Setting Up Metrics
Set up your conversion events to measure what drives impact on your content.
Last updated
Set up your conversion events to measure what drives impact on your content.
Last updated
Metrics measure your conversions and other actions that you are optimising for with your Experiences. Ninetailed offers a number of settings to define what should be tracked and attributed.
Example: you can track the number of newsletter signups or submissions to a form, the order quantity or purchase revenue that a user generates or even just a scroll to a specific position on a page.
A metric starts to track the incoming events from the point that it is set up. Once conversions are flowing in, you can choose the respective metric you want to analyze within Experience Insights.
Metrics are created in your Ninetailed organization dashboard within the "Metrics" sidebar entry. Many configuration options are available to precisely target what conversion information you are interested in.
We recommend that you send your track events of interest prior to constructing metrics based on those track events. This ensures that metrics do not run for any time with zero events, leading to better reporting.
Ninetailed offers a total of 5 different metric types. Choose the metric type depending on what you are measuring with your corresponding conversion event.
In the following section you will find more detailed explanations for the different metric types.
The Binary metric type (also known as Binomial) is designated for measuring outcomes that occur in two distinct states such as success or failure, yes or no, true or false. This type of metric is useful when you want to track conversions or actions that have a clear-cut result.
Useful when you are optimizing for:
The number of users that have signed up to a newsletter
The number of users that have submitted a form
The number of users that have made at least one purchase
This metric type simplifies the analysis of actions that are not quantifiable by numbers but by occurrence. It is important to note that this type should only be used when you do not care about the number of times a single user has performed this type of conversion.
The Count metric type is designed to measure the number of times a particular event occurs. It is especially useful for capturing actions that can happen multiple times per user or session and where each occurrence is significant. Unlike the Binary type, which simply tracks whether or not something happened, the Count type tallies the frequency of these occurrences, providing deeper insights into user behavior.
Useful when you are optimizing for:
The average number of times a (specific or any) button is clicked per visitor
The average number of times a user adds an item to a shopping cart
The average number of times a specific page is viewed
This metric is valuable for understanding the level of engagement or interest in specific aspects of your site or product.
The Currency metric type is specifically designed for conversions that involve monetary transactions or have financial implications. This type should be used when the value of the conversion is best expressed in terms of money.
Useful when you are optimizing for:
The average purchase value per visitor
The average order value per visitor
The average shipping cost per visitor
Utilizing the currency type allows for a direct insight into the financial value (or cost) generated by user activities, making it a useful tool for businesses focusing on ROI, revenue optimization, and financial growth.
The Time metric type is intended for measuring durations or intervals, capturing how long users engage with certain elements or areas of your website or application. This metric is crucial for understanding user engagement depth and pinpointing areas where user interest wanes or holds strong.
Useful when you are optimizing for:
The average time spent on a specific page or the site overall
The time spent in a specific part of a checkout process
The Other Value metric type is used when measuring values that do not directly fit into the currency, or time categories. This type is flexible and can capture a wide range of values that are important for analyzing more specific or unique user interactions and outcomes on your website or application.
Useful when you are optimizing for:
Order quantity - The number of items a user purchases in a single transaction.
Survey scores - The score or rating a user gives in a feedback survey.
Points earned - The number of reward points a user earns for various activities.
The Event Name represents the specific name of the track event that is sent to Ninetailed. The name of this event depends on your setup. We recommend to start sending the event before setting up a corresponding metric. That way, our user interface can help you with selecting the right event using auto-complete. However, you are free to set up any event name, even for events that are going to be sent in the future.
For currency, time and other value metric types, you also need to specify the property of the event that holds the relevant value.
Example: a purchase event can have multiple properties such as revenue, shipping_cost and order_quantity.
Just like with the event name, we recommend to start sending the events before creating the metric. If you are interested in multiple properties of the same event, you can simply create multiple metrics.
Lastly, the attribution window defines when a conversion can be attributed to having seen a specific Experience. Depending on what you measure and how much of an effect Experiences might have on a conversion, you should set a different attribution window.
Ninetailed offers to attribute a conversion to an Experience if if was seen
within the same session
within the same day or
within X days (up to 90 days)
Here are a few examples of when to use which attribution time frame:
Example: An Experience that shows a CTA button to check out a specific site mostly contributes to the session behavior of that user. If we are tracking a "button click" as a metric, we should use "within the same session" for that.
Example: An Experience that suggests an item that the user might want to buy with the items they already have in their basket contributes towards increasing purchase revenue within the same session. Attributing "purchase revenue" only to Experiences within the same session makes most sense here.
Example: If you expect users to visit your content multiple times within a day and potentially perform multiple conversions throughout the day, you might want to attribute any conversions that were seen "within the same day".
Example: Experiences that drive users to sign up to a form contribute towards reaching that goal even across sessions. If we are tracking that final "form submission", we could attribute this conversion to all Experiences that were seen "within 30 days".
In some occasions it makes sense to analyze a single metric across different attribution windows. To do so, you can set up multiple metrics with identical configurations but different attribution windows.
Ninetailed uses the "last touch" attribution model combined with the attribution window to attribute an Experience to a conversion. Any Experience is attributed individually, i.e. if a single user sees multiple Experiences and then converts within the selected attribution window, all of them will be fully attributed to that conversion.
Your Ninetailed Dashboard provides an overview of all the metrics that you have set up. By default, Ninetailed tracks the performance of all metrics that you have set up across all of your Experiences. To ensure that you have set up a metric correctly, we provide a column that shows how many times the set conversion event was triggered in the past 30 days.
In order to prevent mixing up different metric settings throughout the lifetime of a metric, we disallow any editing any configurations (besides the name and description) once it is submitted. If you would like to track a metric in a different way, you can simply create another one and/or delete any existing metrics.
| Type | Useful for measuring | Example |
|---|---|---|
Binary
One-time actions per user
Form submissions
Count
Regular actions per user
Button clicks
Currency
Commerce-related activities
Purchase value
Time
User-activity-related
Engagement time
Other
Custom-defined values
User rating
