Our app to forecast new products on the market is based on the principle of forecast by analogy using diffusion curves given by the BASS model. Our users simply need to upload any historical information (not required), type the information related to long-term potential market (customers), and some parameters: innovation, imitation and elasticities. The former is the percentage of customers that buy the product without other customers’ references, the second is associated with customers that by the product due to word of mouth, and the latter is associated with drivers of adoption of the new product, such as price or/and marketing.
Our customers can perform scenario analysis under different long-term potential markets, parameters or/and new product drivers.
Our customers can perform scenario analysis under different long-term potential markets, parameters or/and new product drivers.
Then, our users click “Hacer estimación”, and obtain the results after a few seconds. We use a Bayesian estimation approach based on prior information from similar products in the market using posterior sampling. The results are the accumulated sales per period and sales per period, both historical and forecast. Using this information, our customers can estimate the sales peak and the taking up periods under different scenarios.
