A Beginner’s Guide to Content Analytics

A Beginner’s Guide to Content Analytics

Originally published on the MindTouch Blog.

One of the most appealing aspects of technical writing is that, unlike other types of writing, there is arguably a best way to present technical content to users. That’s because the best presentation is whatever makes users most successful, which also likely aligns with your business goals.

It’s a fun challenge to constantly strive to optimize content to best meet user needs. Expert wordsmithing, thoughtful organization, and strategic delivery are important facets of successful technical content. However, incorporating content analytics is a necessary effort to achieve the most effective content.

What is the Definition of Content Analytics?

A popular definition was coined by Avinash Kaushik, the author of Web Analytics 2.0:

Web analytics is the analysis of qualitative and quantitative data from your business and the competition to drive a continual improvement of the online experience that your customers and potential customers have, which translates to your desired outcomes (both online and offline).

It’s a hefty definition, but we can unpack it by looking at the three most important components.

1. Qualitative and Quantitative Data

As you embark on a content analytics initiative, take the time upfront to understand everything you can measure. That includes identifying all your web-based assets and confirming they are being tracked properly through your analytics tool. Is your content still in PDFs or long-form articles that make it more difficult to measure user engagement? It’s time to consider a microcontent strategy to deliver the right content to your customers at the right time.

For your qualitative data, take inventory of all the ways your company collects customer feedback. Be sure to check with every department because there could be a survey or isolated feedback channel you’re not aware of.

2. Continual Improvement

How do you incorporate content analytics into your processes to achieve continual improvement? Consider a framework of two strategies that create a positive feedback loop:

  1. Metrics to optimize your work – Incorporate analytics that allow you to do your current job, but armed with data. Search terms, view counts, and click paths are some metrics that can help you prioritize efforts and drive changes.
  2. Metrics to measure impact – Measure trends that feed into organizational KPIs and show how you moved the needle. These metrics should reflect how your content influences key conversion paths.

Over time, as you use data to optimize your work, you’ll see that reflected when you measure the impact of your effort. This will continue to feed your optimization strategy.

3. Desired Outcomes

Your analytics efforts will enable continual improvement to achieve desired outcomes, which align with your main business objectives. For example, maybe you are interested in behavioral and search analytics. When you prioritize what you measure in the strategies outlined above, make sure the focus is to find actionable insights that can directly improve your conversions and desired outcomes. You’re essentially working towards a data-driven system with your content as the mechanism to achieve company goals.

Tips for Getting Started with Analytics

  • Be consistent when trending – When collecting metrics to track changes over time, use the same data drilled down the same way. This may seem obvious, but even the same filters applied in a different order can alter the same metric.
  • Benchmark and establish baselines – Then, look for anomalies or changes in trends over time or across dimensions. Finding an anomaly early on can uncover an issue before it amounts to additional costs.
  • Include content analytics processes on your next performance goals – This will commit you to the effort and can help you obtain needed resources.
  • Be aware of your assumptions – When you think you’ve drawn a reasonable conclusion from the data, ask the golden question: What else could this mean? When you finalize your conclusions, record your assumptions so you can revisit them if needed.

Don’t be afraid to not gain clear insights right away. It takes time to find the right way for content analytics to help you achieve the most effective content. Pursuing content analytics may lead you to ask more questions than provide clear answers at first, but that’s part of the fun and value of it.

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