This article is about Optimizely X. If you're using Optimizely Classic, check this article out instead.
 
relevant products:
  • Optimizely X Web Experimentation
  • Optimizely X Web Personalization
  • Optimizely X Web Recommendations

This article will help you:
  • Change the percentage of total traffic that's eligible to enter your experiment
  • Change what percentage of your experiment traffic sees each variation
  • Stop a variation

By default, Optimizely allocates 100% of visitors to experiments and distributes traffic equally among variations. Read on to learn how to control traffic allocation and distribution in Optimizely X.

Re-allocate and re-distribute traffic

To change traffic allocation and distribution for variations in Optimizely X:

  1. From the Campaigns dashboard, navigate to your experiment. Under Manage Experiment, select Traffic Allocation.



    You can also change your traffic allocation and distribution directly from the Results page. Click Edit Experiment > Traffic Allocation.

  2. In the Traffic Allocation dialog, under Experiment Traffic Allocation, you can change the percentage of eligible visitors who enter your experiment. If you choose 50%, half of the visitors who land on your page and meet your audience conditions will enter the experiment and be tracked in results.

    Under Variation Traffic Distribution, you can adjust the probability that visitors will be bucketed into a particular variation. If you have four variations and the traffic is split equally, each new visitor has a 25% chance of being placed into each variation.

    Changes to the overall experiment traffic allocation will only affect new visitors. Existing visitors (whether or not they were bucketed in a variation) will keep seeing the same variation, even after you change the traffic allocation. Visitors who are excluded from the test will always be excluded, even if you change the overall traffic allocation to 100%.

  3. Click Save to save your traffic allocation changes.

Your changes will go live when you publish your experiment. 

Stop a variation