2018 was a banner year for content personalization investments. More and more brands are rising to the marketing technology challenge and many are investing more in content personalization technology that will help them bring people closer to the content that matters most.
As brands build out their content personalization engines within their tech stacks, they realize the need for more content to meet the individualized content preferences for each customer. For example, a survey by Adobe reported that marketers and advertisers have added an average of 60% to their creative staff for content creation for targeting customer segments.
To catch up with the demand for personalized content, brands may feel they need to invest more man-power and resources into content creation. However, we believe that brands can utilize AI-based content personalization technology to help them scale faster and get more mileage out of their current content investment. Here are a few thoughts on how marketers can keep up with the need for more content for personalization without creating an abundance of new content.
1. Roadmap Your Content Personalization Strategy
Content marketing and personalization are both long-game efforts, and that’s why a critical success factor for content production that supports personalization is a roadmap. This involves defining marketing priorities across audiences and how content personalization can help you achieve those priorities. Your roadmap can help you keep your content production priorities in check, and it’s also a good way to manage upwards so your executive team and stakeholders are aware of how your transparent content production plans align to broader initiatives, including personalization.
2. Nail Down the Creative Brief to Make In-House Studios More Efficient
More brands are building out in-house content studios to scale their content marketing efforts. These studios provide the creative talent, manpower, operating structure and strategic vision to power a content personalization strategy. But studies find that in-house content studies are struggling to operate efficiently—42% of survey respondents reported the creative workflow is one of the biggest challenges and 67% reported that obtaining the necessary information just to begin a creative project was difficult. When content personalization stakeholders don’t have a clearly defined strategy, objective, or set of requirements for their personalization plans, then unnecessary churn starts to muddle the process, causing anguish and frustration among content creation teams. We recommend teams have a formalized process in place for gathering inputs from project stakeholders, also known as “the creative brief.”
3. Automate Content Selection and Delivery
When it comes to personalization, even down to the individualized level, creating a personalized content experience doesn’t always lie in creating net-new content for each individual—creating a personalized experience is about how content is selected and delivered. But even with a vast library of content at your fingertips, it can be a manual, time-consuming and, ultimately, subjective process to identify the most appropriate content for personalization and then execute the personalized web experiences and email campaigns in a scalable way.
With email, for example, curating a personalized experience requires tasks such as content selection, content development and list building. Our own studies show that most marketing teams spend more than 36 hours per week on manual email segmentation. However, email personalization tools that are based on machine learning allow technology to take over the more operational tasks through automation. What’s more, these tools instantly analyze all of your brand’s content and curate the most relevant experience for each subscriber based on multiple signals, such as user behavior, content consumption history and real-time trends.
The benefits of this approach are twofold: 1. You shift manpower resources away from tactical work, enabling your team to focus on more strategic email personalization priorities; and 2. Machine learning tools evaluate and leverage the content you already have, helping you get more mileage from your content creation efforts.
4. Focus on the Content That Inspires Action
While many brands are focused on and worried about generating more content, studies have found that the majority of content generated by the marketing function never gets used. These findings suggest that marketers should spend their time and resources understanding which content drives engagement and action, rather than continuously producing new content. To make better decisions about what content is needed and what content to create, marketers first need to understand what types of content inspire consumer action, and therein ROI. With Active Content Intelligence, for example, brands can better understand the characteristics of content that drive results, including audience engagement and conversion across content themes, topics, types and sources.
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