How effective is your site’s content? A mountain of research and articles focuses on optimizing landing pages and testing calls to action along visitor paths, but there’s surprisingly little information about understanding a site’s non-campaign-related content. Often, content is left on a site to die a slow, withering death or is changed only according to a routine, costly production schedule.
So let’s cover a few relatively simple steps you can take to help determine existing content’s lifetime, estimate an appropriate production schedule for content additions, and make content more relevant for your audience.
- Choose a content area to investigate, and establish your goals. If your site has a “case studies” area, a “help and support” section, or another content category that receives semi-frequent updates, start there. These areas are often designed to help customers make a decision or solve a problem. Understanding their long-term relevancy will benefit you and customers. Next, establish goals for the exercise by asking, “What do I want to learn?”
- Gather page-level data for a 6 to 12 month period. You need enough data to avoid inconclusive results and account for the fact online visitor lifetimes are often very short. Gather page-level data for your content category and have at least one of the following metrics across all pages: unique users, visits, or page views. Gather monthly data for each page in your content category. You’ll need to clean some of the data for pages that were recently posted and don’t have enough data associated with them. Next, know your site’s total unique users, visits, and page views for the period you’re investigating. That information will help you understand the content category’s popularity in relation to your site’s traffic.
- Note the relevant events that took place during the period you’re investigating. Events such as ad campaigns, product launches, and news releases can certainly influence site traffic. Knowing when these events took place will help put site traffic into context for the period you’re analyzing.
- Run a correlation analysis. Correlation is a statistical technique that shows how strongly variable pairs are related to one another. Look at content popularity over time to determine how relevant a given article will remain after it’s been posted. The correlation results will tell you how much variation exists from month to month, in other words, how correlated a given article is in month one with future months. This step requires some additional knowledge, advanced abilities in Excel, or the use of a statistics tool such as SPSS, S-PLUS or SAS. Some tools, such as SAS’ JMP, are easy to use and understand for beginners, powerful, and fairly good at illustrating results.
Two items worth noting:
- Correlation is not causation. For the example above, don’t assume a content popularity change four months after an article was posted is caused by time alone. Correlation merely notes there may be a relationship between variables.
- Correlation works best when the relationship between variables is linear. As one variable gets larger, for example, the other becomes larger or smaller in direct proportion. If you analyze data with curvilinear relationships (relationships don’t follow a straight line), use multiple regression to analyze your results.
- Analyze results, and take action. The results from step four will give you a strong sense of your content’s relevancy over time. Look for trends in results. Explain data anomalies by comparing the data’s peaks and valleys against overall site traffic and events that may have taken place during the analysis period.
Next, answer a few questions:
- When does content popularity tend to fade? If there’s a clear trend, use it to estimate an appropriate production schedule for pushing new content to your site, at least for the content area you analyzed.
- Are certain types of content more popular over time than others?
- Were any events responsible for driving content popularity, such as email blasts or ad campaigns?
- Were there any structural changes to the site that improved visitor navigation to the analyzed content area?
Once you’ve answered these questions you’ll have a very strong sense of your content’s lifetime and a framework to use for future analysis.
Missing from this picture is audience feedback. How customers feel and think about the information you provide is just as relevant and informative as the raw data you analyze.
If you have a content-rich site and don’t have a visitor feedback survey on it, post one. Even a simple three-question radio button survey can be incredibly informative over time. It can help your content team determine not only what content is missing and beneficial but also when to modify or remove existing content. It’s a valuable data set to pair with your traffic data.
Determining content’s lifetime can be tricky. Many factors can influence a site’s content popularity from month to month. What’s important is to better understand your content’s long-term relevancy. Understanding content’s lifetime can greatly improve your ability to speak relevantly to existing customers and market effectively to new ones.
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