Just like paid, social, or affiliate marketing,
content marketing analytics activity may be influenced by data and analytics.
Content marketers aren't the target audience for
most current guidelines on analytics. On the contrary, the examples and
explanations are aimed at targeting optimization techniques and paid to acquire
content marketing analytics specialists.
The Heart
and Soul of content marketing analytics
.webp "The Heart and Soul of content marketing analytics")
Any good content marketer should be able to address
these business concerns using analytics, in my view,
Analytics tell us a lot about the efficacy of our
existing content marketing activities.
● So what were the content marketing
possibilities we’re missing as represented by analytics?
● How can we maximize our content
marketing efforts in the short term?
● At what stages in the funnel are
we dropping users?
● Can we do anything to seal these
vulnerabilities (or collaborate with a team that can)?
● Do we find patterns or insights
that tell us which sorts of content are most successful at acquiring high-value
leads/customers?
● What can analytics offer me about
fresh content marketing ideas and campaigns?
Typically, data must be able to drive your choices
as a content marketer exactly as intended if you’re a hired marketer or SEO.
There’s no need for content to be detached from
business measures, and utilizing data does not invalidate your capacity to
employ creativity.
content marketing analytics: The Quantitative Stuff
In this part, we'll focus on Google Analytics, but
you're free to utilize any other digital analytics platform you'd like.
I have even more experience with Analytics since
it’s free and highly frequent, so I’ll write using an example:
How does
content marketing analytics measure the success of content marketing?
.webp "How does content marketing analytics measure the success of content marketing?")
As we addressed in the ROI of content, you do need
to create the yard post for how well you are performing.
To employ an overused but accurate adage,
"what gets measured gets controlled," we'll go with it.
Analytics helps you to evaluate whether you are
making meaningful progress towards your content objectives.
There is a distinction between measuring and analytics.
A typical issue amongst old-school data analytics professionals.
Measurement is merely measuring that something must
have occurred. Analytics is establishing a context and direction of the
evaluation.
To put it another way, analytics aids in the process
of making choices based on data.
Analytical data would inform me that the day before
and the day following a piece of content had 100 views, respectively.
In the end, analytics should help you make smarter
business choices.
Different types of content marketing analytics
Platform-specific analytics built right within the
platform to aid in the analysis of social media postings
External tools, e.g. Nudge, to gain meaning across
many different sorts of material
Other examples within the vast range of content
analytics technologies include data/text mining, template matching,
visualization, semantic analysis, neural networks, and complicated event
processing, just to mention a few.
conclusion
An already lengthy blog article won't be able to
cover all that needs to be. The point is, that content marketing analytics
don't have to be a contradiction. Instead, you may learn to be a data-driven
content marketer, which will help you develop your right brain.
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reference
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