On a less personal and more france phone number list practical level, predictive analytics is an essential part of logistical planning in retail. It can help to predict the amount of seasonal stock you should buy when the holidays roll around, and by how much you should discount these products when the holiday passes and the sales begin.
When it comes to managing staff, predictive analytics can show you when you’re likely to be busy (and in need of all hands on deck), and when it’ll be quiet enough to tactically ‘understaffed’ yourself.
While many of the previous points have been about the long game, and in particular about keeping customers engaged with your brand and products, these examples will have an immediate financial impact on your business.
Forecasting revenue
All of the above result in the ability to forecast revenue. With the data you’ve gathered, you’ll be able to simulate multiple scenarios and predict the impact they would have on revenue should they come to pass. Machine learning models are able to do this for you, continually absorbing and reacting to new data to give you real-time updates on your revenue forecasts. You can also easily compare the performance of your online, in-store, and third-party presence, to see where you’re the most successful.