How to Identify Which Experiments to Run

The last period I made an appearance here on the HubSpot Marketing Blog, I wasnat shy about my love of experiments.

At the same time, I wasnat shy in my sense that, all too often, theyare conducted for the wrong reasons. We talked about how the purpose of online experimentations is to answer questions about how people use your website.

But how do you know which questions to ask? And how do you know whether experimentations are even a viable option to answer your questions in the first place? Before you jump in, you need to make sure you know these things.

Not sure this is right and when you should start? Fear not — weare here to help. Letas get to it.

How to Tell If You Can Run Experiments

Before you come up with experimentations to operate, you need to make sure you can accurately run them. Experimentations should be completely off the table until you have an established online presence and means to track behaviour. To do that, youall require five things.

1) Traffic

In order to trust that the results of an experiment are unlikely to be influenced by randomness, you need to have a high volume of traffic. Some experimentations necessitate larger sample sizes than others — even hundreds of thousands, in some cases — but typically, you’ll require a minimum of 100 unique page views per day to reaching statistical significance within a reasonable amount of time.

2) Goals

In an experiment, your hypothesis is the statement youare working to prove. But what is it that youare trying to improve as a result of this exam? Those are your key performance indicators( KPIs) — the quantifiable measures designed to the experimentas success. Without those, you have no North star to guide the purpose of your experiment, or the objectives behind it.

3) Tracking

In order to measure and observe the performance and results of your experiment groups, youall need to establish which data youall be tracking and monitoring. In the digital realm, that might include factors like 😛 TAGEND Which pages are people visiting? Where did they come from? What are they doing once they arrive at those pages? Are they converting, bouncing, or taking another action? Run the dummy test for five business days. Take the test down. Analyze research results. Do you have 500+ unique users enrolled in the experimentation? Can you track both experiment groups full funnel? Is funnel CVR about equal for both experiment groups?

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