Let’s say you’ve just taken editorial responsibilities for an existing website or blog. You know from my article, “What it takes to be a great content marketer,” that you’re going to need an editorial process for planning, reviewing, and publishing content on an ongoing basis. And you know that an editorial calendar will be central to your process.
As you begin to manage an editorial calendar and plan what comes next, it helps to evaluate the content that’s already been published.
Import.io makes it easy to scrape article meta data from your website into a spreadsheet. It can scrape article titles, authors, dates, and categories. It can also scrape stats about the articles (if the stats are displayed on the article), such as the number of comments, Facebook shares, tweets, etc. Once a data set has been generated, I like to clean it up in Excel. Special care should be taken to correctly format dates for easy import into Tableau.
Once imported into Tableau, I visually analyze the website data that’s been scraped. For the purpose of illustration, I scraped article meta data from a content marketing blog that I really enjoy by Express Writers. For each article on the site, I was able to pull the title, author, publish date, and category. I was also able to pull the number of comments, Facebook shares, tweets, Google Plus shares, and LinkedIn shares. Here’s a small sample of things that I can visualize with this data:
- Posting activity by author
The site added authors in 2015. 2013 and 2014 had only one author. In contrast, 2015 has had 8 different authors produce content.
- Cadence of posts by category
There’s a very consistent cadence of articles in categories including content marketing and copywriting. Other categories like website content and press releases started out strong in 2014, but haven’t been used at all in 2015.
- Category virality
Using calculated fields in Tableau, I’ve summed up the total number of social shares by category across Twitter, LinkedIn, Facebook, and Google Plus. Then, within each category, I’ve divided the total shares by the number of articles. This produces an average number of shares per article by category. It looks like infographics, articles about social media, and articles about content marketing are the most viral content produced on the site.
- Author virality
Tableau also allows me to study author virality, which shows the average number of shares per article for each author on the site.
Tableau lets you go as deep as your data allows. For example, I can continue on to analyze things at the article level, too. In general, looking at this data should give the person responsible for editorial strategy enough information about the site’s history to chart its way forward.
Now, you can answer questions about how to maintain the site’s existing editorial strategy. You can answer questions like:
- How frequently do I need to publish?
- Which authors should I continue to promote?
- What categories of content should I focus on?
From here, the day-to-day publishing plans can go into a simple editorial calendar in a shared spreadsheet. For example, here’s an editorial calendar template for Google Docs that can be used as a starting point. For every article you intend to publish, this document captures the topic, the author, and the target publish date. The first tab sorts the editorial schedule by week. The second tab is for sites that publish less frequently. It sorts the editorial schedule by month. As content goes live, you can track progress over time by linking each planned piece of content to the actual published piece it becomes.
Overall, the editorial calendar will get you focused on publishing what you want, when you want, by the authors you want. The effort you put into analysis before you populate your editorial calendar will pay off in the long run because it will ensure that you’re charting your site’s future with an understanding of its past.