- Optimizely X Web Experimentation
- Optimizely X Full Stack
- Optimizely X Mobile
- Optimizely X OTT
This article will help you:
- Learn how Optimizely X Web Experimentation calculates results to enable business decisions
- Determine the definitions and formulas for result metrics
- Share the results of your experiments with others
- Export campaign or experiment results in a comma-separated value (CSV) format
The Results page at a glance
Optimizely's experiment Results page helps you measure success in an experiment. Dive into each metric and variation to see how visitors respond to changes you made to your site.
- Segment your results to learn more about your visitors
- Optimizely deduplicates conversions, so a single visitor triggers the same event multiple times is counted just once
What to watch out for
- If you add more than five metrics to an experiment, the additional metrics may take longer to reach statistical significance
- Visitors are bucketed into variations by chance according to the traffic distribution percentage you set, so you may not see the exact same number of visitors in each variation
Optimizely's experiment Results page is powered by Stats Engine. It provides a data-rich picture of how your visitors interact with your site. Use it to measure success in an experiment and learn about visitors to your site. In Optimizely X, the experiment Results page includes confidence intervals and incorporates a Stats Engine improvement that reduces the false discovery rate.
This article walks through the experiment Results page for Optimizely X. You can also check out our Optimizely Academy course, Understand the Results Page.
If you're using Optimizely X Web Personalization, there's a slightly different Results page.
Here's what you'll see in the left-hand navigation:
Options to pause, preview, or archive the experiment
The date when changes were last published
Number of days running
Audience(s) targeted in the experiment
Pages included in the experiment
Number of visitors
The summary and metric modules provide an in-depth view of your visitors' behavior on your site. We'll discuss those below. You can also learn how to interpret the results you see in Optimizely.
All results in Optimizely X are in local time, according to the time zone set on your machine.
Results are typically available within 5 to 10 minutes of Optimizely receiving the data. Read our article about data freshness to learn more.
Find the experiment Results page
Here are two ways to find the experiment Results page:
Experiments dashboard > Results
Manage Experiment dashboard > View Results
The experiment Results page provides a high-level summary and a module for each metric attached to your experiment. We'll walk through the summary and modules below. You'll use them to check which variations are winning, losing, or inconclusive.
The summary provides a high-level overview of the experiment. It allows you to compare how each variation is performing for the primary metric, compared to the original.
Here's what you see once visitors enter your experiment:
Visitors: Optimizely shows the number of unique visitors who've been bucketed into each variation.
Above, 7,406 visitors (or 32.88% of visitors in this experiment) have seen the original variation and 7,542 visitors have seen the "CTA Changed" variation.
Improvement: The summary also shows the improvement to the primary metric (above, the metric is Sample Size Calculator CTA Click) for each variation, compared to the baseline.
Above, clicks to the Sample Size calculator fell by 38.63% in "CTA Changed" variation and rose by 126.12% in the "CTA Higher Up" variation.
Below the summary, you'll see results for each metric that you added to your experiment. The primary metric is always at the top.
Unique Conversions or Total Conversions: When you add a metric to an experiment, you'll choose unique or total conversions. Unique conversions show deduplicated conversions, so a single visitor who triggers the same event multiple times is counted just once. Total conversions show a simple total of conversions for the event.
Conversion Rate or Conversions per Visitor: Under the Unique conversions view, Optimizely shows the conversion rate: the percentage of unique visitors in the variation who triggered the event. Under the Total conversions view, you'll see Conversions per Visitor: the average conversions per visitor, for visitors in the variation.
Improvement: Optimizely displays the relative improvement in conversion rate for the variation over the baseline as a percentage. For example, if the baseline is conversion rate is 5% and the variation conversion rate is 10%, the improvement for that variation is 100%.
Confidence interval: The confidence interval measures uncertainty around improvement. Stats Engine provides a range of values where the conversion rate for a particular experience actually lies. It starts out wide -- as Stats Engine collects more data, the interval narrows to show that certainty is increasing.
Once a variation reaches statistical significance, the confidence interval always lies entirely above or below 0.
|Statistically significant and positive||Statistically significant and negative||Not yet conclusive|
Statistical significance: Optimizely shows you the statistical likelihood that the improvement is due to changes you made on the page, not chance. Until Stats Engine has enough data to declare statistical significance, the Results page will state that more visitors are needed and show you an estimated wait time based on the current conversion rate.
Filter experiment results
Use graphs, date range, attributes, and the baseline to dig into results. We'll show you how below.
You can toggle between different graphs for each metric. To see or hide graphs, click Hide graph or Show graph.
Improvement over Time (the default): Improvement in this metric for each variation, compared to the baseline
Visitors over Time: Total visitors for the variations and the baseline
Conversions over Time: Conversions per day in this metric for each variation, including the original
Conversion Rate over Time: The cumulative conversion rate for each variation, including the original
Statistical Significance over Time: Cumulative statistical significance for the variation
Filter by date range
Use the Date Range dropdown to select start and end dates for your Results page view. Then, click Apply. The results generated will be in your computer's timezone.
Segment experiment results
By default, Optimizely shows results for all visitors who enter your experiment. However, not all visitors behave like your average visitors. Segmenting your results is a powerful way to gain deeper insights about your customers and design data-driven experiments and personalization campaigns.
Use the Segment dropdown to drill down into a segment of your visitors.
For Optimizely X Web Experimentation, the default segments are:
Browser: Firefox, Google Chrome, Internet Explorer, Opera, Safari, Unknown
Source: Campaign, Direct, Referral, Search
Change the baseline
Sometimes, you may want to see how all your variations compare to one variation in particular -- which may not be the original. Use the Baseline dropdown to select a different variation as the baseline.
Share experiment results
Use the Share feature to send your Results page to key stakeholders. Click Share and copy the URL provided.
The Share link provides access to the Results page for that specific experiment. Users can segment data, view charts, filter by data range, and more. However, they can't navigate out of the specific experiment or campaign.
If you'd like to reset the link that you shared, click Reset Link. Users with the previous link will no longer have access to the Results page.
Export experiment results data
Use the Export CSV feature to download the results of your experiment in a comma-separated value (CSV) file. You can use this file to view your results data in your favorite spreadsheet program. You can also share the raw results with others, store the data on your own machines, or perform additional analysis.
Click Export CSV to download the CSV file of the results being shown on the page (limited to the Date Range and Segment selected).
Here's a reference list of columns in your exported CSV files and their meanings. You can also access your Optimizely raw data via our Amazon S3 bucket.
Click Manage Metrics to add or remove metrics, or set a new primary metric.
Remember, if you add more than five metrics to an experiment, the additional metrics will take longer to reach statistical significance. This is because Optimizely's Stats Engine controls the false discovery rate of your experiment, which is a description of the chances of making an incorrect business decision based on your results.
However, the additional metrics don't slow down the speed of your overall test. Stats Engine ensures that the primary metric (which signals whether a variation "wins" or "loses") always reaches significance as quickly as possible.
Click Edit Experiment to make changes to your experiment. Use this option to pause a variation or adjust your traffic distribution.