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Business fundamentals tend to be quite simple, and one of the most important ones is this: the best way to know if something is working is to test it. Repeatedly.
A fact so obvious it’s hardly worth saying - you must test to see if your website is indeed doing better than how it could be doing. Without it, you're effectively flying blind and potentially missing out on a whole lot of revenue.
But how can you carry out reliable tests while minimizing the variables? Sure, you could do a regular split test, running one version of your site for a couple of weeks and then changing it around for the next couple and comparing, but that leaves a lot of variables up in the air.
A difference of two weeks may be imperceptible to you, but to a shopper, that time window could represent a whole new set of pressures or motivations that could make them want to buy where they would not have bought the week before. This is especially true near the holiday season.
The best way to really test what makes shoppers convert is to test at least two versions of the same thing simultaneously.
This is where A/B testing comes in, allowing you to show one version of your site to one set of shoppers and another version to another set in real-time and in a controlled environment, with all other variables remaining equal.
It used to be that Amazon sellers could only do split tests, as simultaneous ones were not available, but the good news is that changed in 2021! Now, Amazon has opened up this option through the Manage Your Experiment tool.
To be eligible to run experiments, you have to be registered as a brand, and any ASINs will need to have passed a traffic threshold. If they have too little traffic, you may need to devote some resources to drive shoppers to your ASIN before you can test.
To get started, the first thing you do is go to the Manage Your Experiments main screen:
Experiment content still has to follow the same guidelines as regular content, so keep your product titles to under 200 characters and pick good images. This will go through a validation process before your experiment can go live.
You can edit an experiment while it is scheduled - whether it’s waiting for validation or if it was successfully validated - but once it’s live you can’t alter it, so you would have to create a new experiment if you want to see specific changes.
First things first. There’s no point in doing this kind of experiment if both versions look the same, so make sure that the two look very different. You don’t want to be running this kind of experiment just to see the difference a single picture change will make. It’s unlikely to really affect customer behavior and any results will not be that useful to you.
What you want to do is play around with entire layout changes, a different approach to copy, text, imagery, color schemes, etc., with a view to creating a different customer experience that will trigger different reactions.
Some ideas include:
Remember, the more data you can collect the better, so ideally you would set the experiment to last around 10 weeks if you want reliable results.
Amazon will give you a pretty good list of metrics that show how the versions differ. This includes units, sales, conversion rate, units sold per unique visitor, and sample size assigned to that version, as well as a probability score of which version is better.
It will also make a one-year projection of the impact of changing to the better option. This takes the average daily increase in metrics from the winning version and multiplies it by 365 but does not take into account the effect of seasonality.
It may turn out that the results are inconclusive, which could be due to a number of reasons, among them the possibility that the versions were too similar or that traffic was too small to yield reliable results. It could turn out that the changes you made were just not something that most shoppers care about very much - you could argue that this is a result in itself.
Amazon will produce results every couple of weeks or so during your experiment, but be careful to let it run its course and not jump to conclusions based on the peeks you take. The best results will come at the end of the test.
Above all, keep testing. Once you’ve wrapped up one experiment, test it again with a different set of variables, then test again with different ASINs to see if the changes can be applied across your product line. When you’re done with those, just keep on testing.
There is never too much data.
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