With OOYYO’s AI neural network, we can calculate the value of the car with the highest accuracy given the inputs such as model, year, geographic location, color, mileage, etc.
Furthermore, the desired vehicle does not even have to be currently offered in the database of ads. OOYYO gives the user an option to configure parameters of a desired vehicle – whether or not that type of ad is available at present time – and get an accurate prediction of the value of such a vehicle.
Additional value of this application is view of the variability of price given the change of input parameters. Visual representation is available in form of a graph.
OOYYO Ai Car Price Prediction System (CPPS) make parallel analysis of SUPPLY (data with millions of records of used cars) and DEMAND (millions of car buyers worldwide), operating on the principle of ARTIFICIAL INTELLIGENCE that is based on neural networks.
OOYYO’s competitive advantage lies in the value of OOYYO’s artificial intelligence (AI) coupled with one of the largest in the industry dynamic databases of used vehicle.
Big Data
OOYYO has data economies of scale that is crucial for effective predictive analysis by the neural data network where only critical mass of data can create effective machine learning. The company has a dynamic database of millions of diverse records that are continuously updated. This is accomplished by frequent refreshing of the base of the available car ads, as well as the constantly updated demand changes by site visitors.
Data is available from both supply and demand sides of targeted 27 markets, and it goes to the lowest level of granularity for millions of vehicles such as: brand, model, price, mileage, year, color, engine, etc. offered by zip code, city, county, selected radius, country.
AI
Parallel analysis of supply and demand
OOYYO Ai Car Price Prediction System (CPPS) creates a prediction by using frequently generated data of current vehicles for sale and current demand for vehicles on the web. The focus is on precision of the most accurate price coupled with the time it takes the vehicle to be sold of each vehicle that is for sale on all posted lots in Europe as well as all online car ads are taken in consideration. This type of data is crucial for dealers of used car lots and are directly tied to profit of car sold, along with the estimated cost of keeping the car on the lot.
Valuable data: Supply and demand comparison; Customer profile
In addition to large database of ads on the side of the supply, OOYYO collects numerous other information about customer profile and habits: geographic location, device used to perform the search, search parameters, movement across the website, etc. which provides strong demand data of the vehicles offered.
OOYYO system can make a prediction of the location/region from where the most buyers are coming from. This is especially important for the German market dealership clients where a high percentage of buyers come from outside of the country. The dealership can use the dynamic data to optimally invest in marketing campaigns and prepare type of vehicles that are in highest demand.
Through AI, OOYYO can provide answers to some key questions (see below) for the sellers and the buyers, car makers, banks, insurance companies, marketing and advertising agencies, etc.
- Relationship between supply and demand of used vehicles based on selected criteria
- Type of sponsored content could be served to a user given the data that shows that the person falls under certain profile
- Comparison of the popularity of two or more groups of vehicles based on differently selected parameters
- Ranking of a group of vehicles in comparison to the competition during the different pricing lifecycles of vehicles (where some lose/retain value at a different pace).
With SERP consideration, OOYYO has maintained high ranking positioning and is either first or second in over thirty markets under “used car” key words.
Detecting data anomalies in website crawling
AI-driven weeding out of data irregularities in website crawling is possible through careful detection of invalid parts that differ from others across the series. This enables quality, timely, and relevant ad selection with minimal errors by speedy detection and servicing seamless crawl operations.
In OOYYO’s case, ads flow through OOYYO’s system in numerous different ways. Culprit for reasons for invalid data could be due to source, or due to an error during the processing (parsing). Depending on the level and the frequency of the error in the ads on a select site, an alert is sent indicating the type of the error – whether it is systematic one that affects a group of ads where additional diagnostics are required, or if it is a one-time error that is automatically dismissed.