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Personalized Car Choosing Apps

Clean the Sky - Positive Eco Trends & Breakthroughs

The autoTRADER autoLYZER Customizes Vehicle Shopping

— May 27, 2012 — Autos
Picking out a car can be a difficult task, but the autoTRADER autoLYZER Facebook application will match you up with the automobile that it believes is the most suited to your lifestyle.

Using a compilation of data taken from your Facebook profile, including pictures posted, online friend listings and recent posts, the app narrows down the endless choices of vehicles on the market to provide three viable options. Not only does it suggest the best cars for your personality, but the cars it chooses for you are linked to those which are already on sale at autoTRADER.ca -- because really, who doesn't like getting a deal on a car?

Driving around in a sweet ride has been proven to enhance one's overall satisfaction with life, so pairing that mentality which a completely customized car shopping app will certainly help make for some happy commuters.
Trend Themes
1. Personalized Car Shopping - Using data from social media profiles, car shopping apps like autoTRADER autoLYZER are customizing the vehicle selection process for consumers.
2. Data-driven Vehicle Recommendations - By analyzing user data, car choosing apps can provide personalized recommendations for the best cars suited to an individual's lifestyle.
3. Integrated Car Sales Platforms - Car shopping apps like autoTRADER autoLYZER are linking their recommendations to available inventory, providing users with convenient access to purchasing options.
Industry Implications
1. Automotive Industry - The automotive industry can benefit from personalized car shopping apps by attracting more potential buyers through targeted recommendations.
2. Technology Industry - The technology industry can provide innovative solutions like car choosing apps that leverage data-driven algorithms to enhance the car buying experience.
3. Social Media Industry - The social media industry can collaborate with car shopping apps to provide data for personalized recommendations based on users' online profiles and preferences.
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