Tech Advances That Are Impacting Content Marketing Trends

When we talk about marketing and technology, the conversation is all over the place. On the one hand, there’s buzz about B2B and B2C content marketing trends and AI that implies there will be explosive growth in tech adoption. On the other, marketing budgets are down as a share of revenue, as is the share of the budget dedicated to tech.

It’s not that content marketers aren’t interested in tech. We are! It does mean, however, that leaders are wary of spending right now. Contributors include the tepid economic expectations this year, coupled with the fact that marketers aren’t using the lion’s share of the martech capabilities they already have. The result is C-suites are continuing to ask marketers to do more with less, a trend we also saw last year.

What does that mean for the hot technologies in marketing right now? A year ago, we reported on our own survey findings showing the ways in which content technology investments mirror our functions’ biggest challenges.

Research from third-party sources for this year shows many of the same tech trends that make us more efficient and more impactful. Unsurprisingly, it all starts with AI.

Generative AI really is affecting content marketing trends!

There is a predictable pattern in technology — a hot new technology grabs everyone’s attention and attracts major investment, only to be followed by a period of disappointment after it fails to produce immediate returns. In the case of generative AI, however, the pattern looks different.

Two years after the release of generative AI, marketing leaders are still excited about its promise and payoff. A survey from Boston Consulting Group finds that 70% of marketing functions already use it. McKinsey estimates that the economic benefits of adopting generative AI could result in between $6.1 to $7.9 trillion in value.

According to multiple surveys, AI is already enabling content marketing teams to produce more content faster and with greater accuracy. Given the fact that creating enough content to meet demand is among content marketing’s top challenges, generative AI’s biggest benefit, regardless of content type, is helping us to keep up with growing expectations. It is not replacing human talent. Nor is investment slowing down. On the contrary, casual experiments are giving way to more formal adoption.

Content marketing teams need customer data to optimize impact

AI’s extended reach is creating an opportunity for marketers to up their customer data game. After all, AI runs on data. In addition, parallel trends related to data privacy and the ongoing retirement of third-party cookies make it clear that businesses need more maturity in customer data and analytics.

Thankfully, one of the benefits of higher-quality data programs is that content marketers can do even better. By “better,” I mean produce more targeted content that results in higher customer engagement.

Customer data will result in better AI-generated content

Most marketing functions adopting generative AI so far have used off-the-shelf solutions. Even as content marketing teams are embedding those tools into their workflows, the most tech-forward organizations are building their own large language models using their own data (LLMs are the foundation on which gen AI platforms operate).

Not every organization has the resources to build its own model. Yet organizations can still augment standard models with in-house data for better outputs that require less manual fact-checking or style refinements.

Customer data drives better content marketing engagement

Beyond improving generative AI outputs, data maturity will also enable content marketers to more effectively use predictive analytics and machine learning to uncover insights into customer needs.

A perennial challenge for content marketers is emphasizing the right content to drive impact. One of the primary ways we have to stay ahead of copycat content is to write about what our customers want to know.

We may find that out by collecting and analyzing direct and indirect sources of customer data. Direct methods include surveys, voice of the customer programs, focus groups, and others. Indirect methods include channel tracking and social listening.

Interest in customer data is not new, but it continues to rise as a critical technology-driven content marketing trend because content teams still struggle so much to use it. For example, your organization may house the data you have in disparate systems. Or, relevant sources of data may belong to other functions that don’t want to or know how to share them with you.

For those reasons and others, businesses have increased investment in customer data platforms (CDPs) to centralize data and gain a single view of the customer to drive marketing practices.

Future tech will enable more efficient creation

Even with generative AI on their side and better data informing their work, content teams will need to up their game with sound processes and an easy-to-use technology stack. So, even as you embrace the hot technologies of the year, don’t forget to leverage your content marketing platform to get the most out of what you do to drive collaboration and streamline workflows.

Ask the Content Strategist: FAQs

How are marketing budgets expected to change in the next few years?

Sources like the semi-annual CMO Survey predict that if economic conditions improve, marketing budgets will gradually increase. In the meantime, content teams only increase their relevance by optimizing how they work and showing positive returns from current investments — including in your content marketing.

What are the potential drawbacks of relying heavily on generative AI for content creation?

One potential drawback of using AI for content is creating high volumes of low-quality content that includes misinformation. To avoid this risk, make sure to keep a human involved in the content creation process, and implement strong fact-checking practices as part of your content processes.

How can I leverage data to improve content marketing?

Leveraging data is not just about knowing your customer (though that is critical). It is also about knowing what is working in your content marketing program and what you need to stop doing to get the most out of your budget. That requires you to continue to leverage data to understand your audience, while also tracking content performance to identify opportunities for amplification.

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