Data science is quickly emerging as a key differentiator for advertising, media, and entertainment organizations. That holy grail of subscriber 360—fully understanding customers—has always been a moving target. But today’s market pressures are converging on companies, demanding they become more responsive to subscribers‘ needs, wants, and preferences. For if they do it right, companies can increase subscriber retention and maximize ad revenue.
Data science, while not new to the industry, is emerging as a vital tool teams can (and must) leverage to effectively unlock customer data insights and enable the use of AI and machine learning (ML) to power deeper intelligence. A recent IDC report reveals that organizations effectively using AI have a 39% improvement in customer experience. Yet the same report notes that 55% of organizations say a lack of skilled data science talent constrains their AI initiatives.
Fierce competition is another factor causing brands to enhance their data science efforts to power more and faster actionable insights. Even the biggest of players are feeling the heat, with media giant Netflix recently admitting competition is affecting its subscriber additions. The streaming behemoth is feeling some competitive effects of other services including Disney+, Warner Bros. Discovery’s HBO Max, Paramount+, and NBCUniversal’s Peacock. The universe of what consumers can watch, play, and listen to continues to expand rapidly, challenging brands to find new ways to win and keep hearts and minds. Unlike no other time before, “consumers are now firmly in control of how they spend their time and money,” according to a recent PwC report.
Challenges to achieving subscriber 360
While most advertising, media, and entertainment organizations have some form of subscriber 360, there are common challenges that make achieving comprehensive, near real-time, 360-degree views using data science nearly impossible. A big one is legacy technology. Legacy technology is often not as agile as modern, cloud-based platforms, making it difficult to aggregate and analyze subscriber data fast enough, hindering effective targeting efforts, and causing organizations to miss revenue opportunities. They also don’t include efficient data collaboration capabilities, which reduces an organization’s capacity to quickly improve advertising effectiveness and optimize business decision-making. Advertising effectiveness requires cooperation with many partners, including agencies, publishers, measurement companies, and more. Data collaboration enables them to work together on the data without having each organization maintain their own ingestion pipeline and copy of the data.
Another common hurdle is data silos. Achieving subscriber 360 relies on bringing together data sources from websites, CRM systems, online streaming, advertisements, social media, and more. But often that data is parsed out in different systems and departments. As a result, organizations are using stale data, causing them to lose valuable insights that would enable them to be more responsive to consumer demand, competition, and market pressures.
Last, but certainly not least, is consumer privacy concerns and related regulations. Now more than ever, customers value companies they can trust as they face the potential unauthorized use of their data. It’s no surprise they are demanding greater privacy features, increased permissions and control over their own data, and the assurance that companies are adhering to strict data governance best practices.
The regulatory environment is also shifting. Lawmakers are imposing tougher regulations on companies that handle consumer data, with more regulations slated for later this year. Regulations, such as the EU’s GDPR and U.S. consumer privacy laws such as California’s Consumer Privacy Act, must now be factored into advertising, media, and entertainment organizations’ data strategy as well as requirements for a cloud data platform that enables their compliance with privacy regulations without hindering innovation.
Data science best practices for subscriber 360
As advertising, media, and entertainment companies come to better understand what data science can do for them, it helps for them to have an idea of what data scientists need to do their jobs effectively. Here are a few best practices (3 out of 11 best practices) from our Subscriber 360 Best Practices for Data Science ebook that companies should follow to build an effective data science organization:
- Break down data silos with a unified cloud data platform that supports a wide variety of data types. On a macro level, data that is centralized and usable can enable data scientists to not only create subscriber 360—it can also spot trends, identify challenges, and reduce inefficiencies. That’s why consolidating data through a platform that supports structured, semi-structured, and unstructured data (for example, image and video files) is so critical.
- Ask key questions to find the right talent. Data science talent is in high demand, and finding and keeping top data science talent is rarely easy. Many times organizations think they don’t have the time to ask key questions such as “What do we really need data scientists to do?”, “What is the current state of our company’s data?”, “What specific skills are required to do the job?” and “What tech stacks do they need to know?” But these are essential questions to consider. This upfront assessment can help steer organizations toward better staffing decisions, and help them assess which candidates will be a better fit than others, based on each company’s unique needs and challenges.
- Use third-party data to improve insights. Media and entertainment companies can greatly benefit from enriching their first-party data with third-party data—such as demographics, behavior, and viewership data—to create robust subscriber profiles. When purchasing third-party data from a data marketplace, ensure that it offers a wide variety of live, secure, ready-to-query data sets that are updated automatically in near real time from reputable companies that are connected directly through prebuilt SaaS connectors. This allows organizations to avoid the risk and hassle of copying and moving stale data, ensuring you are working with the most current data at all times.
Effective data science is an important competitive advantage for advertising, media, and entertainment companies. And fortunately, the consumer appetite for content of all kinds seems to rage on unabated, making opportunities to effectively leverage data science a worthwhile investment.
To learn more, be sure to check out our Subscriber 360 Best Practices for Data Science ebook.