The Q Score
Across all industries, data decision making has an impact, even in ones you might not suspect. Take the entertainment industry: The Q Score is a qualitative measure of programs and celebrities, alongside a standard for measuring consumer appeal of performers, brand ambassadors, influencers, characters and licensed properties and brands.
Based upon this data, television networks, steaming services, social platforms, advertisers, digital marketers and other related industries are able to track who and what brand has the most consumer appeal.
The Q Score has been tracking celebrity appeal since 1964 and long before automated data decision making algorithms. In the 1980s, for instance, the actor Ted Danson from the popular television series Cheers, had the highest Q Score rating. Danson was a valuable asset for advertisers because his ratings were based on likeability and trust and therefore a perfect celebrity to promote their products.
The Q Score index now includes popular YouTube entertainers. PewDiePie, for instance, has the highest Q Score among 6-to-12-year- olds (40) and 9-to-14-year-olds (38). But that score falls to 15 in the 13-to-24-year-old demographic, where Jenna Marbles and Grace Helbig rank highest. Among total viewers over age six, Higa, Smosh, and Helbig all tie for first, at 23.
Advantages of DDDM can include:
1. Improvements to transparency and accountability as to how a problem was solved or actions were prioritised.
2. Greater efficiency as continuous improvement streamlines the processes supporting decision making and problem solving. This includes being able to track improvements over time and critically examining where improvements need to be made in the DDDM process.
3. Real-time access to insights that inform choices and accelerate responses. Through use of real-time data, examination of trends or historical data patterns, the decision-making process becomes fast, more reliable, and secures greater confidence from all the parties involved.
4. Greater competitive advantage occurs as tools and technologies improve to support data collection and analysis, and the people involved acquire the capability necessary to sustainably implement data-driven decisions.
5. Greater responsiveness and line-of-sight on the customer experience. Simply stated, data allows organisations to identify customers, their demographics, their needs, how they want to engage in a customer journey, and if they are satisfied with the customer experience.
6. Promotion of agility through a virtuous circle of data feedback whereby data-driven decisions trigger data and feedback that help the organisation develop new and improved products, services, and ways to raise the customer experience.
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