Imagine yourself in a giant shopping mall. If you look around, the thing that attracts your attention in a glimpse is probably the shining logo of an iconic brand, right? All of the brands spare no cost to have the logo that represents them best and use that logo for their advertising campaigns, because the logo of a brand is a unique visual tool that emits the service and the value of the brand to the customers without using any word. Besides, using the logo on the products of the brand or various areas like billboards and stadium ads boards makes the brand stick in people’s mind. The fact that 90% of Earth’s population recognize the Coca-Cola logo, shows to us how the logos are effective to represent a brand. Because of these reasons, brands spend huge amounts of money for their ads campaigns and want to learn how the money they’ve invested returns. At this stage, companies can gather information about the appearance of their logos in various platforms with the help of AI driven logo recognition tools. Let’s learn more about the areas that are logo recognition tools used.
One of the areas that logo recognition tools can be used actively is ROI investigations about sports sponsorships. Companies mostly prefer to place an ad on sports games watched by thousands of people. Also, brand logos are frequently visible on pre and post game interviews or training videos. For instance, a company that placed an ad containing its brand logo on football field ads boards or jerseys can learn how long the logo was on the screen during the game, by using the logo recognition tools. Thus, the company gets the information about how the ads investment returns and reshapes its ads expenses.
AI driven logo recognition tools can be used for counterfeit goods detection. According to a research from Incopro, 66% of customers lose their trust in a brand after buying the counterfeit product unintentionally. For this reason, detecting and getting rid of the counterfeit products has a critical importance for protecting the brand’s reputation. Using AI driven logo recognition tools, it can be detected whether a product logo used in an online shopping platform or an ad is original or not. By taking action to stop the sales of counterfeit products that are detected, the company protects the brand’s reputation and prevents loss of earnings.
A company wishing to conduct social media research may take the advantage of AI driven logo recognition tools. The company can filter the posts by using the tags to reach the posts on social media platforms related to its brand and obtain information about the brand’s visibility, but detecting the brand logo on the posts that have no tags included might be exhausting, if it is done manually. Thankfully, an AI driven logo recognition tool can detect whether the brand logo exists on various posts, by this way the company can reach information about how its product is being used by people. As an example, after detecting with the logo recognition tools that an Instagram influencer is using its product, the company can make a successful partnership agreement with the influencer and increase its earnings.
To ensure that logo detection tools are identifying the logos in an image or a video, it must be done to make the AI model recognise these logos. At this point, data annotation gets involved. By using data annotation, different logos on various brands are being classified and the AI model that is trained by a dataset containing these annotated images can recognise a logo in any image and detect in which brand it belongs to. Moreover, a professionally driven data annotation process makes the AI model able to detect a logo in different angles or cases. As an example, a brand logo that is partially covered by a cat or upside down can be correctly detected if the AI model is trained by a high quality dataset. Besides, a dataset that is annotated wrong prevents the AI model from working as intended. The AI model may confuse the counterfeit brand logo “Coco-Coco” with Coca-Cola and create inaccurate brand insights. Also a long lasting data annotation process slows down the development of the project. Because of these reasons, the teams aiming to develop a product that detects logos using AI need an agile data annotation service with a high accuracy rate maintained by an experienced team.
At Co-one, we annotate datasets containing brand logos with our well designed process, including excellent data annotation, cross validation and agile tracking. We are aware of the problems that emerge when the data that is used to train AI models doesn’t meet the required properties. With the contribution of data annotators who are actively analyzed and scored based on their performance, Co-one always delivers high quality data in a short time. Thanks to the data annotation service we provide, the teams developing AI driven products get the dataset they need easily and offer suitable solutions for the requests of companies.
Want to build an AI product that works like a well-oiled machine? Let Co-one accelerate you with rapid & accurate data annotation service!!