Computer Vision is Changing the Online Marketing Industry

Computer Vision is Changing the Online Marketing Industry

jason-kulpa-visionWith technological advancements, computers have become smarter and their actions more pertinent to daily life. Computers have learned how to learn and how to implement the process of obtaining information to advance industries and streamline processes. Computer vision is helping advance the retail and marketing industries by providing smarter and more accessible data to further marketing efforts. Here’s a closer look at how this growing technological trend is changing the internet marketing industry—and marketing at large

Relevant Ad Images

Through the use of algorithms, computers have developed the ability to identify images on websites. These identifications are becoming more advanced, with computers now able to detect and understand images on a more profound level than simply determining the umbrella image. For example, computers can detect that an image is a car, but delve even further, recognizing more specific makes and models. With this advancement, companies have developed ways to determine the context of an image and display advertisements over those images to ensure a more targeted approach to advertising.

Visually Similar Products

Each online product carries its own tags—specific attributes that allow customers the opportunity to filter through products to best match their preferences. Computer vision can allow online retailers to bypass the traditional tagging system and instead provide similar products to customers based entirely on visual results.

Social listening

Brands typically monitor social media for mentions of their products. With the help of computer vision, brands are no longer reliant on data retrieved from text alone. Through machine learning technologies that engage with images and videos, companies—such as gumgum—are able to provide more in-depth understandings of customer demographics and when and how customers post images related to certain brands.

Emotional Analytics

As recent as 2016, it was announced that facial detection and analytics technologies would be used for content testing and media planning. Using webcams to capture consumers’ reactions to ads and content, computer vision can provide more direct and accurate analytics than focus groups or surveys.

Retail Analytics

Similar to emotional analytics, computer vision provides in-store analytics that goes beyond determining shopper demographic. Companies such as RetailNext use a variety of sensors and data streams to collect information on where shoppers commonly peruse in certain stores, which features of the store or merchandise underperform or excel, and how long customers remain engaged with the merchandise or with the sales associates. This information is helpful for helping store owners create a more immersive and effective shopping experience.

 

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