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TrainingPeaks Customer Feedback

Share Your Insights and Shape the Future of TrainingPeaks


At TrainingPeaks, we're committed to continually enhancing our platform to better serve your needs. Your feedback is essential in helping us achieve this goal. To submit your feedback:


  • Search for Your Idea: Before adding a new suggestion, take a moment to search for similar ideas. If you find one that matches, you can add your vote and contribute to the discussion with your comments.

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Our product teams regularly review UserVoice contributions during our ongoing prioritization and product discovery process, so this is the best place to suggest the changes you want to see. 


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TrainingPeaks Customer Feedback

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146 results found

  1. Sync with Oura Ring and Hyperice Apps.

    A sync with Oura Ring can help TP’s take into consideration sleep time and quality, HRV, Resting heart rate and recovery status. A sync with Hyperice can help TP’s take into consideration recovery modalities used by the user and adjust the fatigue and stress scores accordingly. Both can help to avoid overtraining and or give overtraining alert suggestions based on data pulled from Oura and Hyperice.

    49 votes
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    Future Opportunity  ·  7 comments  ·  Analytics  ·  Admin →
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  2. Track FTP over time in Training Peaks, as a metric.

    Track FTP over time in Training Peaks, as a metric.

    204 votes
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    Future Opportunity  ·  10 comments  ·  Analytics  ·  Admin →
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  3. Add the ability to compare workouts side by side

    It would be nice to compare all parameters side by side for similar workouts. For example, being able to compare 2-4 RT1 workouts from training plan. Or being able to compare multiple runs on a trail, etc.

    137 votes
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    Future Opportunity  ·  7 comments  ·  Analytics  ·  Admin →
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  4. Add run power Peak Performances

    The power data is imported from stryd to the workouts, it would be great if it is used in Peak Performances too

    46 votes
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    Started  ·  3 comments  ·  Analytics  ·  Admin →
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  5. Scattered Graph - Save settings introduced by user

    Hi there,
    when using the scattered graph and introducing different views of various combinations of data channels, these settings will reset to the default every time it is closed and reopened. This does not make too many sense.
    Would be a very nice feature if the settings I introduce to the scattered graph would be saved when leaving the dialogue saving it or "save and close" ...
    Ideally for bike and run differently as - depending on the discipline - different combinations of channels are relevant / interesting.
    What do you think?
    Christoph

    12 votes
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    2 comments  ·  Analytics  ·  Admin →
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    Future Opportunity  ·  AdminTony Viton (Product Manager, TrainingPeaks) responded

    Thank you for the feedback. This is a common request and has been added to that project’s feedback.

    Future opportunities have not been added to our road map yet, but we are actively collecting feedback which contributes to the prioritization process. We do not want to set up false expectations and want to make sure that there is awareness that this update currently is not prioritized and does not have an ETA.

  6. Make the PP chart infinitely variable. Do not include only the specific time intervals (5s, 10s, 12s, 20s, etc.).

    The PP chart in Strava, Golden Cheetah, etc. show peak power numbers for basically all time intervals, which is very helpful. It's nice to know if someone smashed an effort 8m long, but then you see a big drop to 10m. Or if someone has a great climb that's 45-50m long and their peak performances are on that climb, but not for 30m or 1h. Those highpoints on the curve are impossible to see with the big gaps in TP.

    8 votes
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    0 comments  ·  Analytics  ·  Admin →
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    Future Opportunity  ·  AdminTony Viton (Product Manager, TrainingPeaks) responded

    Thank you for the feedback. This is a common request and has been added to that project’s feedback.

    Future opportunities have not been added to our road map yet, but we are actively collecting feedback which contributes to the prioritization process. We do not want to set up false expectations and want to make sure that there is awareness that this update currently is not prioritized and does not have an ETA.

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