A 2021 survey by Ascend2 revealed that a collective 64% of marketers use data to drive some or most of their marketing decisions. This is not to mention that another 24% make all marketing decisions based on data.
Graph showing what percentage of marketers use data to inform their marketing decisions
Clearly, content marketers and content strategists recognize the performance-driven approach as fuel for effective content solutions. And for a good reason since this approach positions organizations to:
Continuously assess how their content is performing and why
Make informed decisions to improve content performance and better meet the needs of consumers in the future
Both are critical to content marketing success. So let’s explore further what performance-driven content looks like, why it’s essential, and how to set it up successfully.
Understanding the basics of content performance
Several years ago, I published Enterprise Content Strategy: A Project Guide, outlining a content strategy framework based on a performance-driven model. Performance-driven content looks like this:
What a performance-driven content strategy framework looks like
This diagram represents the phases of a performance-driven framework, with governance at the centre.
“Putting these phases together creates a cyclical process. Within this closed-loop process, an experience never exists in a complete state; measurements and continual evolution inform future priorities.” (Enterprise Content Strategy, Page 9).
What activities are critical for the success of such a model? They include the following:
Planning of project goals and scope
Assessment of current experiences and competitive models
Defining the new content experience and appropriate key performance indicators (KPIs)
Designing of the new or updated content experience
Building of content to fill the experience
Publishing and distribution of the content
Measuring content performance
Optimizing the experience based on data
The process of implementing a performance-driven content model
Let’s look at how such a model can function.
I use the following diagram in my book to show how a performance-driven approach can work within an organization:
Components of a data-driven content model
Diagram 1-2 shows three columns: inputs, meeting and outputs, with the first column containing a series of information required for a performance-driven model.
With this model, you should ask yourself two questions. First, how is our content performing against its initial objectives? Second, how can all these inputs—trends, user data and content marketing metrics, for example—inform future content priorities?
Need to Know: After content is published, you should regularly review each of the input types, analyse the data they yield, and then make recommendations for future content investments.
For example, outputs of this process might include any or all of the following:
Recommendations for optimizing existing content
Identification of new areas worth investing in for future content
Validation on which content performs well
Content that could be sunset or archived
Good to Know: Done well, performance-driven content assesses consumers’ needs, behaviours, attitudes and creates a user-centric approach to content creation.
Thus, using this approach, your organization can understand what content is successful and why it’s successful—and spot future opportunities. In general, this approach can create more relevant, functional, and compelling content for the consumer.
Setting up a performance-driven content model
Performance-driven content starts by setting up content lifecycles so that each can be measured, evaluated and then acted upon. To do so, build the following approach into your content publishing model. (For each of these areas, I’ll paraphrase chapters 7 and 8 of my book.)
1. Identify unique content lifecycles
Identify each content type (E.g., articles, product pages or news updates) or format type (E.g., videos, images or infographics) that will have its own unique lifecycle.
Use diagram 1-3, which is similar to the first closed-loop model diagram, as a starting point.
High-level overview of a typical content lifecycle
You likely already have content lifecycles if you publish content. If that’s the case, focus on steps 6 and 7, detailing the sub-steps for each and ensuring that you have strong content governance to support them.
2. Measure content performance
For step 6, “Evaluate through metrics and user feedback”:
If you haven’t already, identify which objectives are necessary for content success. What is your end goal?
Select the appropriate content marketing metrics to measure progress toward objectives. To give you a starting point, this infographic developed by Rebecca Schneider and I demonstrates which metrics are best for which channels.
Common content performance metrics by channel
Define tactics for each area in the inputs column of diagram 1-2 above. For example, plan meetings to ascertain new business needs, processes to stay informed about the latest industry trends, and mechanisms to capture user feedback and insights. Roll all of this information into a dashboard or format you can use to analyse the data.
Ensure the right roles to execute your performance content marketing strategy. These include analytics experts, user researchers, content strategists, and user experience practitioners.
3. Evaluate your content based on the data
For step 7, “Optimise or leave as-is”:
Look at whether the content under evaluation meets the objectives you set for it. Does it convert users in the ways you want? Does it get shared at your desired rate? Are calls to customer support lessened due to quality troubleshooting content online? If your content performs as desired, leave it alone.
For content that performs exceptionally well, invest in similar and related content. Or find ways to promote the topic within the content in additional formats such as video. Analyse why it works to uncover keys for success that you can use for other content within your experience.
💡 Pro tip: Don’t remove or change the placement of content that performs well or above expectations (i.e., don’t move it to a different place on a website page).
For content that doesn’t perform well, determine why. Can the user find it? Is it optimised for the channel where it lives? Is it well-written? Is the topic or theme relevant, useful and interesting to your users?
4. Reassess your user journey
What if consumers do view the content but don’t convert or take your desired action? Reassess your user and consumer journeys. Ask yourself: Can the consumer easily complete the next step in a journey? Does the consumer find the content helpful or relevant?
5. Reconsider your goals
If you can’t pin down any major issues with the content or user journey, review your objectives and make sure they’re attainable. Perhaps your content is acceptable but is “underperforming” due to unrealistic objectives set by your organisation.
6. Analyse competitor content
Look at competitive sites to see how they use similar content and how their audiences respond to it. For example, does a particular content type seem to result in tonnes of social shares for competitors? Take note of their strategies and look for performance clues. Then, to finalise your assessment, do user testing.
7. Optimise content for better performance
Based on your analysis up to this point, outline improvements to your existing content and investments in new content. Also, identify unnecessary content that can be archived.
Performance Content Models: 5 keys to success
Having understood a bit more about the model, let’s turn to five key points to stand up a performance-driven model for success. The first three, which focus on data-driven approaches, come from Tom Redman, author of Data Driven: Profiting from Your Most Important Business Asset.
1. “Cast a wide net”
As Tom notes, many organisations place an emphasis on analytics as a sole input. Yet, your Google Analytics data alone isn’t enough to form a comprehensive picture of how your content is performing and why.
Casting a wide net, on the other hand, means leveraging many inputs, including those outlined above in diagram 1-2. Use them as inspiration to build a well-rounded model (based on all inputs) with which you can regularly and accurately assess your content.
2. Take data out of IT departments
According to Tom:
“Organisations that get data out of IT improve data quality faster!”
(IT is fine for implementing technology solutions but these teams should not own or define the data itself.)
It would be best if you had experts in data—analytics practitioners, content strategists, user researchers, search engine optimization (SEO) experts and social media practitioners—to own the definitions and maintenance of data to ensure its quality and integrity.
3. Place a high value on data integrity
Not all data is equal. You must use relevant, quality data—metrics, analytics, and KPIs—for continued success. Investing in good data involves starting with clear objectives for your content and, from those, defining KPIs to measure success.
Remember, a metric should answer as many of the following as possible: who, what, where, when, why, and how. For example, a well-defined goal might be: to increase purchases via our website by 20% within six months.
Ensure that each piece of content has a goal, objectives, targeted users and then measure whether these yield success through metrics.
4. Use roadmaps and start small
Measure, evaluate and test over time. Especially for omnichannel solutions and personalization, both of which require performance-driven approaches for success.
Stewart Pratt, former SVP of Strategy & Analysis at DigitasLBi, rightly noted: "Nothing overcomes organizational rigidity and promotes adoption better than success. Any solid roadmap should have a bias towards action, prioritising low-barrier opportunities and celebrating quick wins."
5. Remember the people element
Forget the people element, and you fail. To avoid this pitfall, you need people in your organization who can analyse current performance and recommend solutions.
Additionally, remember that consumers provide the most up-to-date information about their needs and behaviours as they change over time. Sofollow in the footsteps of Netflix, which has historically used what it calls “consumer science” to test new data-driven content ideas with consumers. Never forget that consumer input is essential for defining worthy content focus areas.
Selecting the right content KPIs
In addition to the above, key performance indicators—mentioned earlier—are another critical component of performance content success. You can’t accurately measure content performance without having set the proper KPIs. So it’s important to know which performance indicators correspond to which content types.
For example, for blog posts and articles, you might measure website traffic, new vs. returning visitors, bounce rate, time on page, unique page views and page views per visit, referral sources, and geographic trends.
Yet, for a pay-per-click campaign, for instance, KPIs would differ. They would include cost per click, click-through rate, conversion rate, cost per conversion, return on ad spend, and so on.
Think about what type of content your organisation produces to more easily decide on the right metrics to track. It can also be helpful to work backward from the goals you set, identifying each step in the customer journey toward that objective. You’ll then notice that each step corresponds with a metric such as website traffic, engagement or sales.
Good to Know: As a rule of thumb, good KPIs are both closely linked to your content goals and work for your content type. So, look for overlap.
A Dynamic Duo: consumer inputs and technology
Technology too plays a significant role in content performance (but as a tool, not as the solution). Let’s look at a few areas where technology and consumer inputs converge:
Measure cross-channel performance. According to VP of Marketing at SundaySky, Rachel Eisenhauer, a comprehensive view of the entire consumer journey with your brand and across various channels is critical. This may require integration of technology and systems such as web analytics, customer relationship management software, and in-store data.
Leverage consumer research and user testing. Analytics, social listening, and clout measuring tools are helpful. As are surveys…if and when you can get a sizable portion of your users or customers to participate. However, there’s no substitute for building focus groups and one-on-one user testing into your content assessment process. Nielsen Norman Group created an excellent guide on best practises for testing content with users to get you started.
Build annual or semi-annual content audits into your content evaluation process. Paula Land, author of Content Audits and Inventories, stressed: "Regular check-ups on the health of your content help you find and address problems or gaps early, so you can avoid making larger, more expensive fixes down the road. Auditing regularly is an important part of a performance-driven content strategy, enabling ongoing optimisation for best results."
Download our Content Audit Spreadsheet to easily take inventory of your content, gain the insights you need, and identify gaps.
Achieving Optimal Content Performance
Creating performance content and achieving content marketing success are not without their challenges.
Both require a significant commitment and comprehensive approach not just from content teams and marketing teams but also from the entire company.
But achieve that unity, and you’ll be able to create user-centric content that reaches and even surpasses your business’s objectives. Why is this?
Having a performance-driven model at the core of your digital marketing strategy means that your content decisions:
are based on reliable data, insights, and consumer research;
are scalable, which can help you progressively meet more challenging objectives;
and can evolve from a series of ongoing inputs and measurements.
Done right, this approach will streamline your content workflow and, more importantly, future-proof your organisation’s content ecosystem.
A 2021 survey by Ascend2 revealed that a collective 64% of marketers use data to drive some or most of their marketing decisions. This is not to mention that another 24% make all marketing decisions based on data.
Graph showing what percentage of marketers use data to inform their marketing decisions
Clearly, content marketers and content strategists recognize the performance-driven approach as fuel for effective content solutions. And for a good reason since this approach positions organizations to:
Continuously assess how their content is performing and why
Make informed decisions to improve content performance and better meet the needs of consumers in the future
Both are critical to content marketing success. So let’s explore further what performance-driven content looks like, why it’s essential, and how to set it up successfully.
Understanding the basics of content performance
Several years ago, I published Enterprise Content Strategy: A Project Guide, outlining a content strategy framework based on a performance-driven model. Performance-driven content looks like this:
What a performance-driven content strategy framework looks like
This diagram represents the phases of a performance-driven framework, with governance at the centre.
“Putting these phases together creates a cyclical process. Within this closed-loop process, an experience never exists in a complete state; measurements and continual evolution inform future priorities.” (Enterprise Content Strategy, Page 9).
What activities are critical for the success of such a model? They include the following:
Planning of project goals and scope
Assessment of current experiences and competitive models
Defining the new content experience and appropriate key performance indicators (KPIs)
Designing of the new or updated content experience
Building of content to fill the experience
Publishing and distribution of the content
Measuring content performance
Optimizing the experience based on data
The process of implementing a performance-driven content model
Let’s look at how such a model can function.
I use the following diagram in my book to show how a performance-driven approach can work within an organization:
Components of a data-driven content model
Diagram 1-2 shows three columns: inputs, meeting and outputs, with the first column containing a series of information required for a performance-driven model.
With this model, you should ask yourself two questions. First, how is our content performing against its initial objectives? Second, how can all these inputs—trends, user data and content marketing metrics, for example—inform future content priorities?
Need to Know: After content is published, you should regularly review each of the input types, analyse the data they yield, and then make recommendations for future content investments.
For example, outputs of this process might include any or all of the following:
Recommendations for optimizing existing content
Identification of new areas worth investing in for future content
Validation on which content performs well
Content that could be sunset or archived
Good to Know: Done well, performance-driven content assesses consumers’ needs, behaviours, attitudes and creates a user-centric approach to content creation.
Thus, using this approach, your organization can understand what content is successful and why it’s successful—and spot future opportunities. In general, this approach can create more relevant, functional, and compelling content for the consumer.
Setting up a performance-driven content model
Performance-driven content starts by setting up content lifecycles so that each can be measured, evaluated and then acted upon. To do so, build the following approach into your content publishing model. (For each of these areas, I’ll paraphrase chapters 7 and 8 of my book.)
1. Identify unique content lifecycles
Identify each content type (E.g., articles, product pages or news updates) or format type (E.g., videos, images or infographics) that will have its own unique lifecycle.
Use diagram 1-3, which is similar to the first closed-loop model diagram, as a starting point.
High-level overview of a typical content lifecycle
You likely already have content lifecycles if you publish content. If that’s the case, focus on steps 6 and 7, detailing the sub-steps for each and ensuring that you have strong content governance to support them.
2. Measure content performance
For step 6, “Evaluate through metrics and user feedback”:
If you haven’t already, identify which objectives are necessary for content success. What is your end goal?
Select the appropriate content marketing metrics to measure progress toward objectives. To give you a starting point, this infographic developed by Rebecca Schneider and I demonstrates which metrics are best for which channels.
Common content performance metrics by channel
Define tactics for each area in the inputs column of diagram 1-2 above. For example, plan meetings to ascertain new business needs, processes to stay informed about the latest industry trends, and mechanisms to capture user feedback and insights. Roll all of this information into a dashboard or format you can use to analyse the data.
Ensure the right roles to execute your performance content marketing strategy. These include analytics experts, user researchers, content strategists, and user experience practitioners.
3. Evaluate your content based on the data
For step 7, “Optimise or leave as-is”:
Look at whether the content under evaluation meets the objectives you set for it. Does it convert users in the ways you want? Does it get shared at your desired rate? Are calls to customer support lessened due to quality troubleshooting content online? If your content performs as desired, leave it alone.
For content that performs exceptionally well, invest in similar and related content. Or find ways to promote the topic within the content in additional formats such as video. Analyse why it works to uncover keys for success that you can use for other content within your experience.
💡 Pro tip: Don’t remove or change the placement of content that performs well or above expectations (i.e., don’t move it to a different place on a website page).
For content that doesn’t perform well, determine why. Can the user find it? Is it optimised for the channel where it lives? Is it well-written? Is the topic or theme relevant, useful and interesting to your users?
4. Reassess your user journey
What if consumers do view the content but don’t convert or take your desired action? Reassess your user and consumer journeys. Ask yourself: Can the consumer easily complete the next step in a journey? Does the consumer find the content helpful or relevant?
5. Reconsider your goals
If you can’t pin down any major issues with the content or user journey, review your objectives and make sure they’re attainable. Perhaps your content is acceptable but is “underperforming” due to unrealistic objectives set by your organisation.
6. Analyse competitor content
Look at competitive sites to see how they use similar content and how their audiences respond to it. For example, does a particular content type seem to result in tonnes of social shares for competitors? Take note of their strategies and look for performance clues. Then, to finalise your assessment, do user testing.
7. Optimise content for better performance
Based on your analysis up to this point, outline improvements to your existing content and investments in new content. Also, identify unnecessary content that can be archived.
Performance Content Models: 5 keys to success
Having understood a bit more about the model, let’s turn to five key points to stand up a performance-driven model for success. The first three, which focus on data-driven approaches, come from Tom Redman, author of Data Driven: Profiting from Your Most Important Business Asset.
1. “Cast a wide net”
As Tom notes, many organisations place an emphasis on analytics as a sole input. Yet, your Google Analytics data alone isn’t enough to form a comprehensive picture of how your content is performing and why.
Casting a wide net, on the other hand, means leveraging many inputs, including those outlined above in diagram 1-2. Use them as inspiration to build a well-rounded model (based on all inputs) with which you can regularly and accurately assess your content.
2. Take data out of IT departments
According to Tom:
“Organisations that get data out of IT improve data quality faster!”
(IT is fine for implementing technology solutions but these teams should not own or define the data itself.)
It would be best if you had experts in data—analytics practitioners, content strategists, user researchers, search engine optimization (SEO) experts and social media practitioners—to own the definitions and maintenance of data to ensure its quality and integrity.
3. Place a high value on data integrity
Not all data is equal. You must use relevant, quality data—metrics, analytics, and KPIs—for continued success. Investing in good data involves starting with clear objectives for your content and, from those, defining KPIs to measure success.
Remember, a metric should answer as many of the following as possible: who, what, where, when, why, and how. For example, a well-defined goal might be: to increase purchases via our website by 20% within six months.
Ensure that each piece of content has a goal, objectives, targeted users and then measure whether these yield success through metrics.
4. Use roadmaps and start small
Measure, evaluate and test over time. Especially for omnichannel solutions and personalization, both of which require performance-driven approaches for success.
Stewart Pratt, former SVP of Strategy & Analysis at DigitasLBi, rightly noted: "Nothing overcomes organizational rigidity and promotes adoption better than success. Any solid roadmap should have a bias towards action, prioritising low-barrier opportunities and celebrating quick wins."
5. Remember the people element
Forget the people element, and you fail. To avoid this pitfall, you need people in your organization who can analyse current performance and recommend solutions.
Additionally, remember that consumers provide the most up-to-date information about their needs and behaviours as they change over time. Sofollow in the footsteps of Netflix, which has historically used what it calls “consumer science” to test new data-driven content ideas with consumers. Never forget that consumer input is essential for defining worthy content focus areas.
Selecting the right content KPIs
In addition to the above, key performance indicators—mentioned earlier—are another critical component of performance content success. You can’t accurately measure content performance without having set the proper KPIs. So it’s important to know which performance indicators correspond to which content types.
For example, for blog posts and articles, you might measure website traffic, new vs. returning visitors, bounce rate, time on page, unique page views and page views per visit, referral sources, and geographic trends.
Yet, for a pay-per-click campaign, for instance, KPIs would differ. They would include cost per click, click-through rate, conversion rate, cost per conversion, return on ad spend, and so on.
Think about what type of content your organisation produces to more easily decide on the right metrics to track. It can also be helpful to work backward from the goals you set, identifying each step in the customer journey toward that objective. You’ll then notice that each step corresponds with a metric such as website traffic, engagement or sales.
Good to Know: As a rule of thumb, good KPIs are both closely linked to your content goals and work for your content type. So, look for overlap.
A Dynamic Duo: consumer inputs and technology
Technology too plays a significant role in content performance (but as a tool, not as the solution). Let’s look at a few areas where technology and consumer inputs converge:
Measure cross-channel performance. According to VP of Marketing at SundaySky, Rachel Eisenhauer, a comprehensive view of the entire consumer journey with your brand and across various channels is critical. This may require integration of technology and systems such as web analytics, customer relationship management software, and in-store data.
Leverage consumer research and user testing. Analytics, social listening, and clout measuring tools are helpful. As are surveys…if and when you can get a sizable portion of your users or customers to participate. However, there’s no substitute for building focus groups and one-on-one user testing into your content assessment process. Nielsen Norman Group created an excellent guide on best practises for testing content with users to get you started.
Build annual or semi-annual content audits into your content evaluation process. Paula Land, author of Content Audits and Inventories, stressed: "Regular check-ups on the health of your content help you find and address problems or gaps early, so you can avoid making larger, more expensive fixes down the road. Auditing regularly is an important part of a performance-driven content strategy, enabling ongoing optimisation for best results."
Download our Content Audit Spreadsheet to easily take inventory of your content, gain the insights you need, and identify gaps.
Achieving Optimal Content Performance
Creating performance content and achieving content marketing success are not without their challenges.
Both require a significant commitment and comprehensive approach not just from content teams and marketing teams but also from the entire company.
But achieve that unity, and you’ll be able to create user-centric content that reaches and even surpasses your business’s objectives. Why is this?
Having a performance-driven model at the core of your digital marketing strategy means that your content decisions:
are based on reliable data, insights, and consumer research;
are scalable, which can help you progressively meet more challenging objectives;
and can evolve from a series of ongoing inputs and measurements.
Done right, this approach will streamline your content workflow and, more importantly, future-proof your organisation’s content ecosystem.
Kevin P. Nichols is an award-winning thought leader, digital industry enthusiast, and author with more than 20 years of professional experience. In 2014, he coauthored (with Donald Chesnut) UX For Dummies and in 2015, Enterprise Content Strategy: A Project Guide. Recently, Kevin left his position of Global Head of Content Strategy at SapientNitro, where Kevin grew that team to become one of the largest and most successful in the world. Currently, Kevin is devoting his time to promoting and developing his personal brand. Kevin has been a forerunner and major contributor to user experience and content strategy. He has authored numerous articles on content strategy, user experience, personalization, omnichannel and digital strategy. You can learn more about him at kevinpnichols.com. His Twitter handle is @kpnichols.
Share on Facebook
Share on Twitter
Share on LinkedIn
Share with email
