Is your content strategy hampered by poor or stagnant performance? Are you relying on shiny-tool syndrome, hoping that this week’s content marketing tactic will get you on the right track?
I call this Content Gambling: Creating content without a plan or expectation of results.
Content Gambling hurts your marketing effort because:
- Content Creation is labor intensive: Resources wasted pursuing topics that aren’t profitable
- Wastes time: Each piece requires hour of concentrated effort. This time could be better spent on different topics and tactics
- Poor Feedback: Lack of consistent and accurate feedback promotes mediocre quality and a status quo approach to creation
The only way to pull out of the Content Gambling death spiral is to take a systematic approach to creating and evaluating your content. We use an approach we’ve dubbed CAO or Content Analytics and Optimization. CAO is a systematic methodology for identifying, evaluating, and applying content performance insights to content production.
Content Analytics & Optimization: Key Activities
Our Content Analytics and Optimization approach is built on 4 activities:
#1: Focus on Leading Metrics
At Pushing Social, we concentrate on identifying and tracking Leading Metrics. Leading Metrics track completion of key activities that measure content production and deployments. Leading metrics are easy to identify but notoriously difficult to influence.
Examples of leading metrics include:
- Blog Post Outlines Submitted: How many outlines have been submitted by your team for editorial approval?
- Blog Posts Published: How many blog posts are published weekly?
- Social media updates scheduled: Aggregate number of social media updates across all social platforms?
- “Give versus Get” Retweet / Like Ratio: Number of third party links shared versus the number of promotional updates tweeted?
- Link Mentions Secured: How many 3rd party sites have agreed to link to content on your site?
Leading metrics are selected based on the deliverables needed to fulfill the content marketing strategy. Tracking leading metrics will pinpoint problems that could hurt overall content plan execution.
#2: Weekly Reviews
I recommend setting up two review meetings each week:
- Performance Review: Gather your key team members, pull your leading metrics and review looking for red flags.
- Experiment Review: Identify an area of improvement, define a hypothesis describing how the metric can be improved, devise an experiment to test your hypothesis. For example, one of our clients wanted to improve the number of social shares per post. Our hypothesis was: Readers are overlooking social share icons. Moving social share icons immediately after the headline would increase social shares. Experiment: Change the placement of icons for 3 days and measure results. (Note: The experiment worked)
These review meetings should be mandatory to create a culture of tough transparency (
#3: Rapid Content Experiment Deployment
Organize your content team around content production and content experimentation. Your content team should be able to deploy an experiment within 1-2 business days to quickly generate data for review at the next Experiment Review meeting.
#4: Test Then Rollout
Deploy content experiments to a representative sample of readers/visitors first. Review the results and decide if the experiment was a success. Immediately roll out successful experiments to the entire reader base.
How Test then Rollout works:
- Test: Placing a blog subscription call-to-action form after each blog posts.
- Set the goal: 1% reader to subscriber ratio
- Execution: If the blog has 3,000 visitors a month, the representative sample size would be 787 visitors. Place the new call-to-action form and keep a close eye on the number of visitors exposed to the new form. Remove the form once traffic reaches the sample size number. Review results. If the test hits the goal, rollout the form to the entire audience.
In many cases, plugins and conversion rate optimization (CRO) software can be used to easily deploy content experiments. We’ve used Visual Website Optimizer and were happy with the results.
Using this approach guards against burning the entire audience with a poorly performing experiment. For example,
How to Get Started with Content Analytics
1. Install and Configure Content Tracking
Use Google Analytics. It’s free and extremely powerful. WordPress users can use the Yoast Google Analytics plugin for quick installation.
2. Select 3 Leading Metrics
Your Leading Metrics will depend on your strategy. Many of our clients use content marketing to generate more sales qualified. In this case, the 3 Leading Metrics are: 1. Pre-Sell Content Published, 2. # of LinkedIn Updates, and 3. # of Pre-Sell SlideShare Presentations Published. (Pre-Sell = Content that diagnoses a problem and presents solutions aligned with the company’s approach and services)
4. Schedule 2 Weekly Meetings: Review and Experiments
Block out time on the team calendar. Make these meetings mandatory. Be prepared to bring the appropriate metric data to the meeting to maximize the team’s productivity. Set a goal to produce one hypothesis and content experiement each meeting.
5. Create and deploy 1 Experiment per Week
Success almost always comes down to execution. Offer the proper training, resources, and incentives to execute one content experiment per week. The most effective content marketing strategies quickly ramp up to 3-5 content experiments per week.
The Key to Success
Execute. That’s it. Most organizations fail to execute and blame their failure on the strategy. The winners focus on relentless execution.
Executing Content Analytics and Optimization isn’t easy. Most successful strategies require work, focus and investment, but that is the good news. Your competition may decide to look for the “silver bullet” and shun the work Content Analytics requires which is an opportunity for you.