The Victoria's Secret July 2014 lookbook showcases a range of sexy lingerie perfect for sizzling up summer days even more. Although that might be too much heat for someone to handle, both women and men will surely take the risk. In any event, it will simply give them a reason to stay longer in bed. Top model and Maxim's hottest woman of 2014 Candice Swanepoel shows people the benefit of lounging about with ease.
Captured in a sun-drenched loft space, the Victoria's Secret July 2014 lookbook focuses on lacy bras, contemporary corsets and even the odd knit sweater for those who experience a bit of a chill instead of a heatstroke. The blonde beauty is a vision in these sensual numbers, showing off her famous svelte figure for all to enjoy.
Sun-Drenched Lingerie Lookbooks
The Victoria's Secret July 2014 Catalog Stars Candice Swanepoel
Trend Themes
1. Lingerie Lookbooks - Disruptive innovation opportunity: Introducing augmented reality to lingerie lookbooks could truly change the online shopping experience for customers by allowing them to virtually try on lingerie without leaving their homes.
2. Sun-drenched Visuals - Disruptive innovation opportunity: Using UV-responsive materials in lingerie to highlight cut-out details could appeal to consumers looking for a unique summer visual experience.
3. Sensual Comfort - Disruptive innovation opportunity: The rise of athleisure wear presents the chance for lingerie brands to showcase comfortable, functional lingerie that can be worn throughout the day as well as in the bedroom.
Industry Implications
1. Lingerie - Disruptive innovation opportunity: Developing lingerie made from eco-friendly and sustainable materials to appeal to a growing number of environmentally conscious consumers.
2. Fashion Photography - Disruptive innovation opportunity: Experimenting with new techniques like 360-degree video to showcase Victoria's Secret lingerie lookbooks could lead to an engaging and interactive viewing experience.
3. Online Retail - Disruptive innovation opportunity: Using artificial intelligence and machine learning to create personalized shopping experiences for customers, based on their previous purchases and preferences.