In the marketing services industry, CMOs struggle to cross the marketing talent gap and, as a result, turn to performance-driven agency partners. But those partners are struggling to meet the needs of the market.
Agencies are expected to be immersed in marketing technology and well-versed in core disciplines like content marketing, SEO, paid search, social media monitoring and analytics. But many fail to attract, close and service business opportunities because they struggle to hire adequate talent, integrate new technology and address evolving client needs profitably.
The result? Companies are taking marketing in-house, reports Mark Schaefer in Harvard Business Review, because agencies fail to evolve their services and skills fast enough to create value.
It’s a huge problem for agencies, and one that artificial intelligence can help them address. Artificial intelligence presents a way for agencies to create more value faster, as well as automate, augment and accelerate their operations—improving results for clients and the bottom line.
Consider how much time your team spends on repetitive and administrative tasks, such as drafting social media updates, writing data-driven blog posts, personalizing emails and website copy, managing paid media spend, conducting keyword research and more.
Even with the use of marketing automation software, most of these tasks require significant human involvement, distracting agencies from high-value strategic activities that drive lasting value for clients and the bottom line.
But what if we told you every one of these tasks, and many more, could be done more efficiently using artificial intelligence technology today?
Tools like Automated Insights and Narrative Science can write stories at scale from data, vastly reducing the time it takes to write internal reports or external-facing content. A solution like Albert by Adgorithms optimizes paid media spend and performance, potentially better and faster than human beings. PaveAI can automatically generate reports from Google Analytics data, eliminating repetitive and lengthy reporting efforts that sap team time and creativity.
By using AI tools to automate these types of tasks, agencies have the potential to free up talent to pursue higher value and higher profit activities, as well as increase margins.
AI also has the potential to augment human creativity.
Agencies—and marketers as a whole—are limited by a finite ability to process information, build strategies and achieve performance potential. As the number of connected consumers and devices expands, the amount of data produced exponentially increases. Meanwhile, our ability to filter through the noise and turn data into actionable intelligence remains limited by biases, beliefs, education, experiences, knowledge and brainpower.
AI, however, excels at analyzing structured and unstructured data to give marketers actionable insights and separate the signal from the noise.
For instance, Crayon’s marketing intelligence platform arms marketers with inspiration for their next campaigns. A solution like Atomic Reach delivers recommendations on which content works best, freeing marketers to craft highly targeted and relevant messages. Acrolinx gives you immediate guidance on how to improve content, while you create it.
These insights can enhance the high-value creative work that agencies do, driving performance, productivity and personalization.
As artificial intelligence tools automate and augment operations, they in turn accelerate agency success, both online and offline. Agencies that are able to deliver better performance and valuable outcomes in less time are freer to pursue further growth and profitability. They may even secure the ability to experiment with new value-driven business models.
For instance, PR 20/20, the agency that powers the Marketing Artificial Intelligence Institute, implemented natural language generation (NLG) to cut down the analysis and production time of Google Analytics reports by 80%. This helped create the freedom to experiment with additional AI tools, which now drive even greater performance and productivity.
The effect of experimenting and adopting AI is cumulative—and it starts with understanding what’s possible.