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Herry
A UK based Digital Media startup
AI-Based Solution to Track Marketing ROI
A UK based Digital Media startup involved in delivering highly advanced technology services and solutions to its clients all over the world. The company started its glorious journey to make the latest technology accessible to everyone. The customer is doing out-of-home (OOH) marketing and they wanted a tech-based solution to figure out how to improve the marketing ROI by analyzing the user demographics along with the ads which help to boost their business.
Problem Statement
To increase the marketing ROI they wanted more details of the user which is practically difficult to get in out-of-home media marketing. So, Problem was how to optimize the marketing stands & marketing ROI of their clients, and the solution is by providing user demographic data along with geolocation.
Challenges
They wanted more details of the user which is practically difficult to get in out-of-home media marketing:
A problem in finding the number of viewers of a marketing campaign.
Getting the essential Demographics (gender, age, height, etc.) along with Geolocation.
Inability to find the right audience to target. Thus difficulty in justifying the marketing return on investment.
A problem in counting customers who have viewed the advertisement. For instance, when putting an ad or banner on a van, it is difficult to determine how many viewers have viewed the same or how many times the ad has been viewed by the same viewer, and difficult to find human count, car count, car size, etc.
Solution
Our AI-based Analytics solution will provide information on the gender, age, and height of the viewer.
Our solution offers a live feed using a camera to detect and count the exact number of persons in a frame and then provide real-time data on the dashboard.
The AI-based solution makes it possible to count the cars in real-time, check out car brand, car type, car size, color, and car company logo.
With this solution, businesses can identify and target their potential customers.
Our solution captures the video feed to detect human faces using a computer vision library and matches it with pre-trained face models to find out the ethnicity (Black, White, Asian, and Indian).
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