Managing Director & Partner
Chief marketing officers, ad agencies, and others on the buy side are embracing generative and other forms of AI. The sales teams of traditional media companies, however, have been slower to adopt these tools.
The sales teams of traditional media companies have an opportunity to implement AI tools to help generate ad revenue and improve the level of client support and campaign customization.
A recent survey of 200 chief marketing officers conducted by BCG revealed that:
Brands and agencies are adopting generative AI to become more efficient and effective. Their ability to generate content more easily, for example, will translate to a higher degree of personalization and greater number of campaigns.
By contrast, the ad sales teams of many media organizations are still evaluating generative AI and its potential. Executives cite several reasons for the delay, notably a backlog of digital distribution and monetization initiatives and a concern over how to get started with AI. Fortunately, there are steps organizations can take to help accelerate their transformations.
Generative AI is clearly in the “hype cycle” due to new releases of ChatGPT, Bard, and other solutions, but media organizations should consider the full portfolio of AI capabilities available to improve workflows and business processes:
Companies need a structured approach to bring AI to scale. And they must bring teams along the transformation journey. Here are three steps to follow:
Understand your workflows. Before they transform, media companies need to identify workflows and sales channels that would benefit the most from increased automation, optimization, and content creation capabilities. For broadcasters and cable programmers, for example, automating direct sold traditional TV campaigns—with their manual processes, ad-hoc analyses, and significant revenue contribution—is ripe for AI and automation. (See Exhibit 1.)
Generally, most media companies will want to focus on teams supporting the direct sale and delivery of campaigns rather than support functions such as HR, legal, and customer. The teams supporting sales, planning, and operations generally are the largest in ad sales and so are promising places to seek efficiencies through generative AI.
Identify pain points. AI excels at solving frictions and process bottlenecks. Exhibit 2 shows four of the main common pain points:
Overcome resistance. Teams can sometimes resist the adoption of AI on the grounds that it cannot execute a sales team’s activities. That belief is only partly true. AI may not yet help with strategic tasks such as developing the pricing strategy but is fully capable of taking on more tactical tasks such as demand forecasting and calculating premiums and discounts.
Media companies can overcome employee resistance by decomposing work into tactical, operational, and strategic activities. This approach also helps diffuse potential pushback by recognizing some use cases and activities are not good candidates for AI.
Establish priorities. All use cases are not created equal. Media companies should start with those that are feasible in the near-term and provide high benefit in the long term.
When thinking about feasibility consider:
Likewise, there are many ways to evaluate the benefit, or potential, of a use case:
In our experience, plan automation and creative review and testing are likely to yield the most benefit across the four dimensions of potential. But media companies should analyze their own operations to be sure. (See Exhibit 3.)
Get started. For many ad sales executives, generative AI can understandably seem daunting in face of other challenges. But inaction is not an option. Start with high-value short-term uses cases that can quickly demonstrate value before moving on to more ambitious cases. The opportunity to lower costs, improve efficiency, and provide customers a higher level of service should be cause for action and even optimism.
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