyone would recognize. I worked along, split testing and improving my clients’ businesses, and I didn’t really pay attention to the other people working in the field. At one point, I remember reading some comments by other industry leaders saying things like a 40% success rate on split tests is a good outcome. This surprised me because we had always gotten around 90% success rates, and I just assumed that was normal. Once I realized we were doing something different, I scrutinized our own methods to figure out why we were so fortunate with our successes. I now believe the reason we get such high success rates is because of our Test Before You Test (TBYT) method of data gathering before we run a full-blown split test on a theory or recommendation. Many of my clients are eager to start changing things and testing ideas right away, but I let them know that it’s well worth taking a little extra time (usually a couple of months) to run some early data-gathering tests first. Once they see the results, they almost always understand the value of TBYT and go on to see much bigger gains in the long run.

The TBYT method was the main theme of my first best-selling book, Failure is Obsolete. That book detailed many ways to use the method in business and everyday life. For this skills lab, we are just going to touch on its uses as a highly accurate data gathering method used to exponentially reduce the risk of your split tests failing. Now that you understand the fundamentals of split testing and Universal Conversion Logic, it will be much easier to grasp how to use this method in your own HCRO efforts.

Have you ever heard the saying, “If you must fail, do it quickly and move on”? With this method, you will be able to experiment and test high-risk ideas in a low- risk environment, practically eliminating the need to fail at all. It’s all about getting to the real truth of the matter, as quickly as possible. Often company historical data contains flaws or assumptions that undermine your progress. If you make an assumption and base your CRO efforts on an error, you may wind up wasting a lot of time and money.

People who don’t know me very well tend to think I’m a big risk-taker. They see me starting multiple businesses, investing in growth, even skydiving, and they think he must be some kind of adrenaline junkie. But really this is just an illusion.

The reality is I hate taking risks. Well, I hate taking risks without a whole lot of confidence that everything is going to turn out in my favor. Even jumping out of a perfectly good airplane didn’t seem like a risk to me because I knew the statistics proved that I’d most likely be perfectly fine.

I can trace all this back to two of my childhood mentors, my father, Joe, and my grandfather. They didn’t know it at the time, but I watched how they made decisions, what motivated them, and how they invested their time and their money. Their actions shaped how I approached life.

My grandfather was an entrepreneur with a very high risk tolerance. Sometimes things worked out for him, and sometimes they didn’t. The high points balanced out the low points for him. I imagine it’s the same story for any big risk-taker. My father, on the other hand, gravitated in the other direction and developed a low risk tolerance. He liked to know the facts, and be sure of how things would turn out. Both these men had great influence on my life, though they probably didn’t know it (until they read this book). I saw the positive and the negative sides of both the high- risk and low-risk lifestyles. I wanted the best of both worlds — to have the excitement and reward of risk, but only if I knew it was a sure thing. Isn’t that what we all want, at least some of the time? To be fairly sure our ventures and ideas are going to turn out in our favor?

Combining my father and grandfather’s influence with my natural inclination to experiment and reverse-engineer things helped me come up with the Test Before You Test method. The basic idea is to run a lower-risk (usually cheaper) data-gathering test before you spend time and money developing a full-blown split test. The best way to explain this concept to you is with a real-life example from one of my clients.

They run a website that sells high-end luxury products that cost more than $1,000. The owner was spending hundreds of thousands of dollars on Google advertising, and each sale required a high level of education to get people to buy. (In other words, it took a lot of text to persuade people to open their wallets for this product.)

He came to us for help in getting more people to call in from the website to their sales representatives because that’s where the most sales came from. Or so he thought.

I asked him what percentage of online sales did not come from a phone call first. He replied “almost none.” It was his belief that every person who bought online had first called in and spoken to someone live. In this scenario, it made sense to try to encourage people to call in as soon as possible. The sooner they called, the more likely they would buy. But I was cautious. I didn’t want to hurt his bottom line revenues by changing things at random. I’ve learned from experience that even the most educated guesses can be wrong. So I decided to run a TBYT scenario to test his assumptions about the online sales. He was skeptical about running this data-gathering test, I’ll admit. But he went along with it.

I designed a quick test to discover how many of the website customers had actually talked to a team member by phone before buying. At a glance, I didn’t have any reason to suspect the owner was wrong. But in order to maintain the likelihood of success, I wanted to test those assumptions, just to be sure. He was unwilling to ask customers directly, but he was willing to put an additional question on the order form. So that’s what we did. We added one line that said, “Did you speak with a representative before making this purchase? Yes/No.”

Of course, there’s room for a margin of error because we weren’t testing actual behavior, we were asking a question (basically taking a survey). But it was a creative solution that gave us the data we needed.

Within three weeks we found out that over 90% of people who ordered online never spoke to anyone on the phone! Considering online sales accounted for half their total revenue, that was a huge discovery. If we had done what they requested and used CRO strategies to get people calling in sooner, they may have lost a lot of money. At best, they might have broken even.

When he saw this data, he was in shock. He had absolutely no idea that this was the case. In fact, it’s very likely this was the reason why the company had been unexplainably shrinking over the previous five years. He instantly understood the value of what we do as holistic conversion rate optimization experts and why the TBYT method is so amazing. Knowing his business model combined with experience from past customers with similar situations, I can tell you he saved hundreds of thousands of dollars and a year of his life focusing on the wrong thing.

This was the very first test we designed for him. It was implemented in one day, for less than $100.

Once we had this data collected, we could move forward with implementing split tests that were based on correct assumptions — tests that really mattered to his bottom line.

So, before you spend time and money implementing and testing ideas, spend some time testing your assumptions, your historical data, and your market’s interest levels. It might feel like an unnecessary step, but in my experience it’s always been worth taking the time in the long run.

If you’d like to dive deeper into this topic and discover different applications for the TBYT method, you can find that in my book Failure is Obsolete.

Click the link below to get the book for free (just pay for shipping).

That’s it for now. See you in the next lab!

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