Understanding Experiments

How many times have you made a business decision due to a gut feeling, an intuition, or because a competitor does it?

Now these business operations might be viable for your e-commerce, but a question emerges:

"Does it positively impact your revenue?"

With Experiments, you can test the impact of your business operations. Test different A/B groups against each other and monitor how it affects your customer LTV.

Example of an experiment:

• How many newsletters should you send per week?

You want to test how many newsletters your e-commerce should send each week.

At this moment you're sending 1 per week, but your intuition tells you that your email revenue might increase if you send more.

• Create three groups of customers for your newsletter experiment:
  1. Group test A (60% of customers): Receives 1 newsletter per week
  2. Group test B (20% of customers): Receives 2 newsletters per week
  3. Group test C (20% of customers): Receives 3 newsletters per week

Once the groups have been activated, start sending newsletters to all three groups. Monitor each group's performance in the Experiments view, keeping track of metrics such as open rates, click-through rates, and conversion rates. After a predetermined amount of time, compare the performance of each group to see which one performed the best.

The group that performs the best will become your new email strategy going forward. By conducting this experiment, you will have determined the optimal number of newsletters to send per week for your e-commerce business. This information can help you tailor your email marketing strategy to better serve your customers and maximize your revenue.

➡️ We've collected 10 of the most interesting experiments, view them here

Setting up an experiment:

After having saved and started the experiment, Custimy will start tracking the data of your selected customer group. Once the experiment has been completed, this tracking will be stopped. 

💡 Tip: Click Export if you need your customer-list in a non-integrated source, e.g. your warehouse system.

Reviewing an experiment:

Monitor the LTV of your experiment throughout your experimental period. 

Hopefully an insight like this helps you make better decisions when planning e.g. your next marketing campaign. Experimenting goes across departments - be sure to tell your colleagues about it.

Continue to test and experiment, head to Custimy.

🙇🏽‍♂️ Know how we could improve? We would love some feedback!

➡️ View next: Understanding Activation