Consumers currently struggle to find the right cosmetic skin care products suited to their personal needs and preferences. Hundreds of brands and product forms sit next to each other on store shelves without simple and intuitive means for consumers to determine what's right for them. A new skin advisor tool has been developed to deliver a personalized beauty consultation tailored for consumers unique skin needs right at her fingertips. We identified that getting the right level of educational information to the consumer, combined with understanding her concerns and aesthetic preferences, can drive product compliance. We collected over 50,000 images of women of known chronological age and built a deep convolutional neural network model that could not only predict a woman's visible skin age with great accuracy but also identify which areas of her face she should focus her skincare on, to improve her skin appearance. Skin age accuracy was validated compared to image gradings from over 350 dermatologists. We'll discuss how we used NVIDIA GPUs and deep learning techniques to develop this new tool.