How data analytics and bi can change content and profits in the entertainment and fashion industries
Have you ever had the thought that Netflix or YouTube know more about you than you do? They just appear to understand what you’re looking for and are always willing to help. Advanced data analytics processes are to blame for this outstanding personalization. Big data privacy issues aren’t just rhetoric; BI can help business owners monetize their wishes.
Three uses for Business Intelligence and Data Analytics in Entertainment and Fashion
Giving your audience what they want
If you don't, someone else will. The entertainment industry’s most important responsibility is to provide customers with tailored content. Netflix employs machine learning-based recommender algorithms to ensure that no one cancels their membership. Every user wants to view material that is fascinating and relevant to them; otherwise, they will not click, will be unsatisfied with the experience, and will not become loyal customers. Efforts to personalize material may be seen all throughout the entertainment sector. Consider YouTube and Netflix recommendations, Facebook feeds, and Google’s news item suggestions — the list goes on and on. Providers know exactly what each individual consumer wants thanks to big data analytics, and they can give it to them.
Video streaming businesses aren’t the only ones who rely on BI in the entertainment sector. Television stations, internet blog proprietors, and influencers all fall under this category. Every online content creator understands that even seemingly insignificant details like when a piece is published have an impact on how many people see it and how well it performs. The entertainment industry relies heavily on scheduling, and data analytics can help decide the best time to release new content. The same is true of television networks, which explains why there are so many food shows on Saturday mornings.
Focused Ad Targeting
Targeted advertising existed before the advent of AI, big data, and machine learning, but it was crude. According to legend, soap operas got their name because soap firms sponsored radio dramas in exchange for an ad platform during the first part of the twentieth century. They were not cultural philanthropists or good Samaritans. Instead, soap opera marketers realized that the core audience for these operas were housewives, who were also the most loyal consumers of these enterprises. Today’s ad targeting is far more sophisticated. Big data reveals customer preferences, allowing organizations to increase their return on marketing spending.
Predictive Analytics & Model Behavior
The use of data analytics to find trends and forecast future actions is known as predictive behavior modeling. For example, if an online retailer uses BI and maintains a close eye on their customers’ purchases, it will be evident which products they frequently buy together (say, protein powder and nutritional yeast at a sports nutrition store). If they try to buy protein without nutritional yeast again, they should be supplied yeast as well, because they are more likely to buy it if they are reminded. The entertainment business can benefit from predictive behavior modeling as well. If a gamer typically plays on Fridays but didn’t this week, the online gaming platform may consider sending them an email and offering a bonus to entice them to return.