Forecasting consumer trends is nothing new. In fact, almost 200 years ago, a forecasting model was used to determine seasonal patterns of weather, but was then also utilized for marketing purposes. It was simply a matter of data collection to forecast future patterns.

This led to supply chain management issues such as inaccurate demand forecasting, a glut of supplies, or not enough inventory.

Very recently, it all changed.

Forget demand-forecasting. Welcome demand-sensing.

With an on-demand culture and the rise of e-commerce, demand changes much quicker and leaves businesses with two far-from-ideal realities: incapable of meeting demand or simply too much inventory.

Demand-sensing harnesses the power of big data to inform a business of the customers’ intentions. Short term data is used to predict the actions of a consumer within a small timeframe, generally hours or days, and reduces forecasting errors by half. Knowing what the customer wants or needs, in real-time, as well as having information on market conditions, point-of-sale data, sales history, complementary products, and more, allows companies to meet the demand with their current inventory.

Imagine you own a car dealership and you’re always looking for leads. Without car buyers, you have a lot full of unsold inventory worth hundreds-of-thousands of dollars, if not millions. Leads come from just about everywhere and most are unreliable. Demand-sensing can make heads or tails of a large quantity of data and help you allocate your marketing dollars to the right spots; for example, a customer looking for cars on a manufacturer’s website gives the dealership the power to market to that customer searching for a new vehicle.

Now, imagine you’re the same dealership and you sold a car. The margins are low, so you want the customer to return for service or purchase accessories. Proprietary software designed to anticipate the customer’s needs can present the customer with additional service reminders, accessories and extended warranty services at the right time to encourage repeat business — and it often works. When checking out on many e-commerce sites, you’ll see “customers who bought this, also bought that.” They want to upsell you.

It’s not different for a car dealership. “Customers who bought an SUV and live in Phoenix, also bought window tints (or an extended warranty, or a theft-deterrent device, or had a 60-month auto loan).”

Demand-sensing is about using big data to anticipate the customer’s needs and intentions. For a business like a car dealership, selling a vehicle is only a small part of its revenue. Using demand-sensing can help determine when a car buyer needs to service their vehicle and present the right messaging at the right time. This drives retention and increases the likelihood that the buyer will return to purchase their next vehicle.