What are the challenges and opportunities of using big data and AI for audience measurement in media sales?

1 The need for accurate and reliable audience measurement

Audience measurement is the process of collecting and analyzing data on who, what, when, where, and how people consume media content. It is essential for media sales professionals to have accurate and reliable audience measurement data, as it helps them to identify their target markets, segment their customers, tailor their offers, and evaluate their performance. However, audience measurement is not a simple or straightforward task, as it involves dealing with complex and dynamic media environments, diverse and fragmented audiences, and ethical and privacy issues.

2 The potential of big data and AI for audience measurement

Big data and AI are technologies that can help media sales professionals overcome some of the challenges of audience measurement. Big data refers to the large and diverse sets of data that are generated by various sources, such as digital platforms, social media, sensors, and devices. AI refers to the systems and algorithms that can process, analyze, and learn from big data, such as machine learning, natural language processing, and computer vision. Together, big data and AI can enable media sales professionals to access more granular, real-time, and predictive audience measurement data, as well as to discover new insights, patterns, and trends.

3 The challenges of using big data and AI for audience measurement

However, using big data and AI for audience measurement also poses some challenges for media sales professionals. First, they need to have the skills and resources to collect, store, manage, and interpret big data and AI outputs, which can be costly, time-consuming, and complex. Second, they need to ensure the quality, validity, and reliability of the data and the AI models, which can be affected by factors such as noise, bias, errors, and limitations. Third, they need to comply with the ethical and legal standards and regulations regarding data protection, privacy, consent, and transparency, which can vary across different markets and contexts.

4 The opportunities of using big data and AI for audience measurement

Despite the challenges, using big data and AI for audience measurement also offers some opportunities for media sales professionals. First, they can enhance their competitive advantage and differentiation by providing more customized and relevant solutions to their clients, based on their specific needs, preferences, and behaviors. Second, they can improve their efficiency and effectiveness by automating and optimizing some of the tasks and processes involved in audience measurement, such as data collection, analysis, and reporting. Third, they can innovate and create new value propositions and business models by leveraging the new possibilities and capabilities that big data and AI provide, such as personalization, recommendation, and engagement.

5 The best practices of using big data and AI for audience measurement

To make the most of the benefits and overcome the drawbacks of using big data and AI for audience measurement, media sales professionals need to follow some best practices. First, they need to define their objectives and questions clearly, and choose the most appropriate data sources, methods, and tools for their purposes. Second, they need to collaborate and communicate with their internal and external stakeholders, such as data scientists, media buyers, media owners, and audience panels, to ensure alignment, trust, and feedback. Third, they need to constantly monitor, evaluate, and update their data and AI systems, to ensure accuracy, relevance, and improvement.

6 The future of using big data and AI for audience measurement

Using big data and AI for audience measurement is not a one-time or static activity, but a dynamic and evolving one. As the media landscape changes and the audience behavior evolves, media sales professionals need to keep up with the latest trends and developments in big data and AI technologies, such as cloud computing, edge computing, 5G, blockchain, and quantum computing. These technologies can offer new opportunities and challenges for audience measurement, such as faster processing, higher security, lower costs, and higher complexity. Media sales professionals need to be agile, adaptable, and curious, to embrace the change and seize the opportunity.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?