The Feature Adoption dashboard widget provides insight on how much your visitors use your product. It also helps you answer which areas of your product that users find the most valuable.
Add the widget to the dashboard
- Navigate to a dashboard, then select Add to dashboard > Widget in the top-right corner of the page.
- Select Feature Adoption from the list of available widgets.
- Update each field to your preference.
- Name. Enter a display name of the widget as it appears on your dashboard.
- Date range. Select the time period where event usage is measured.
- Segment. Select the users included in the analysis for usage data. Larger segments generally result in less variable data.
- App. Select the application queried for event selection and product usage data.
- Benchmark. Configure the benchmark percentage to identify Features or Pages generating a significant portion of usage within the chosen timeframe. The default is set to 80%, but you can customize it between 1% and 99% to suit your analysis needs.
- Metric. Choose either Percent of feature clicks or Average percent of daily Feature clicks to align the benchmark calculation method with your preferences.
- Event type. Choose whether to calculate the usage of Pages or Features.
- Apps or Events. Select whether to filter Pages and Features by a specific app, Product Area, or Page or Feature.
- Select Save to add the widget to your dashboard.
For more information on general dashboard and widget functionality, see Dashboards.
Interpret the widget data
The Feature Adoption widget employs the Pareto principle, where 80% of the output is typically generated by 20% of the input. This principle guides the widget's functionality, helping you identify which features drive a significant portion of user engagement within your selected timeframe.
Percentage of Feature clicks or Page views
When you select Percent of Feature clicks or Percent of Page views in the widget configuration, this calculation reveals the percentage of usage for each Feature or Page relative to the total Feature or Page usage within the specified date range.
To illustrate this calculation, consider the following example scenario:
- There are four Features tagged.
- The date range spans three days.
- The benchmark is set at 80%.
| Day 1 | Day 2 | Day 3 | Total | |||||
|
Feature |
Clicks | Volume | Clicks | Volume | Clicks | Volume | Clicks | Volume |
| A | 4,000 | 20% | 5,000 | 22.7% | 6,000 | 24% | 15,000 | 22.4% |
| B | 12,000 | 60% | 12,500 | 56.8% | 13,000 | 52% | 37,500 | 56.0% |
| C | 1,000 | 5% | 1,500 | 6.8% | 2,000 | 8% | 4,500 | 6.7% |
| D | 3,000 | 15% | 3,000 | 13.6% | 4,000 | 16% | 10,000 | 14.9% |
| Total | 20,000 | 22,000 | 25,000 | 67,000 | ||||
In this table, you can see each Feature's engagement levels within the specified timeframe:
- Each Feature's click volume and corresponding percentage are shown for each day.
- The Total column aggregates the clicks and volumes across all days.
- The Volume percentage represents each Feature's contribution to the total click volume.
Average percentage of daily Feature clicks or Page views
When you choose Average percent of daily Feature clicks or Average percent of daily Page views in the widget configuration, it calculates the average percentage of clicks for each Feature or views for each Page based on the usage for each Feature or Page for each active day within the chosen date range. This calculation then normalizes the average percentages per Feature or Page to identify the top events that make up the 80% (or your specified benchmark).
To illustrate this calculation, consider the following example scenario:
- There are four Features tagged.
- The date range spans three days.
- The benchmark is set at 80%.
On the first day, the percentage of click volume is calculated by dividing the total number of clicks from each Feature by the total click volume, resulting in the percentage of clicks for each Feature.
| Feature | Clicks | Volume |
| A | 4,000 | (4,000/20,000) x 100 = 20% |
| B | 12,000 | (12,000/20,000) x 100 = 60% |
| C | 1,000 | (1,000/20,000) x 100 = 5% |
| D | 3,000 |
(3,000/20,000) x 100 = 15% |
| Total | 20,000 | 100% |
This calculation is repeated for each day within the date range. The normalized average of the percentages for each Feature across all days is then calculated: (Average/Average Total) x 100.
|
Feature |
Day 1 | Day 2 | Day 3 | Average | Normalized average |
| A | 20% | 22.7% | 24% | 22.2% | (22.2/99.9) x 100 = 22.2% |
| B | 60% | 56.8% | 52% | 56.3% | (56.3/99.9) x 100 = 56.4% |
| C | 5% | 13.6% | 16% | 11.5% | (11.5/99.9) x 100 = 11.5% |
| D | 15% | 6.8% | 8% | 9.9% | (9.9/99.9) x 100 = 9.9% |
| Total | 20,000 | 22,000 | 25,000 | 99.9% | 100% |
Feature or Page list
The list of Features or Pages on the right side of the widget is generated based on the percentage of all clicks in descending order. Using the same example scenarios mentioned earlier for both metrics (percentage of Feature clicks or Page views and average percentage of daily Feature clicks or Page views), your top Features or Pages list comprises the Features and Pages that collectively contribute to to 80% (or your specified benchmark) of the total usage.
Percent of Feature clicks
In the following table, Features B and A account for 80% of the click volume:
| Feature | Click percentage |
| B | 56.0% |
| A | 22.4% |
| D | 14.9% |
| C |
6.7% |
| Total | 100% |
Average percent of daily Feature clicks
Similarly, in the following table, Features B and A represent 80% of the click volume, where the normalized average = percentage sum / number of active days:
|
Feature |
Day 1 | Day 2 | Day 3 | Normalized average |
| B | 60% | 56.8% | 52% | 56.4% |
| A | 20% | 22.7% | 24% | 22.2% |
| D | 5% | 13.6% | 16% | 11.5% |
| C | 15% | 6.8% | 8% | 9.9% |
| Total | 100% |
If the Features or Pages don't exactly sum up to 80% (or your specified benchmark percentage), Pendo identifies the Features that contribute volume as close to 80% as possible.
Tip: Quickly discern trends by reviewing the Product Areas assigned to your Features or Pages. This can help you understand which parts of your product users find more valuable than others at a glance.