Forecasting for μCommerce?

Published on by Joannes Vermorel.

42stores-screenshot.png In same way that μISV (micro independent software editor), the eCommerce has its own wave of μCommerce (pronounced micro-commerce) where a single person without any funding starting selling goods online through his/her own webshop.

I have recently met the people from 42stores, a very interesting hosted solution for μCommerce. Basically, 42stores is a blog platform that has been extended with shopping cart features. The idea is pretty nice because the biggest barrier to enter the eCommerce market is not the amount of features in your shopping cart, but getting the community interest that you desperately need. For μCommerce, blogging looks a really cheap yet efficient way to generate sales through highly relevant traffic.

I have been asked whether there was anything to do with forecasting for a μCommerce like 42stores? Obviously, the average per-product sales are completely negligible (a couple of sales at most); thus forecasting won't be very accurate with such limited history. Yet, if the sales get aggregated on a webshop basis (summing up all product sales), then even a couple sales a month become sufficient to actually get some accurate forecasts after 3 or 6 months of activity. Such aggregated sales forecasts would not provide much help for inventory optimization; but it might give some business visibility to the retailer (how much revenue should I expect in 3 months?)

Then, web traffic itself could be subject to forecasting. I suspect that for many μCommerce, the volume of sales is directly proportional to its "organic" traffic (i.e. everything but paid traffic). Since traffic has an important impact on the value of the μCommerce, forecasting the traffic would help forecasting the future business value of the μCommerce.

In summary, for a μCommerce platform, I would suggest to restrict the forecasting operations to

  • monthly forecast for the total number of orders.
  • monthly forecast for the total value of orders.
  • monthly forecast for the total number of web hits.

Through those forecasts, the retailer gets visibility on his/her emerging business.

Categories: business, eCommerce, forecasting Tags: