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Top 15 Most Popular Content Analytics Mistakes

July 29th, 2013 by

Top 15 Most Popular Content Analytics MistakesContent analytics is a very useful tool these days. In fact, any marketing manager who underestimates the importance of content analytics is bound to run into trouble. Such “trouble” may include missing important sales goals and objectives, failing to maximize SEM/SEO initiatives, and, in extreme cases, straying from the mission of the organization.

The Mistakes: 

Inadequate investment: Although it makes sense to try to save money, there is such a thing as being too stingy. Maybe you cannot allocate as much money as the big corporations but, at the very least, make sure that what you budget for content analytics is commensurate to what you intend to get out of it.

Lack of proactive follow-through: Don’t get so bogged down analyzing data that you fail to take action periodically based on what you learned.

Failing to sift through data properly: There is going to be a huge amount of data coming your way. Each set of data will bring different demands; make sure you have in place a way to properly separate and manage different sets of data.

Underestimating the complexity of analytics: Some people put too much faith on software and staff. Instead, develop a proper respect, acknowledging that, at best, you can only manage a small percentage of what’s available out there.

Poor/inexistent high-quality content creating strategies: The quality of the content you offer can make or break your site. Therefore, strive to reach for the best content.

Utilizing wrong metrics: Are your data-analyzing “dials” set correctly? Is the data you’re pulling directly relatable to specific goals?

Not focusing properly on clients: Some marketers are so busy concentrating on data/methodology that they forget about clients and what their needs and expectations.

Failing to double-check accuracy of information: Content that is entertaining but full of errors can’t but hurt your site’s credibility!

Failing to focus on essential things & follow logical steps: This is where a clearly defined mission statement can help guide decision-making. Content marketing analytics should follow organization-specific action plans.

Not structuring accounts properly: Google Analytics, for example, specifies how to properly classify accounts; nevertheless, people often try to adapt programs without pausing long enough to consider potential ramifications.

Not properly separating “administrator” and “user” roles: Most content analytics software give special privileges to administrators while placing limitations on users; ignoring these distinctions can create problems.

Failing to set analytics goals correctly: Whether it is because of software-inherent limitations or a lack of understanding of enterprise goals, not having clear goal-oriented guidance can be disastrous.

Failing to set up event-tracking: This is especially important when monitoring visitor/user interactions.

Improperly managing e-commerce data: Naturally, each set of data is different. E-commerce data, however, requires special attention since it encompasses more than one type of data-sets.

Improperly segmenting data: This is perhaps one of the most under-estimated mistakes people make. Data segmentation, probably because it is generally conducted by machines, is taken for granted but, if done incorrectly, can lead to incorrect interpretations.

Although content analytics is probably one of the most promising prognosticating tools, it is rarely utilized to its full potential. Maybe the technology is too new or maybe people are relying too much on computers to do their thinking. It should suffice to say, though, that content analytics is merely a tool. Like every other “tool,” it works best when used appropriately and at the right time.

Fred F is a freelance writer available on WriterAccess, a marketplace where clients and expert writers connect for assignments.

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