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Sorina MoneMarketer, Magnolia
Where Does Content Analytics Fit in the Content Workflow?
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Many brands find themselves almost obsessed with content creation. The sheer volume of content required to appeal to the multiple customer types they serve and eventually personalize that content puts content production front and center of content marketing priorities for most organizations.
However, just as important is analyzing that content to make sure you produce the correct type of content for your audience and that your content is yielding the results you want. According to the Content Marketing Institute, many marketers are aware of the importance of content analytics, with 81% of marketers indicating that their organization had established metrics for tracking content performance. Another 88% of respondents also stated that they used analytics tools to assist their content marketing efforts.
It's clear that brands are well aware of the value analytics can bring, but they may not be using those analytics often enough or at the right time. In this article, we'll explain where content analytics fits in the content workflow, define some of the metrics that matter and show you how you can further optimize your content workflows with the help of a modular DXP.
Breaking Down the Content Workflow
The content workflow is the set of tasks a team needs to complete in order to create and publish a piece of content. Content workflows are essential processes that should be documented so that teams are aware of their responsibilities.
But where does analytics fit in the workflow? A typical content workflow may look like this:
Goal Setting Phase: In this stage, your brand may be focusing on the types of content that need to be produced to meet overall company goals. This could include which channels must be targeted, KPIs for how much content should be produced, and the value you want to get out of the content.
Strategy Phase: In this phase, you may choose to focus on gathering information about each of the specific channels that you've chosen and deciding which content types will work best for each channel. In this stage, each piece of content's goal will also be decided whether that means providing awareness about your brand, educating visitors about the product you offer or directly trying to convert site visitors into customers.
Creation Phase: In the creation phase, content is produced. This includes writing, filming or editing content before publication.
Publishing Phase: In the publishing phase, content is finally being sent out for production. This may include final editing and reviewing, deciding on which channels the content will be added to, and creating that content into a CMS before publication to one or multiple channels.
Promotion & Distribution Phase: Next, in the promotion and distribution phase it's time to start promoting the content that has been published and try to drive traffic to that piece of content, either through social media, ads, email campaigns, or another format.
Analysis Phase: Finally, in the analysis phase, content is analyzed to determine how much traffic is produced as a result, identifying which channel or channels the content needs to be attributed to and determining which KPIs have been met or not met as a result of that content production. In the typical content workflow, analytics may seemingly come only at the end. However, that places limitations on what can be achieved with proper content analytics and how it can fit into other content workflow areas to improve overall performance.
Magnolia Marketing Analytics Connector Pack
Learn more about the Marketing Analytics Connect Pack and how it works in Magnolia by reading our walkthrough
Goal Setting: Content analytics can help to better understand which goals are realistic given the previous marketing campaigns that have been completed and the results obtained.
Strategy: Analytics can help provide research about which channels might perform the best, which types of content will resonate with different target audience members, and which pieces of content should be produced.
Creation: Analytics can provide customer data access, allowing content creators to focus their efforts on content that appeals to the target audience and helps them avoid creating wasted content.
Publishing, Promotion & Distribution: Content analytics can provide more accurate information about which content pieces should be published where and when so that creators know ahead of time which channels are likely to produce the best results.
When measuring content, it's essential to conduct a comprehensive analysis, identifying where opportunities lie and how to improve the quality of marketing campaigns.
Which Metrics Matter?
Each stage of the content workflow can produce a host of valuable insights that companies and marketing teams can use to enhance their effectiveness. However, they must first determine which metrics matter the most to avoid overcollection of data.
Production Metrics: By measuring the amount of each content type produced, the authors of each piece of content, the categories, and the number of pieces of content allocated to each buyer persona, marketing teams can come up with an effective content production plan to meet content volume demands.
Engagement Metrics: Engagement data such as the number of shares, likes and comments on social media, the number of backlinks gathered for SEO and more can indicate which content resonates the most or the least with a particular target audience.
Performance Metrics: The content that produces the most traffic or the best performing posts over a particular period can indicate whether or not KPIs are being met.
Revenue: Marketing attribution can be used to determine the channels and content pieces that produce the most conversions and sales.
Optimize Content Workflow with Magnolia CMS
Analytics is a critical component of the content workflow, but it cannot be a standalone or siloed piece of the puzzle or else brands will find it challenging to improve the effectiveness of the content. Content analytics needs to be connected so you can analyze it throughout the entire workflow, and that can be done with the help of a modular DXP.
Magnolia CMS provides a DXP platform that can help you launch digital experiences that delight your customers.
With the Analytics Connector Pack, you can integrate analytics directly into the CMS, providing a native view that helps you make data-driven decisions that improve the customer experience. Marketing data can be viewed in context through highly customizable visual dashboards, whether you're using out of the box analytics tools or connecting other tools that fit your particular industry.
When viewing in context like this, you can gather personalization data to determine how customers responded to previous campaigns, streamlining the content creation process and ensuring that the right content gets delivered at the right time.
