Making sure content marketing is a revenue center is one major issue cited by respondents in Content Marketing Institute and MarketingProfs’ ninth annual B2B Content Marketing 2019: Benchmarks, Budgets, and Trends—North America report.
To do that, content marketers need to make sure every dollar and hour spent on content marketing goes as far as possible and produces real results.
This is why so many top-performing content marketers rely on technology to help them build smarter content marketing programs. In fact, 67% of the most successful content marketers in CMI’s NAME study say they have “expert/advanced proficiency” at using content marketing technology (compared to just 5% among the category of least successful content marketers).
Content marketing technology helps marketers build smarter content programs and gain insights into how to improve performance. It’s truly revolutionary - and it’s just in the early stages.
Advances in AI in content marketing have unlocked the possibility of much smarter content marketing technology. In fact, AI is being used today to unlock unprecedented performance and productivity in content marketing thanks to the technology’s incredible speed and scale.
Traditional content marketing technology certainly does plenty of tasks much faster than humans. That kind of productivity is welcome for content marketers who are trying to do more—and, often, more with less.
But traditional content marketing technology relies on human teams to get smarter. Think of your favorite marketing automation software. A series of product updates and new features have (hopefully) made it more robust over time. You can probably do far more with the software than you could when it was first released. But the only time the system “gets better” is when the company invests significant time and energy into making it better.
Artificial intelligence tools, however, can get better on their own—without human involvement. That means AI-powered tools actually learn from past performance, then use that information to improve.
So, let’s say you have a traditional content marketing tool that rates your email subject lines and gives you recommendations on how to improve them. That tool draws from a fixed dataset to make recommendations. The recommendations may be good to start, but they don’t get better or evolve based on performance—unless a human rewrites the tool’s rules.
The same tool powered by AI, however, has the ability to learn from the performance of every email subject line you wrote, then improve its recommendations based on what works best and what doesn’t.
The result? A dynamic technology that has the speed to adapt to changing customer preferences, markets, and data. This level of speed is critical in a fast-moving content marketing ecosystem.
The other key advantage of AI over traditional content marketing technology is scale.
Plenty of content marketing tools help you do more. But, the more data you acquire, the more difficult it can be to extract value from these tools.
Take your marketing automation platform again as an example. It certainly helps you do more, but it starts to require serious work to extract insights from it when it’s running hundreds of campaigns or holds tens or hundreds of thousands of contacts. Sorting meaningful signals from the noise becomes harder as your content marketing programs grow.
In fact, this is where many content marketing programs stop being effective. They get somewhat successful in generating traffic, interest, contacts, and (overall) data. But then all the moving parts get extremely complicated to manage. Scale is possible, but it still requires a huge investment of time and money into additional human and technology resources.
Artificial intelligence actually offers a better way to achieve true scale. AI-powered tools excel at extracting insights from large datasets. They’re actually designed for scale. And, because AI tools learn from data and improve accordingly, they become more, rather than less, effective as your available data grows.
Let’s take a common content marketing use case as an example: content strategy.
Traditional content marketing tools might give you data on your content marketing efforts, which you would then have humans analyze to build content strategy. The more content you publish, the more data points you have. But this also creates much more work when it comes to analysis. That work cuts into time spent expanding your content marketing efforts, which slows down your rate of scale. And the whole thing becomes more complex the more you do.
Now, take as a comparison an AI-powered content strategy tool. The tool analyzes your existing content program, then offers actionable insights. Your team is exclusively focused on executing on those insights, so you have greater capacity to produce more content. As more content is produced, your AI content strategy tool continues to offer insights with no additional work on your end. Additionally, these insights get better over time, so you produce even more results, making each hour of your time spent on content creation even more effective.
In this way, AI creates a virtuous cycle of speed and scale that can benefit almost any content marketing program.
For some inspiration on potential AI-powered content marketing tools, check out Marketing AI Institute's Marketing AI Buyer's Guide.
Additionally, one tool to check out for your content strategy needs is Cobomba, an AI-powered tool for content planning and intelligence. Cobomba uses AI to show you what content and messaging customers want. Try it out below.
An accomplished and innovative top B2C and B2B marketing executive with profit and loss responsibility, as well as extensive experience in marketing strategy, business development, digital marketing, advertising, brand management, CRM and eCommerce.