Kentucky Patent of the Month – July 2023
In today’s digital age, content creators and advertisers face the challenge of effectively reaching their target audience and obtaining valuable feedback. Traditional methods such as surveys and questionnaires often yield rushed or incomplete responses, making it difficult to gauge the true impact of content items. RAADZ, Inc., experts in surveys and market research, have developed a predictive analytics approach to solving this dilemma.
RAADZ utilizes a sophisticated predictive model and a user-friendly mobile app to gather insights and predictions from a diverse group of users. This method gamifies surveys and content collection from market research.
The company was founded as a unique and innovative solution for digital advertisers, marketers, and businesses looking for consumer insights. Their approach provides an engaged audience through thought-provoking gamification. The predictive analytics works in the following way:
- Selecting the Predicting and Target Groups:
RAADZ deploys its mobile app to a wide range of devices, creating a pool of users known as the predicting group. The predicting group is carefully selected based on various criteria such as location, gender, and age. Additionally, the app allows the content inquirer to specify a target group, which consists of users with distinct characteristics from the predicting group. This differentiation ensures a diverse range of perspectives and predictions.
- Engaging Users in the Feedback Process:
Once the app is deployed, the content inquirer presents a content item, which can be an advertisement, video, image, or even a song, to the predicting group. The content item is accompanied by relevant questions, allowing users to provide their own responses and predictions on how members of the target group will respond to the content in the future.
- Constructing the Predictive Model:
During the feedback session, users provide their responses and predictions using intuitive user interfaces within the app. The RAADZ system captures this data and constructs a predictive model based on a comparison value calculated from the responses received from the target group during a subsequent feedback session. The model takes into account deviation values, representing the variance between individual responses and the comparison value.
- Sorting and Selecting Thoughtful Responses:
The system sorts the responses based on their respective deviation values, with lower values indicating more thoughtful responses. The content inquirer is then granted access to the predictive model and a selection of the most accurate predictions. This invaluable data empowers the inquirer to measure the effectiveness of their content item and make data-driven decisions.
RAADZ has the potential to revolutionize the way content creators, advertisers, and researchers gather feedback and make informed decisions. By leveraging the power of predictive analytics and user engagement, this innovative method opens up new possibilities for more accurate predictions and improved content effectiveness.
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