- April 22, 2022
- Business Analytics and Big Data Solutions
Forecast the demand using prior sales data on various categories e.g. sporting goods, baby and toddlers etc.
The Sales data contains:
Demand is forecasted by taking sales value of product, counts of product sold earlier, brand index, discount band, price band, topic values (deal text data), seasonal index and color index. Most of these values are a value of strings but we converted them to numbers by using index using moving averages (in case we have sales data for all the 52 weeks for that brand or color).
Topic modeling and forecasting and validation:
Topic modeling is done by using text mining using tools like R, Pyhton and SAS using the text information from deal text data, like color, brand, shape, size etc. The solution looks at clustering similar words into different cluster (we call them topic1, topic2 etc), this is done by latent drichlette allocation.
The prediction window is for 7-15 days, the prediction monitored everyday using web based tableu account and the model is refreshed in every 3 months.
Some Benefits of Forecasting: