For manufacturers and suppliers of aftermarket automotive parts, one of the most basic determinants of production or inventory is the likelihood that someone will need to replace a particular part. Aftermarket Analytics can leverage your investment in data and turn it into meaningful replacement rate models for the products relevant to your business
We examine several years of survey data to calculate actual repair rates; we then fit the data to a statistical model that predicts repair rates based on vehicle age and type. This baseline model allows you to assign a replacement rate to any vehicle, no matter how obscure it might be.
Although baseline models provide an excellent starting point for assigning replacement rates, factors create differences in replacement rates, even among vehicles of the same type. Climate, for example, can impact rates. A unique, targeted replacement rate for nearly any vehicle on the road can be created by analyzing the differences between actual and predicted repairs.
The final step in the modeling process is data validation. In order to ensure we are providing the best possible model, we review the predictive accuracy of our findings. After applying the appropriate adjustment factors, we look at how closely our predicted replacement rates fit the survey results. We continue to analyze and make adjustments as needed.