Comprehensive fitting tool using a predictive and dynamic fitting process.
Extremely Retail Efficient
ErgoFiT has been proven to be fast and accurate, perfect for a retail environment.
Removes subjective decisions and guesswork.
Easy to Use
Low Threshold of Experience Required as the IP of the system lies in the system, not the fitment staff.
6 Point Optimisation Steps
Predictive and 6 point optimisation steps are independent – Level of redundancy corrects for almost all possible errors made by the fitter.
Large Customer Database
Complete database of all customers, including their bikes. Easy to update client profile, check an existing bike fit or start a new bike fitting altogether
We like to use this example to get the point across:
John & Simon are twins. John is a professional who rides 25 hours a week and has done so for the last 10 years. Simon doesn’t ride at all, but is now getting his act together & giving riding a go. If they both go for a bike fitment using traditional fitting methods, they would more than likely end up with the same seat height, saddle setback, reach and handlebar drop. This doesn’t make sense does it? John’s body may be more flexible and is clearly going to be more adapted to riding a bike. This would probably mean a position where he would be more efficient at producing power from a position that is more aggressive and with a greater saddle height and setback, while Simon would probably require the opposite. With an ErgoFiT fitment, both riders would have very different fitment outcomes.
Without a predetermined set of parameters it is not possible to determine the correct frame size. An incorrect frame size can be manipulated to create the impression that the bike fits, but there will be consequences such as compromised handling or sub-optimal muscle recruitment patterns.
For example, a frame that is too large can be adjusted to fit a rider by shortening the stem and moving the saddle further forward. However, this will result in under-steer and the possibility that the front wheel will slide out in sharp turns or in wet conditions. In addition, it will result in over recruitment of the quadriceps, placing them at risk of premature fatigue.
Part 1 of the fitting process begins with an in depth individual assessment where the cyclist’s training history, flexibility, and measurements such as leg length, height and arm length are captured. With this information the system uses the advanced algorithms to generate an extremely accurate predicted bike fitting report. An important distinction between ErgoFiT and other systems is the use of trochanteric leg length instead of inseam measurements (which have been shown to be extremely inaccurate)
Part 2 entails the accurate application of these predicted measurements on to the bike using using both objective and highly reproducible measurements through the use of a simple X-Y reference frame or traditional measurements. ErgoFiT utilises a simple cross hair laser to accurately and easily identify the important parameters to accurately measure and implement changes in bike fit parameters.
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ErgoFit has been proven to be fast and accurate, perfect for a retail environment.