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Startups are synonymous with innovation. In this highly competitive market, they have to constantly come up with innovative ideas. However, not all ideas are good enough, so it becomes essential to pre-test the ideas to validate them. A well-known method for doing this is called A/B testing, or rather, experimentation.
However, experiments fail too often because of imprecise experiment design. We have all witnessed it. This leads to a prejudice against the process of experimentation. We argue strongly against this prejudice. Experimentation can be the key to growth for a startup.
However, a lot can go wrong when designing experiments. In particular, what we’re going to shed light on in this article is how understanding consumer behavior intelligence can lead to successful experiment design. This is something that is not often talked about, and I see many in the industry not paying attention to it.
Related: The 5 Most Important Elements of a Successful Experiment
Consumer behavior intelligence, or behavioral economics, is the field where scientists study human behavior in terms of money and value. Behavioral economics shows that human decisions, especially in the context of money, can be quite irrational. Therefore, we can use behavioral economics when designing our experiments.
If you’re looking to improve your earnings, your adoption, your trial rates, or your retention, then behavioral economics experimentation could be a growth hack for you. It can be a very powerful concept when designing your experiments. Given the vastness of behavioral economics, let’s break down three concepts and discuss how they can be used in experiments.
1. The allure of free
It seems logical that charging an insignificant fee for a service should make no difference to customer growth. That is not the case.
Let’s explore this concept through a much-discussed case study: Hershey’s Kisses vs. Lindt, the gourmet chocolate. An experiment was conducted where Hershey’s was priced at 1 cent and Lindt at 15 cents. Consumers were asked to choose between them.
A significantly greater number of people chose Lindt at a much higher cost than Hershey’s, which were nearly free. The consumers justified their choice by saying that Lindt was luxury chocolate.
Later, the experiment was repeated with the same group of people. This time, however, the choice was a little different. In both cases there was a price reduction of 1 cent. Which means Lindt fell to 14 cents and Hershey’s became free. To the researchers’ surprise, the results completely reversed, and a significantly greater number of people chose Hershey’s, even though Hershey’s was regular chocolate.
This experiment proves conclusively that there is a great attraction for ‘free’ in the human mind, and we make a big distinction between ‘free’ and ‘almost free’. So here’s a tip: if you own an app business, know that in a user’s mind “free” and “almost free” make a big difference. They are two distant options. Also keep this in mind when designing your experiment.
Related: The Basics Of Experimentation And Why It’s Key To Growing Your Startup
2. Priming
Another experiment was conducted at an airport. People at the airport were asked to pick up either yogurt or fruit from a counter. Initially, almost half opted for yogurt and the other half for fruit.
For the next part, someone spoke to people in line on the way to the counter. What they found was that when this person talked to them about yogurt, people were picking more yogurt. And when this person spoke to them about the fruit, they plucked more of the fruit. This is a good example of priming.
What we learn here is: The key is to draw the consumer’s attention to a product/service you want to sell. Their decision will probably be influenced automatically. The way to get attention doesn’t even have to be direct.
The person who was talking to the people in the queue didn’t necessarily have to point to the product. What they say may simply revolve around the product. To sell the fruit we don’t have to ask them to buy the fruit, we can just ask them which fruit they like, and that does the magic.
3. The Lure Effect
Let’s take the example of a dating app. The app gives three matching profiles in the free account and then has an option to upgrade. The upgrade has two options: There is a basic upgrade and a premium upgrade. Let’s say there are 5% of users who are upgrading, and the breakdown is 4% for basic and 1% for premium. Can we introduce a lure in these choices to turn the ratio around? Well, it’s possible!
Suppose the app introduces another upgrade option. It is in line with the premium package and is called standard pricing but is inferior to premium pricing. Let’s say the basic upgrade has five features, the premium upgrade has five plus seven great features, priced at $999, and the standard upgrade has five plus one other feature, priced at $899.
You would be surprised to know that just by introducing this inferior alternative, the app can change the ratio from 4%:1% to 1%:4%. The reason for this shift is that the users were previously unable to compare basic with premium. However, now they have found a comparison between the premium and standard packages. Five plus one is available for $899, rather than 5 plus 7 for $999. It’s an easy comparison, and the app could potentially influence people toward the bounty. This is another very useful concept that you can use to design your experiments.
Related: 4 Ways to Get the Most Out of A/B Testing Right Away
Many studies in behavioral economics give us a good idea of consumer behavior in terms of money and value. Startups can use these studies to design and run successful experiments. We discussed three simple, yet very powerful concepts of behavioral economics above, and implementing them can help you conduct successful experiments on your own.
