CarStory Insights FAQ

Which cars on my lot will I receive alerts on?

We respect your time and will only alert you when there is a problem. There are two types of alerts you will see. The first is a Fast Seller. This tells you when a car might sell too fast. This is an opportunity to adjust your price and maximize your profit. The second is a Slow Seller. These are cars that will sell beyond your days on lot target.

How do I get setup to start receiving alerts?

The first step is sign up online at carstory.ai. After we receive your information, we will do an inventory check. If we don't have a current feed, we will email you instructions. Once we receive your inventory, we will process it and be ready to send alerts in <24 hours. The final step is to download the CarStory Insights app and enable notifications. You will also receive a daily summary email of the alerts we generate.

Who is Vast/CarStory?

Vast is a leader in artificial intelligence for the automotive industry. We apply expertise and content understand vehicles and the market. CarStory is Vast’s auto platform, and includes products like,  CarStory Market Reports. Vast powers the largest automotive brands including Car & Drive, AutoBlog and JD Power. The company is 12 years old and based in Austin, TX.

Are you competitive with vAuto, Inventory+ or FirstLook?

Not at all. We are a complement. Think of us a 24x7 monitor for your lot and the market. We'll let you know when you need to take action and give you the reasons why.

How does your prediction algorithm work?

We start with 11+ years of automotive data and expertise. Then, using the latest in artificial intelligence we crunch the data. Here is the process:

Step 1: Analyze your vehicle

First we find which features on your vehicle affect price, demand and turn. Then we calculate a market price.

Step 2: Identify current competition

Using a patented algorithm, we find the vehicles you compete with in the market. We then analyze those in the same way we examined your vehicle.

Step 3: Pull recent sales history

Then we look for similar vehicles that have sold in your local market recently.  

Step 4: Evaluate consumer demand

Next we analyze online shopping behavior. The goal at this stage is to understand the vehicle's, features and colors that are in highest demand.

Step 5: Make the prediction

We then feed the information from steps 1-4 to an algorithm that predicts when each vehicle will sell at the current price. Then we run what-if scenarios across a range of prices to identify the price and sell date suggestions.